Reviewer #2 (Public Review):

Dipasree Hajra et al demonstrated that Salmonella was able to modulate the expression of Sirtuins (Sirt1 and Sirt3) and regulate the metabolic switch in both host and Salmonella, promoting its pathogenesis. The authors found Salmonella infection induced high levels of Sirt1 and Sirt3 in macrophages, which were skewed toward the M2 phenotype allowing Salmonella to hyper-proliferate. Mechanistically, Sirt1 and Sirt3 regulated the acetylation of HIF-1alpha and PDHA1, therefore mediating Salmonella-induced host metabolic shift in the infected macrophages. Interestingly, Sirt1 and Sirt3-driven host metabolic switch also had an effect on the metabolic profile of Salmonella. Counterintuitively, inhibition of Sirt1/3 led to increased pathogen burdens in an in vivo mouse model. Overall, this is a well-designed study. There are a few comments below that would further strengthen the current study.

Major comments:<br /> In the in vivo study (lines 436-446) - the authors noticed increased pathogen burden in the EX-527 or the 3TYP-treated mice cohorts but decreased pathogen burden within the F4/80+ macrophage population. What are the other cell types that have increased pathogen burden in splenocytes from EX-527 or the 3TYP treated? Can this be further explored and explained?

While the authors indicated that IL-6 cytokine storm and elevated ROS production could result in bacterial dissemination in vivo, one could also argue that Sirt1/3 inhibitors might have an impact on gut function and/or gut microbiota (PMID: 22115311). Did Sirt1/3 inhibitors also lead to increased pathogen burdens in the gut? If so, the potential effect of these in vivo treatments on gut microbiota/colonization resistance should be discussed.

Minor comment:<br /> Sirt1 has been shown to be degraded during Salmonella infection (PMID: 28192515), which is different from the current study. An explanation should be provided for this.

Reviewer #3 (Public Review):

Summary:<br /> In this paper, Hajra et al have attempted to identify the role of Sirt1 and Sirt3 in regulating metabolic reprogramming and macrophage host defense. They have performed gene knockdown experiments in RAW macrophage cell lines to show that depletion of Sirt1 or Sirt3 enhances the ability of macrophages to eliminate Salmonella Typhimurium. However, in mice, inhibition of Sirt1 resulted in dissemination of the bacteria but the bacterial burden was still reduced in macrophages. They suggest that the effect they have observed is due to increased inflammation and ROS production by macrophages. They also try to establish a weak link with metabolism. They present data to show that the switch in metabolism from glycolysis to fatty acid oxidation is regulated by acetylation of Hif1a, and PDHA1.

Strengths:<br /> The strength of the manuscript is that the role of Sirtuins in host-pathogen interactions has not been previously explored in-depth making the study interesting. It is also interesting to see that depletion of either Sirt1 or Sirt3 results in a similar outcome.

Weaknesses:<br /> The major weakness of the paper is the low quality of data, making it harder to substantiate the claims. Also, there are too many pathways and mechanisms being investigated. It would have been better if the authors had focussed on either Sirt1 or Sirt3 and elucidated how it reprograms metabolism to eventually modulate host response against Salmonella Typhimurium. Experimental evidence is also lacking to prove the proposed mechanisms. For instance, they show correlative data that the knockdown of Sirt1-mediated shift in metabolism is due to HIF1a acetylation but this needs to be proven with further experiments.

Reviewer #1 (Public Review):

The manuscript by Sun and colleagues followed on their previous findings on the tumor suppressive role of PDLIM2 in lung cancer. They further investigated various mechanisms, including epigenetic modification, copy number variation and LOH, that led to the decrease expression of PDLIM2 in human lung cancer. Next, they used nanoparticle-based approach to specifically restore the expression in mouse lung tumors. They showed that over-expression PDLIM2 in lung cancer repressed its progression in vivo. Also, this treatment could synergize with chemotherapy and checkpoint inhibitor anti-PD-1. Overall, the results were quite promising and convincing, using a treatment combination that would appear to have potential for clinical implementation.

Reviewer #2 (Public Review):

Summary: The authors have previously demonstrated that the E3 ligase PDLIM2 inhibits NF-kB and STAT3 and is epigenetically repressed in human lung cancers (Sun et al. Nat. Comm. 2019 10: 5324); therefore, PDLIM2 is a tumor suppressor in lung cancer. In this manuscript, they follow up on their previous findings and show that expression of PDLIM2 is downregulated in human lung cancers by both genetic deletion and promoter methylation. They further describe a novel approach to restore the expression of PDLIM2 in mouse lung tumors by systemically administering PDLIM2 plasmids encapsulated in nanoparticles (termed "nanoPDLIM2"). The nanoPDLIM2 approach was shown to exhibit efficacy with low toxicity in a urethane-induced mouse lung cancer model. The authors further demonstrated synergy of nanoPDLIM2 with chemotherapy and PD-1 blockade immunotherapy. The combination therapy of nanoPDLIM2, chemotherapy and immunotherapy proved most effective with complete tumor remission in 60% of mice. Mechanistically, nanoPDLIM2 upregulated MHC-I expression, enhanced CD4/CD8 T cell activation and tumor infiltration, and suppressed MDR1 induction and nuclear expression of STAT3, RelA and prosurvival genes in tumors. Overall, this study is important because it reinforces the critical roles of PDLIM2 in suppressing lung cancer, and also identifies a potential approach to restoring PDLIM2 expression in lung tumors. The experiments were well executed; the data are convincing and support the conclusions made by the authors.

Reviewer #2 (Public Review):

Summary:<br /> The authors present a report of a large Pseudomonas aeruginosa hospital outbreak affecting more than 80 patients with first sampling dates in 2011 that stretched over more than 10 years and was only identified through genomic surveillance in 2020. The outbreak strain was assigned to the sequence type 621, an ST that has been associated with carpabapenem resistance across the globe. Ongoing transmission coincided with both increasing resistance without acquisition of carbapenemase genes as well as the convergence of mutations towards a host-adapted lifestyle.

Strengths:<br /> The convincing genomic analyses indicate spread throughout the hospital since the beginning of the century and provide important benchmark findings for future comparison.

The sampling was based on all organisms sent to the Multidrug-resistant Organism Repository and Surveillance Network across the U.S. Military Health System.

Using sequencing data from patient and environmental samples for phylogenetic and transmission analyses as well as determining recurring mutations in outbreak isolates allows for insights into the evolution of potentially harmful pathogens with the ultimate aim of reducing their spread in hospitals.

Weaknesses:<br /> The epidemiological information was limited and the sampling methodology was inconsistent, thus complicating the inference of exact transmission routes. Epidemiological data relevant to this analysis include information on the reason for sampling, patient admission and discharge data, and underlying frequency of sampling and sampling results in relation to patient turnover.

Reviewer #3 (Public Review):

Summary:<br /> This paper by Stribling and colleagues sheds light on a decade-long P. aeruginosa outbreak of the high-risk lineage ST-621 in a US Military hospital. The origins of the outbreak date back to the late 90s and it was mainly caused by two distinct subclones SC1 and SC2. The data of this outbreak showed the emergence of antibiotic resistance to cephalosporin, carbapenems, and colistin over time highlighting the emerging risk of extensively resistant infections due to P. aeruginosa and the need for ongoing surveillance.

Strengths:<br /> This study overall is well constructed and clearly written. Since detailed information on floor plans of the building and transfers between facilities was available, the authors were able to show that these two subclones emerged in two separate buildings of the hospital. The authors support their conclusions with prospective environmental sampling in 2021 and 2022 and link the role of persistent environmental contamination to sustaining nosocomial transmission. Information on resistance genes in repeat isolates for the same patients allowed the authors to detect the emergence of resistance within patients. The conclusions have broader implications for infection control at other facilities. In particular, the paper highlights the value of real-time surveillance and environmental sampling in slowing nosocomial transmission of P. aeruginosa.

Weaknesses:<br /> My major concern is that the authors used fixed thresholds and definitions to classify the origin of an infection. As such, they were not able to give uncertainty measures around transmission routes nor quantify the relative contribution of persistent environmental contamination vs patient-to-patient transmission. The latter would allow the authors to quantify the impact of certain interventions. In addition, these results represent a specific US military facility and the transmission patterns might be specific to that facility. The study also lacked any data on antibiotic use that could have been used to relate to and discuss the temporal trends of antimicrobial resistance.

Reviewer #2 (Public Review):

Summary:<br /> In this work, Hu and colleagues investigate telomerase-independent survival in Saccharomyces cerevisiae strains engineered to have different chromosome numbers. The authors describe the molecular patterns of survival that change with fewer chromosomes and that differ from the well-described canonical Type I and Type II, including chromosome circularization and other atypical outcomes. They then take advantage of the strain with 3 chromosomes to examine the effect of deleting all the subtelomeric elements, called X and Y'. For most of the tested phenotypes, they find no significant effect of the absence of X- and Y'-element, and show that they are not essential for survivor formation. They speculate that X- and Y'-elements are remnants of ancient telomere maintenance mechanisms.

Strengths:<br /> This work advances our understanding of the telomerase-independent strategies available to the cell by altering the structure of the genome and of the subtelomeres, a feat that was enabled by the set of strains they engineered previously. By using strains with non-standard genome structures, several alternative survival mechanisms are uncovered, revealing the diversity and plasticity of telomere maintenance mechanisms. Overall, the conclusions are well supported by the data, with adequate sample sizes for investigating survivors. The assessment of the genetic requirements for survivors in strains with different chromosome numbers greatly improved the quality of this work. The molecular analyses based on Southern blots are also very well-conducted.

Weaknesses:<br /> The authors discovered alternative telomerase-independent survival strategies beyond the well-described type I and II (including circularization, type X and atypical, as they called them) at play in the context of reduced number of chromosomes. Their work provides a molecular and a partial genetic characterization of these survival pathways. A more thorough analysis of the frequency of each type of survivors and their genetic requirements would have advanced our understanding or the diversity of survival strategies in the absence of telomerase. However, as noted by the authors, the quantification of the rate of emergence of survivors (and their subtypes) is very difficult to achieve. This comment is therefore not meant as a criticism but rather as a perspective on exciting future research avenues.

Reviewer #3 (Public Review):

This study investigates subtelomeric repetitive sequences in the budding yeast Saccharomyces cerevisiae, known as Y' and X-elements. Taking advantage of yeast strain SY12 that contains only 3 chromosomes and six telomeres (normal yeast strains contain 32 telomeres) the authors are able to generate a strain completely devoid of Y'- and X-elements.

Strengths: They demonstrate that the SY12 delta XY strain displays normal growth, with stable telomeres of normal length that were transcriptionally silenced, a key finding with wide implications for telomere biology. Inactivation of telomerase in the SY12 and SY12 delta XY strains frequently resulted in survivors that had circularized all three chromosomes, hence bypassing the need for telomeres altogether. They show that survivors with fused chromosomes and so-called atypical survivors arise independently of the central recombination protein Rad52. The SY12 and SY12 delta XY yeast strains can become a useful tool for future studies of telomere biology. The conclusions of this manuscript are well supported by the data and are valuable for researchers studying telomeres.

Weaknesses: A weakness of the manuscript is the analysis of telomere transcriptional silencing. They state: "The results demonstrated a significant increase in the expression of the MPH3 and HSP32 upon Sir2 deletion, indicating that telomere silencing remains effective in the absence of X and Y'-elements". However, for the SY12 strain, their analyses indicate that the difference between the WT and sir2 strains is nonsignificant. In addition, a striking observation is that the SY12 strain (with only three chromosomes) express much less of both MPH3 and HSP32 than the parental strain BY4742 (16 chromosomes), both in the presence and absence of Sir2.

Reviewer #3 (Public Review):

The authors have done a fine job of updating the manuscript and it is substantially improved. In particular, the paragraphs towards the end of the Introduction and Discussion are vastly improved. The last paragraph of the Introduction now clearly explicates the hypotheses (save one minor point of confusion). The limitations section of the Discussion is also very helpful and fair. However, there are still areas where claims need to be tempered.

Major criticisms<br /> • The results still do not lead to the conclusion that the angular gyrus is causally involved in insight-driven memory configuration. Although the authors do state that other regions such as the hippocampus may have contributed to the pattern of results, there is still no evidence of target engagement or a link between target engagement and the behavioral results. Thus, while the results support that cTBS to the angular gyrus affects insight-driven memory configuration, it is a strong overstep to say that the angular gyrus is causally involved in insight-driven memory reconfiguration. In particular, this applies to both the title and the last line of the Abstract. In relation to this, have the authors conducted any target engagement analyses? It seems like a good starting point would be to identify the censor closest to the stimulation site in each individual, Hjorth transforms the signal of that sensor by subtracting the average of the surrounding sensors to increase signal localization, and then measure the effects of stimulation on theta power. Presumably, we would expect that cTBS would decrease theta power relative to sham stimulation. Although this isn't the only type of analysis that could at least partially confirm target engagement, there needs to be some sort of formal analysis to maintain the claims of the title and last line of the Abstract.<br /> • The authors removed the mentions of "inhibitory stimulation" from the manuscript to their credit, but a rigorous and fair treatment of the effects of cTBS is still lacking, and it is still unclear why cTBS to the angular gyrus would cause an inhibitory effect in the first place. The authors state that

"Previous evidence has demonstrated the inhibitory effect of cTBS on the targeted brain region under stimulation (Huang et al., 2005; Jannati et al., 2023). Nonetheless, the effects of cTBS appear to vary based on the targeted region, with cTBS to parietal regions demonstrating the capability to enhance hippocampal connectivity (Hermiller et al., 2019, 2020)."

The inhibitory effects of motor cortex cTBS s on corticospinal excitability in nine subjects from the Huang paper and the Jannati review (not a primary source) do not constitute sufficient evidence to hypothesize an inhibitory effect on insight-driven memory reconfiguration. The second sentence provides much more sufficient evidence that parietal stimulation should have some sort of a facilitatory effect, but this is simply glossed over without an explanation of why cTBS to the parietal cortex should inhibit insight-driven memory reconfiguration. Pilot data showing such inhibitory effects or a body of evidence showing inhibitory effects of angular gyrus stimulation on closely-related areas of cognition would have given reason to believe this. However, without these, an a priori assumption that parietal cTBS would be inhibitory seems highly debatable and paints the results as provisional, rather than confirmatory"

Reviewer #3 (Public Review):

The findings of Bo Yu and colleagues titled "Identification of fallopian tube microbiota and its association with ovarian cancer: a prospective study of intraoperative swab collections from 187 patients" describes the identification of the fallopian tube microbiome and relationship with ovarian cancer. The studies are highly rigorous obtaining specimens from the fallopian tube, ovarian surfaces, paracolic gutter of patients of known or suspected ovarian cancer or benign tumor patients. The investigators took great care to insure there was no or limited contamination including test the surgical suite air, as the test locations are from low abundance microbiota. The findings provide evidence that the microbiota in the fallopian tube, especially in ovarian cancer has similarities to gut microbial communities. This is a potentially novel observation.

The studies investigate the microbiome of >1000 swabs from 81 ovarian cancer and 106 non-cancer patients. The sites collected are low biomass microbiota making the study particularly challenging. The studies provide descriptive evidence that the ovarian cancer fallopian tube microbiota contain species that are similar to the gut microbiota. In contrast the fallopian tube microbiota of non-cancer patients that exhibit more similarity to the uterine/cervical microbiota. This may be a relevant observation but is highly descriptive with limited insights on the functional relevance.

The data indicate the presence of low biomass FT microbiota. The findings support the existence of FT microbiota in ovarian cancer that appears to be related to gut microbial species. While interesting, there is no insights on how and why these microbial species are found in the FT. The studies only identify the species but there is no transcriptomic analysis to provide an indication on whether the bacteria are activating DNA damage pathways. This is an interesting observation that requires more insights to address how these bacteria reach the fallopian tube and a related question is whether these bacteria are found in the peritoneum.

An additional concern is whether these data can be used to develop biomarkers of disease and early detection of disease.

Reviewer #1 (Public Review):

In the article "Temporal transcriptomic dynamics in developing macaque neocortex", Xu et al. analyze the cellular composition and transcriptomic profiles of the developing macaque parietal cortex using single-cell RNA sequencing. The authors profiled eight prenatal rhesus macaque brains at five timepoints (E40, E50, E70, E80, and E90) and obtained a total of around 53,000 high-quality cells for downstream analysis. The dataset provides a high-resolution view into the developmental processes of early and mid-fetal macaque cortical development and will potentially be a valuable resource for future comparative studies of primate neurogenesis and neural stem cell fate specification. Their analysis of this dataset focused on the temporal gene expression profiles of outer and ventricular radial glia and utilized pesudotime trajectory analysis to characterize the genes associated with radial glial and neuronal differentiation. The rhesus macaque dataset presented in this study was then integrated with prenatal mouse and human scRNA-seq datasets to probe species differences in ventricular radial glia to intermediate progenitor cell trajectories. Additionally, the expression profile of macaque radial glia across time was compared to those of mouse apical progenitors to identify conserved and divergent expression patterns of transcription factors.

The main findings of this paper corroborate many previously reported and fundamental features of primate neurogenesis: deep layer neurons are generated before upper layer excitatory neurons, the expansion of outer radial glia in the primate lineage, conserved molecular markers of outer radial glia, and the early specification of progenitors. Furthermore, the authors show some interesting divergent features of macaque radial glial gene regulatory networks as compared to mouse. Overall, despite some uncertainties surrounding the clustering and annotations of certain cell types, the manuscript provides a valuable scRNA-seq dataset of early prenatal rhesus macaque brain development. The dynamic expression patterns and trajectory analysis of ventricular and outer radial glia provide valuable data and lists of differentially expressed genes (some consistent with previous studies, others reported for the first time here) for future studies.

Reviewer #1 (Public Review):

Summary<br /> Liao et al leveraged two powerful genomics techniques-CUT&RUN and RNA sequencing-to identify genomic regions bound by and activated or inactivated by SMAD1, SMAD5, and the progesterone receptor during endometrial stromal cell decidualization. Additionally, the authors generated novel knock-in HA-SMAD1 and PA-SMAD5 tagged mice to combat antibody issues facing the field, generating a novel model to advance the study of BMP signaling in the female reproductive tract. During decidualization in a murine model, SMAD1/5 are bound to many genomic sites of genes important in decidualization and pregnancy and coregulated responses with progesterone receptor signaling.

Strengths<br /> The authors utilized powerful next generation sequencing and identified important transcriptional mechanisms of SMAD1/5 and PGR during decidualization in vivo.

Weaknesses<br /> None.

Overall, the manuscript and study are well structured and provide critical mechanistic updates on the roles of SMAD1/5 in decidualization and preparation of the maternal endometrium for pregnancy.

Reviewer #2 (Public Review):

Summary:<br /> Liao and colleagues generated tagged SMAD1 and SMAD5 mouse models and identified genome occupancy of these two factors in the uterus of these mice using the CUT&RUN assay. The authors used integrative bioinformatic approaches to identify putative SMAD1/5 direct downstream target genes and to catalog the SMAD1/5 and PGR genome co-localization pattern. The role of SMAD1/5 on stromal decidualization was assayed in vitro on primary human endometrial stromal cells. The new mouse models offer opportunities to further dissect SMAD1 and SMAD5 functions without the limitation from SMAD antibodies, which is significant. The CUT&RUN data further support the usefulness of these mouse models for this purpose.

Strengths:<br /> The strength of this study is the novelty of new mouse models and the valuable cistromic data derived from these mice. Overall the present manuscript is an excellent resource paper for the field of reproductive biology.

Weaknesses:<br /> The weakness of the present version of the manuscript includes the self-limited data analysis approaches such as the proximal promoter based bioinformatic filter and an outdated method on inferring the cell type composition. Evidence was provided for potential associations between SMAD1/5 and other major transcription factors. However, causal effects of SMAD1/5 on the genome occupancy of other major uterine transcription factors were discussed but not experimentally examined in the present manuscript, which is understandable.

For data in Figure 2B, the current manuscript fails to elaborate the common and distinct features between clusters 1 and 3 as well as the biological significance of having two separate clusters for SMAD1. In addition, Figure S1A shows overlapping genome occupancy between SMAD1 and SMAD5, which is not clearly demonstrated in Figure 2B.

For data in Figure 5A, the result description does not provide adequate information to guide readers to full understanding of the data. The biological meaning behind the three PR clusters is not stated nor speculated. Moreover, Figure 5A and Figure S1B are inherently connected but fail to be adequately described in the main text.

Reviewer #3 (Public Review):

Summary:<br /> As SMAD1/5 activities have previously been indistinguishable, these studies provide a new mouse model to finally understand unique downstream activation of SMAD1/5 target genes, a model useful for many scientific fields. Using CUT&RUN analyses with gene overlap comparisons and signaling pathway analyses, specific targets for SMAD1 versus SMAD5 were compared, identified, and interpreted. These data validate previous findings showing strong evidence that SMADs directly govern critical genes required for endometrial receptivity and decidualization, including cell adhesion and vascular development. Further, SMAD targets were overlapped with progesterone receptor binding sites to identify regions of potential synergistic regulation of implantation. The authors report strong correlations between progesterone receptor and SMAD1/5 direct targets to cooperatively promote embryo implantation. Finally, the authors validated SMAD1/5 gene regulation in primary human endometrial stromal cells. These studies provide a data-rich survey of SMAD family transcription, defining its role as a governor of early pregnancy.

Strengths:<br /> This manuscript provides a valuable survey of SMAD1/5 direct transcriptional events at the time of receptivity. As embryo implantation is controlled by extensive epithelial to stromal molecular crosstalk and hormonal regulation in space and time, the authors state a strong, descriptive narrative defining how SMAD1/5 plays a central role at the site of this molecular orchestration. The implementation of cutting-edge techniques and models and simple comparative analyses provide a straightforward, yet elegant manuscript.

Although the progesterone receptor exists as a major regulator of early pregnancy, the authors have demonstrated clear evidence that progesterone receptor with SMAD1/5 work in concert to molecularly regulate targets such as Sox17, Id2, Tgfbr2, Runx1, Foxo1 and more at embryo implantation. Additionally, the authors pinpoint other critical transcription factor motifs that work with SMADs and the progesterone receptor to promote early pregnancy transcriptional paradigms.

Weaknesses:

Although a wonderful new tool to ascertain SMAD1 versus SMAD5 downstream signaling, the importance of these factors in governing early pregnancy is not novel. Furthermore, functional validation studies are needed to confirm interactions at promoter regions. Additionally, the authors presume that all overlapped genes are shared between progesterone receptor and SMAD1/5, yet some peak representations do not overlap. Although, transcriptional activation can occur at the same time, they may not occur in the same complex. Thus, further confirmation of these transcriptional events is warranted.

Since whole murine uterus was used for these studies, the specific functions of SMAD1/5 in the stroma versus the epithelium (versus the myometrium) remain unknown. Further work is needed to delineate binding and transcriptional activation of SMAD1/5 and the progesterone receptor in the uterine compartments.

There are asynchronous gene responses in the SMAD1/5 ablated mouse model compared to the siRNA-treated human endometrial stromal cells. These differences can be confounding. Further investigation is needed to understand the meaning of these differences and as they relate to the entire SMAD transcriptome.

Reviewer #1 (Public Review):

Summary:<br /> This paper conducted a GWAS meta-analysis for COVID-19 hospitalization among admixed American populations. The authors identified four genome-wide significant associations, including two novel loci (BAZ2B and DDIAS), and an additional risk locus near CREBBP using cross-ancestry meta-analysis. They utilized multiple strategies to prioritize risk variants and target genes. Finally, they constructed and assessed a polygenic risk score model with 49 variants associated with critical COVID-19 conditions.

Strengths:<br /> Given that most of the previous studies were done in European ancestries, this study provides unique findings about the genetics of COVID-19 in admixed American populations. The GWAS data would be a valuable resource for the community. The authors conducted comprehensive analyses using multiple different strategies, including Bayesian fine mapping, colocalization, TWAS, etc., to prioritize risk variants and target genes. The polygenic risk score (PGS) result demonstrated the ability of the cross-population PGS model for COVID-19 risk stratification.

Weaknesses:<br /> 1. One of the major limitations of this study is that the GWAS sample size is relatively small, which limits its power.

2. The fine mapping section is unclear and there is a lack of information. The authors assumed one causal signal per locus, and only provided credible sets, but did not provide posterior inclusion probabilities (PIP) for the variants to be causal.

3. Colocalization and TWAS used eQTL data from GTEx data, which are mainly from European ancestries. It is unclear how much impact the ancestry mismatch would have on the result. The readers should be cautious when interpreting the results and designing follow-up studies.

Reviewer #2 (Public Review):

This is a genome-wide association study of COVID-19 in individuals of admixed American ancestry (AMR) recruited from Brazil, Colombia, Ecuador, Mexico, Paraguay, and Spain. After quality control and admixture analysis, a total of 3,512 individuals were interrogated for 10,671,028 genetic variants (genotyped + imputed). The genetic association results for these cohorts were meta-analyzed with the results from The Host Genetics Initiative (HGI), involving 3,077 cases and 66,686 controls. The authors found two novel genetic loci associated with COVID-19 at 2q24.2 (rs13003835) and 11q14.1 (rs77599934), and other two independent signals at 3p21.31 (rs35731912) and 6p21.1 (rs2477820) already reported as associated with COVID-19 in previous GWASs. Additional meta-analysis with other HGI studies also suggested risk variants near CREBBP, ZBTB7A, and CASC20 genes.

Strengths:<br /> These findings rely on state-of-the-art methods in the field of Statistical Genomics and help to address the issue of a low number of GWASs in non-European populations, ultimately contributing to reducing health inequalities across the globe.

Weaknesses:<br /> There is no replication cohort, as acknowledged by the authors (page 29, line 587), and no experimental validation to assess the biological effect of putative causal variants/genes. Thus, the study provides good evidence of association, rather than causation, between the genetic variants and COVID-19. Lastly, I consider it crucial to report the results for the SCOURGE Latin American GWAS, in addition to its meta-analysis with HGI results, since HGI data has a different phenotype scheme (Hospitalized COVID vs Population) compared to SCOURGE (Hospitalized COVID vs Non-hospitalized COVID).

Reviewer #3 (Public Review):

Summary:<br /> In the context of the SCOURGE consortium's research, the authors conduct a GWAS meta-analysis on 4,702 hospitalized individuals of admixed American descent suffering from COVID-19. This study identified four significant genetic associations, including two loci initially discovered in Latin American cohorts. Furthermore, a trans-ethnic meta-analysis highlighted an additional novel risk locus in the CREBBP gene, underscoring the critical role of genetic diversity in understanding the pathogenesis of COVID-19.

Strengths:<br /> 1. The study identified two novel severe COVID-19 loci (BAZ2B and DDIAS) by the largest GWAS meta-analysis for COVID-19 hospitalization in admixed Americans.

2. With a trans-ethnic meta-analysis, an additional risk locus near CREBBP was identified.

Weaknesses:<br /> 1. The GWAS power is limited due to the relatively small number of cases.

2. There is no replication study for the novel severe COVID-19 loci, which may lead to false positive findings.

3. Significant differences exist in the ages between cases and controls, which could potentially introduce biased confounders. I'm curious about how the authors treated age as a covariate. For instance, did they use ten-year intervals? This needs clarification for reproducibility.

4."Those in the top PGS decile exhibited a 5.90-fold (95% CI=3.29-10.60, p=2.79x10-9) greater risk compared to individuals in the lowest decile". I would recommend comparing with the 40-60% PGS decile rather than the lowest decile, as the lowest PGS decile does not represent 'normal controls'.

5. In the field of PGS, it's common to require an independent dataset for training and testing the PGS model. Here, there seems to be an overfitting issue due to using the same subjects for both training and testing the variants.

6. The variants selected for the PGS appear arbitrary and may not leverage the GWAS findings without an independent training dataset.

7. The TWAS models were predominantly trained on European samples, and there is no replication study for the findings as well.

Reviewer #3 (Public Review):

Summary:

This study uses a state-of-the-art artificial skin assay to determine the quantity of P. falciparum sporozoites expelled during feeding using mosquito infection (by standardised membrane feeding assay SMFA) using both cultured gametocytes and natural infection. Sporozoite densities in salivary glands and expelled into the skin are quantified using a well-validated molecular assay. These studies show clear positive correlations between mosquito infection levels (as determined by oocyst numbers), sporozoite numbers in salivary glands, and sporozoites expelled during feeding. This indicates potentially significant heterogeneity in infectiousness between mosquitoes with different infection loads and thus challenges the often-made assumption that all infected mosquitoes are equally infectious.

Strengths:

Very rigorously designed studies using very well validated, state-of-the-art methods for studying malaria infections in the mosquito and quantifying load of expelled sporozoites. This resulted in very high-quality data that was well-analyzed and presented. Both sources of gametocytes (cultures vs. natural infection) show consistent results further strengthening the quality of the results obtained.

Weaknesses:

As is generally the case when using SMFAs, the mosquito infections levels are often relatively high compared to wild-caught mosquitoes (e.g. Bombard et al 2020 IJP: median 3-4 ), and the strength of the observed correlations between oocyst sheet and salivary gland sporozoite load even more so between salivary gland sporozoite load and expelled sporozoite number may be dominated by results from mosquitoes with infection levels rarely observed in wild-caught mosquitoes. This could result in an overestimation of the importance of these well-observed positive relationships under natural transmission conditions.

The results obtained from these excellently designed and executed studies very well supported their conclusion - with a slight caveat regarding their application to natural transmission scenarios

This work very convincingly highlights the potential for significant heterogeneity in the infectiousness between individual P. falciparum-infected mosquitoes. Such heterogeneity needs to be further investigated and if again confirmed taken into account both when modelling malaria transmission and when evaluating the importance of low-density infections in sustaining malaria transmission.

eLife assessment

This is an important study on DNA gyrase that provides further evidence for its mode of action via a double-stranded DNA break and against a recently-proposed alternative mechanism. The evidence presented is solid and is derived from state-of-the-art techniques. The work casts new light on the interactions that occur between gyrase molecules and will be of interest to biochemists and cell biologists.

Reviewer #1 (Public Review):

Germe and colleagues have investigated the mode of action of bacterial DNA gyrase, a tetrameric GyrA2GyrB2 complex that catalyses ATP-dependent DNA supercoiling. The accepted mechanism is that the enzyme passes a DNA segment through a reversible double-stranded DNA break formed by two catalytic Tyr residues-one from each GyrA subunit. The present study (now described in a revised manuscript) sought to understand an intriguing earlier observation that gyrase with a single catalytic tyrosine that cleaves a single strand of DNA, nonetheless has DNA supercoiling activity. This unexpected finding led to the proposal that gyrase acts instead via a nicking closing mechanism. Germe et al used bacterial co-expression to make the wild-type and mutant heterodimeric BA(fused).A complexes with only one catalytic tyrosine. Whether the Tyr mutation was on the A side or BA fusion side, both complexes plus GyrB reconstituted fluoroquinolone-stabilised double-stranded DNA cleavage and DNA supercoiling activity. This indicates that the preparations of these complexes sustain double strand DNA passage as envisaged in the current double-strand break mechanism of gyrase. Of possible explanations for how double-strand cleavage arises, contamination of heterodimeric complexes or GyrB with GyrA dimers was ruled unlikely by the meticulous prior analysis of the proteins on native Page gels, by analytical gel filtration and by mass photometry (although low levels of endogenous GyrA were seen in some preparations). Involvement of an alternative nucleophile on the Tyr-mutated protein was ruled out by analysis of mutagenesis studies focused on the catalytic ArgTyrThr triad of residues. Similarly, analysis of 5'- and 3'- DNA ends generated by cleavage ruled out water as a nucleophile. Instead, results of the present study favour a third explanation wherein double-strand DNA breakage arises as a consequence of subunit (or interface/domain) exchange. The authors showed that although the A subunits in the GyrA dimer were thought to be tightly associated, addition of GyrB to heterodimers with one catalytic tyrosine stimulated DNA cleavage with a time lag consistent with rapid DNA-dependent subunit or interface exchange to generate complexes with two catalytic tyrosines capable of double-stranded DNA breakage. Subunit exchange between heterodimeric complexes was facilitated by DNA bending and wrapping by gyrase, by the ability of both GyrA and GyrB to form higher order aggregates and by dense packing of gyrase complexes on DNA. By addressing a puzzling paradox, this study provides further support for the accepted double strand break (strand passage) mechanism of gyrase (without having to invoke a nicking-closing mechanism) and opens new insights on subunit exchange that may have biological significance in promoting DNA recombination and genome evolution.

The conclusions of the work are mostly well supported by the experimental data. Moreover, in the revised manuscript, the various concepts, experiments and outcomes are better explained and more accessible to the reader through a reorganised text, clearer figures and an extended Supplementary section.

Strengths:

The study examines a fundamental biological question, namely the mechanism of DNA gyrase, an essential and ubiquitous enzyme in bacteria, and the target of fluoroquinolone antimicrobial agents.

The experiments have been carefully done and the analysis of their outcomes is comprehensive, thoughtful and considered.

The work uses an array of complementary techniques to characterize preparations of GyrA, GyrB and various gyrase complexes. In this regard, mass photometry seems particularly useful. Analysis revealed that purified GyrA and GyrB can each form multimeric complexes and highlights the complexities involved in investigating the gyrase system.

The various possible explanations for the double-strand DNA breakage by gyrase heterodimers with a single catalytic tyrosine are considered and addressed by appropriate experiments.

The study highlights the potential biological importance of interactions between gyrase complexes through domain-or subunit-exchange.

Reviewer #2 (Public Review):

DNA gyrase is an essential enzyme in bacteria that regulates DNA topology and has the unique property to introduce negative supercoils into DNA. This enzyme contains 2 subunits GyrA and GyrB, which forms an A2B2 heterotetramer that associates with DNA and hydrolyzes ATP. The molecular structure of the A2B2 assembly is composed of 3 dimeric interfaces, called gates, which allow the cleavage and transport of DNA double stranded molecules through the gates, in order to perform DNA topology simplification.<br /> The article by Germe et al. questions the existence and possible mechanism for subunit exchange in the bacterial DNA gyrase complex.

The complexes are purified as a dimer of GyrA and a fusion of GyrB and GyrA (GyrBA), encoded by different plasmids, to allow the introduction of targeted mutations on one side only of the complex. The conclusion drawn by the authors is that subunit exchange does happen in vitro, favored by DNA binding and wrapping. They propose that the accumulation of gyrase in higher-order oligomers can favor rapid subunit exchange between two active gyrase complexes brought into proximity. This study is nicely illustrated with diagrams that explain the possible mechanism.

The authors are also debating the conclusions of a previous article by Gubaev, Weidlich et al 2016 (https://doi.org/10.1093/nar/gkw740). Gubaev et al. originally used this strategy of complex reconstitution to propose a nicking-closing mechanism for the introduction of negative supercoils by DNA gyrase, an alternative mechanism that precludes DNA strand passage, previously established in the field. Germe et al. propose that the detected negative supercoiling activity in this earlier study may be due to the subunit swapping of the recombinant protein with the endogenous enzyme.

Strengths

The mix of gyrase subunits is plausible, this mechanism has been suggested by Ideka et al, 2004 and also for the human Top2 isoforms with the formation of Top2a/Top2b hybrids being identified in HeLa cells (doi: 10.1073/pnas.93.16.8288).<br /> Germe et al have used extensive and solid biochemical experiments, together with thorough experimental controls, involving :<br /> - the purification of gyrase subunits including mutants with domain deletion, subunit fusion or point mutations.<br /> - DNA relaxation, cleavage and supercoiling assays<br /> - biophysical characterization in solution (size exclusion chromatography, mass photometry, mass spectrometry)

Together the combination of experimental approaches provides convincing evidence for subunit swapping in gyrase in vitro, despite the technical limitations of standard biochemistry applied to such a complex macromolecule.

Weaknesses

The conclusions of this study could be strengthened by in vivo data to identify subunit swapping in the bacteria. Indeed, if shown in vivo, together with this biochemical evidence, this mechanism could have a substantial impact on our understanding of bacterial physiology and resistance to drugs. These in vivo perspectives are beyond the scope of the present in vitro investigation but are however explained by the authors.

Reviewer #2 (Public Review):

Summary:

The study provides valuable and compelling evidence that while activation of the mTOR cascade confers some similarities in alterations in cell size, mTOR pathway activation, cortical lamination, baseline firing properties, and synaptic activity, there are distinctions that could account for clinical differences in seizure and epilepsy phenotypes in patients harboring these mutations. These findings could have important implications going forward as we design clinical therapeutic strategies to modulate mTOR activity in these individuals to treat seizures.

This study presents a valuable finding on the role that distinct mTOR pathway genes play in altered cell shape, cortical laminar migration, and cellular excitability in the mouse medial prefrontal cortex (mPFC). The evidence supporting the claims of the authors is solid, although analysis of the role of the mTORC2 pathway and consideration of distinct metabolic states i.e., amino acid levels would have strengthened the study. The work will be of interest to neuroscientists working on human epilepsy. These genes have each been assayed in previous independent studies and thus the direct comparison is what provides the innovation and interest.

The manuscript by Nguyen and colleagues attempts to define both the common and differential roles of mTOR pathway genes, both by gene knockout (KO) and activation, on cortical neuronal size, cortical lamination, and excitability. They focused on 5 genes that have been linked to human malformations of cortical development (MCD) and epilepsy: RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO. The RhebY35L, mTORS2215Y are known and pathogenic human gain-of-function variants. Each of these genes is known to modulate the activity of mTORC1 and either KO or activation will lead to abnormal and persistent hyperactivation of mTOR activity. Using in utero electroporation they transfected plasmids containing these gene constructs into fetal mouse brains at E15.5 and then assessed neuronal shape and size, laminar positioning, spontaneous activity, synaptic activity, and expression of a novel voltage-gated potassium channel (HCN4) at varying time postnatally e.g., P7-9 (neonates) and P28-43 (young adults).

The study clearly achieves its stated aims i.e., that disruption of each of five distinct mTOR pathway genes, Rheb, mTOR, Depdc5, Pten, and Tsc1, individually impacts pyramidal neuron development and electrophysiological function in the mouse mPFC. The data from each of the 5 genes provides strong support to the notion that mTOR pathway gene mutations yield the unifying clinical parcellation of mTORopathies, likely as a consequence of mTOR pathway activation. The data also provide interesting evidence that subtle or even overt differences in clinical phenotypes between RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO in humans could be due to effects of these genes either on mTOR or on yet to be defined alternative pathways. Assuredly follow-up studies to examine how Rheb, mTOR, Dedpdc5, Pten, and Tsc1 engage with other protein binding partners or other pathways will be warranted in future studies.

Strengths:

The investigators demonstrate that gene KO or activation leads to common changes in cell size (enlargement) though with different effects across each gene subtype suggesting distinct genetic effects despite a common effect on mTOR signaling. The major effect was seen in forebrain neurons expressing mTORS2215Y. They also report gene-specific effects of each mTOR pathway gene on cortical lamination. For example, while RhebY35L, mTORS2215Y, Dedpdc5KO, and Tsc1KO significantly disrupted laminar positioning of neurons in layer 2/3, PtenKO had minimal effects on laminar positioning. This finding is intriguing since it means that simply activating mTOR during fetal brain development will not necessarily alter cortical lamination and that an increase in cell size by itself doesn't disrupt laminar fidelity. To verify that the expression of plasmids led to mTORC1 hyperactivation, phosphorylated levels of S6 (i.e., p-S6), a downstream substrate of mTORC1, were assayed by immunohistochemistry in P28-43 mice. Expression of the RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO plasmids all led to significantly increased p-S6 staining intensity, supporting that the expression of each of these plasmids leads to increased mTORC1 signaling.

Whole-cell current- and voltage-clamp recordings were performed in P25-P51 mice in acute brain slice preparations. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to decreased depolarization-induced excitability, but only RhebY35L, mTORS2215Y, and Tsc1KO expression led to depolarized resting membrane potentials. Interestingly, expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to the abnormal presence of HCN4 channels with variations in functional expression suggesting a common cellular mechanism that could confer excitability. Treatment with rapamycin, an mTOR inhibitor, reversed the expression changes in HCN4. Expression of RhebY35L, mTORS2215Y, Dedpdc5KO, PtenKO, and Tsc1KO led to different impacts on sEPSC properties. Effects of treatment with the selective HCN channel blocker zatebradine on hyperpolarization-induced inward currents in mTORS2215Y neurons confirmed the identity of ΔI as Ih.

Overall the data presented provides a convincing and compelling direct comparison of the roles that select mTOR pathway genes play on brain development and network excitability. It is critical to directly compare these gene effects in mouse models because although these genes are part of the mTOR pathway and clearly cause augmentation of mTOR activation, there are mechanistic differences in how these gees modify mTOR and how they interact with other proteins and phenotypic differences in humans harboring mutations in these same genes.

Reviewer #2 (Public Review):

Summary:<br /> This study examined the possible affect of spike-wave discharges (SWDs) on the response to visual or somatosensory stimulation using fMRI and EEG. This is a significant topic because SWDs often are called seizures and because there is non-responsiveness at this time, it would be logical that responses to sensory stimulation are reduced. On the other hand, in rodents with SWDs, sensory stimulation (a noise, for example) often terminates the SWD/seizure.

In humans, these periods of SWDs are due to thalamocortical oscillations. A certain percentage of the normal population can have SWDs in response to photic stimulation at specific frequencies. Other individuals develop SWDs without stimulation. They disrupt consciousness. Individuals have an absent look, or "absence", which is called absence epilepsy.

The authors use a rat model to study the responses to stimulation of the visual or somatosensory systems during and in between SWDs. They report that the response to stimulation is reduced during the SWDs. While some data show this nicely, the authors also report on lines 396-8 "When comparing statistical responses between both states, significant changes (p<0.05, cluster-) were noticed in somatosensory auditory frontal..., with these regions being less activated in interictal state (see also Figure 4). That statement is at odds with their conclusion. I do not see that this issue was addressed.

They also conclude that stimulation slows the pathways activated by the stimulus. I do not see any data proving this. It would require repeated assessments of the pathways in time. This issue was not addressed.

The authors also study the hemodynamic response function (HRF) and it is not clear what conclusions can be made from the data. This is still an issue. No conclusions appear to be possible to make.

Finally, the authors use a model to analyze the data. This model is novel and while that is a strength, its validation is unclear. The authors did not add any validation of their model.

Strengths:<br /> Use of fMRI and EEG to study SWDs in rats.

Weaknesses:<br /> Several aspects of the Methods and Results were improved but some are still are unclear.

Reviewer #3 (Public Review):

Summary:<br /> This is an interesting paper investigating fMRI changes during sensory (visual, tactile) stimulation and absence seizures in the GAERS model. The results are potentially important for the field and do suggest that sensory stimulation may not activate brain regions normally during absence seizures. But the findings are limited by substantial methodological issues that do not enable fMRI signals related to absence seizures to be fully disentangled from fMRI signals related to the sensory stimuli.

Strengths:

Investigating fMRI brain responses to sensory stimuli during absence seizures in an animal model is a novel approach with potential to yield important insights.

Use of an awake, habituated model is a valid and potentially powerful approach.

Weaknesses:

The major difficulty with interpreting the results of this study is that the duration of the visual and tactile stimuli were 6 seconds, which is very close to the mean seizure duration per Table 1. Therefore the HRF model looking at fMRI responses to visual or auditory stimuli occurring during seizures was simultaneously weighting both seizure activity and the sensory (visual or auditory) stimuli over the same time intervals on average. The resulting maps and time courses claiming to show fMRI changes from visual or auditory stimulation during seizures will therefore in reality contain some mix of both sensory stimulation-related signals and seizure-related signals. The main claim that the sensory stimuli do not elicit the same activations during seizures as they do in the interictal period may still be true. But the attempts to localize these differences in space or time will be contaminated by the seizure related signals.

In their response to this comment the authors state that some seizures had longer than average duration, and that they attempted to model the effects of both seizures and sensory stimulation. However these factors do not mitigate the concern because the mean duration of seizures and sensory stimulation remain nearly identical, and the models used therefore will not be able to effectively separate signals related to seizures and related to sensory stimulation.

The claims that differences were observed for example between visual cortex and superior colliculus signals with visual stim during seizures vs interictal remain unconvincing due to above.

Maps shown in Figure 3 do not show clear changes in the areas claimed to be involved.

In their response the authors enlarged the cross sections. However there are still discrepancies between the images and the way they are described in the text. For example, in the Results text the authors say that comparing the interictal and ictal states revealed less activation in the somatosensory cortex during the ictal than during the interictal state, yet Figure 3 bottom row left shows greater activation in somatosensory cortex in this contrast.

eLife assessment

The important work by Aballay et al. significantly advances our understanding of how G protein-coupled receptors (GPCRs) regulate immunity and pathogen avoidance. The authors provide convincing evidence for the GPCR NPR-15 to mediate immunity by altering the activity of several key transcription factors. This work will be of broad interest to immunologists.

Reviewer #1 (Public Review):

Summary:

Otarigho et al. presented a convincing study revealing that in C. elegans, the neuropeptide Y receptor GPCR/NPR-15 mediates both molecular and behavioral immune responses to pathogen attack. Previously, three npr genes were found to be involved in worm defense. In this study, the authors screened mutants in the remaining npr genes against P. aeruginosa-mediated killing and found that npr-15 loss-of-function improved worm survival. npr-15 mutants also exhibited enhanced resistance to other pathogenic bacteria but displayed significantly reduced avoidance to S. aureus, independent of aerotaxis, pathogen intake and defecation. The enhanced resistance in npr-15 mutant worms was attributed to upregulation of immune and neuropeptide genes, many of which were controlled by the transcription factors ELT-2 and HLH-30. The authors found that NPR-15 regulates avoidance behavior via the TRPM gene, GON-2, which has a known role in modulating avoidance behavior through the intestine. The authors further showed that both NPR-15-dependent immune and behavioral responses to pathogen attack were mediated by the NPR-15-expressing neurons ASJ. Overall, the authors discovered that the NPR-15/ASJ neural circuit may regulate distinct defense mechanisms against pathogens under different circumstances. This study provides novel and useful information to researchers in the fields of neuroimmunology and C. elegans research.

Strengths:

1. This study uncovered specific molecules and neuronal cells that regulate both molecular immune defense and behavior defense against pathogen attack and indicate that the same neural circuit may regulate distinct defense mechanisms under different circumstances. This discovery is significant because it not only reveals regulatory mechanisms of different defense strategies but also suggests how C. elegans utilize its limited neural resources to accomplish complex regulatory tasks.

2. The conclusions in this study are supported by solid evidence, which are often derived from multiple approaches and/or experiments. Multiple pathogenic bacteria were tested to examine the effect of NPR-15 loss-of-function on immunity; the impacts of pharyngeal pumping and defecation on bacterial accumulation were ruled out when evaluating defense; RNA-seq and qPCR were used to measure gene expression; gene inactivation was done in multiple strains to assess gene function.

3. Gene differential expression, gene ontology and pathway analyses were performed to demonstrate that NPR-15 controls immunity through regulating immune pathways.

4. Elegant approaches were employed to examine avoidance behavior (partial lawn, full lawn, and lawn occupancy) and the involvement of neurons in regulating immunity and avoidance (the use of a diverse array of mutant strains).

5. Statistical analyses were appropriate and adequate.

Reviewer #2 (Public Review):

Summary:<br /> The authors are studying the behavioral response to pathogen exposure. They and others have previously describe the role that the G-protein coupled receptors in the nervous system plays in detecting pathogens, and initiating behavioral patterns (e.g. avoidance/learned avoidance) that minimize contact. The authors study this problem in C. elegans, which is amenable to genetic and cellular manipulations and allow the authors to define cellular and signaling mechanisms. This paper extends the original idea to now implicate signaling and transcriptional pathways within a particular neuron (ASJ) and the gut in mediating avoidance behaviour.

Strengths:<br /> The work is rigorous and elegant and the data are convincing. The authors make superb use of mutant strains in C. elegans, as well tissue specific gene inactivation and expression and genetic methods of cell ablation. to demonstrate how a gene, NPR15 controls behavioral changes in pathogen infection. The results suggest that ASJ neurons and the gut mediate such effects. I expect the paper will constitute an important contribution to our understanding of how the nervous system coordinates immune and behavioral responses to infection.

eLife assessment

This study characterized the activity of optogenetically identified dopaminergic and GABAergic neurons in the ventral tegmental area in mice performing a memory-guided T-maze task, and shows that subpopulations of dopaminergic and GABAergic neurons exhibited choice-related activity during the delay period, consistent with some previous studies (e.g. Morris et al., 2006, Parker et al., 2016). The authors demonstrate that these delay-period activities were enhanced when the task requires short-term memory. The results are convincing and this study provides important results regarding the nature of delay-period activity in the task.

Reviewer #1 (Public Review):

Midbrain dopamine neurons have attracted attention as a part of the brain's reward system. A different line of research, on the other hand, has shown that these neurons are also involved in higher cognitive functions such as short-term memory. However, these neurons are thought not to encode short-term memory itself because they just exhibit a phasic response in short-term memory tasks, which cannot seem to maintain information during the memory period. To understand the role of dopamine neurons in short-term memory, the present study investigated the electrophysiological property of these neurons in rodents performing a T-maze version of short-term memory task, in which a visual cue indicated which arm (left or right) of the T-maze was associated with a reward. The animal needed to maintain this information while they were located between the cue presentation position and the selection position of the T-maze. The authors found that the activity of some dopamine neurons changed depending on the information while the animals were located in the memory position. This dopamine neuron modulation was unable to explain the motivation or motor component of the task. The authors concluded that this modulation reflected the information stored as short-term memory.

Comments on revised submission:

The authors adequately responded to all my concerns in the revised manuscript.

Reviewer #2 (Public Review):

The authors phototag DA and GABA neurons in the VTA in mice performing a t-maze task, and report choice-specific responses in the delay period of a memory-guided task, more so that in a variant task w/o a memory component. Overall, I found the results convincing. While showing responses that are choice selective in DA neurons is not entirely novel (e.g. Morris et al NN 2006, Parker et al NN 2016), the fact that this feature is stronger when there is a memory requirement is an interesting and a novel observation.

eLife assessment

This study used prolonged stimulation of a limb to examine possible plasticity in somatosensory evoked potentials and the role of the blood brain barrier (BBB). The significance is important because thus far BBB modulation of plasticity is mostly in the context of pathology. The revisions greatly improved the paper and the strength of evidence is convincing.

Reviewer #1 (Public Review):

The goal of the current study was to evaluate the effect of neuronal activity on blood-brain barrier permeability in the healthy brain, and to determine whether changes in BBB dynamics play a role in cortical plasticity. The authors used a variety of well-validated approaches to first demonstrate that limb stimulation increases BBB permeability. Using in vivo-electrophysiology and pharmacological approaches, the authors demonstrate that albumin is sufficient to induce cortical potentiation and that BBB transporters are necessary for stimulus-induced potentiation. The authors include a transcriptional analysis and differential expression of genes associated with plasticity, TGF-beta signaling, and extracellular matrix were observed following stimulation. Overall, the results obtained in rodents are compelling and support the authors' conclusions that neuronal activity modulates the BBB in the healthy brain and that mechanisms downstream of BBB permeability changes play a role in stimulus-evoked plasticity. These findings were further supported with fMRI and BBB permeability measurements performed in healthy human subjects performing a simple sensorimotor task. There is literature to suggest that there are sex differences in BBB dysfunction in pathophysiological conditions and the authors have acknowledged the use of only males as a minor limitation of the study that should be addressed in the future. Future studies should also test whether the upregulation of OAT3 plays a role in cortical plasticity observed following stimulation. Overall, this study provides novel insights into how neurovascular coupling, BBB permeability, and plasticity interact in the healthy brain.

Reviewer #2 (Public Review):

Summary:<br /> This study builds upon previous work that demonstrated that brain injury results in leakage of albumin across the blood brain barrier, resulting in activation of TGF-beta in astrocytes. Consequently, this leads to decreased glutamate uptake, reduced buffering of extracellular potassium and hyperexcitability. This study asks whether such a process can play a physiological role in cortical plasticity. They first show that stimulation of a forelimb for 30 minutes in a rat results in leakage of the blood brain barrier and extravasation of albumin on the contralateral but not ipsilateral cortex. The authors propose that the leakage is dependent upon neuronal excitability and is associated with an enhancement of excitatory transmission. Inhibiting the transport of albumin or the activation of TGF-beta prevents the enhancement of excitatory transmission. In addition, gene expression associated with TGF-beta activation, synaptic plasticity and extracellular matrix are enhanced on the "stimulated" hemisphere. That this may translate to humans is demonstrated by a break down in the blood brain barrier following activation of brain areas through a motor task.

Strengths:<br /> This study is novel and the results are potentially important as they demonstrate an unexpected break down of the blood brain barrier with physiological activity and this may serve a physiological purpose, affecting synaptic plasticity.

The strengths of the study are:<br /> 1) The use of an in vivo model with multiple methods to investigate the blood brain barrier response to a forelimb stimulation.<br /> 2) The determination of a potential functional role for the observed leakage of the blood brain barrier from both a genetic and electrophysiological view point<br /> 3) The demonstration that inhibiting different points in the putative pathway from activation of the cortex to transport of albumin and activation of the TGF-beta pathway, the effect on synaptic enhancement could be prevented.<br /> 4) Preliminary experiments demonstrating a similar observation of activity dependent break down of the blood brain barrier in humans.

Weaknesses:<br /> The authors adequately addressed most of my points. A few remain:<br /> 1) Although the reviewers have addressed the possible effects of anaesthesia on neuro-vascular coupling. They have not mentioned or addressed the possible effects of ketamine (an NMDA receptor antagonist) on synaptic plasticity. Indeed, the low percentage of SEP increase following potentiation (10-20%) could perhaps be explained by partial block of NMDA receptors by ketamine.<br /> 2) The experimental paradigms remain unclear to me. Now, it appears that drugs are applied for 50 minutes and that the stimulation occurs during the "washout period". The more conventional approach would be to have the drug application during the stimulation period to determine if the drugs occlude or enhance the effects of stimulation and then washout the drugs. The problem is that drugs variably washout at different rates depending upon their lipid solubility.<br /> 3) It is still not clear to what extent the experimenters and those doing the analysis were blinded to group. If one or both were blind to group, then please put this in the methods.

Reviewer #3 (Public Review):

Summary:

This study used prolonged stimulation of a limb to examine possible plasticity in somatosensory evoked potentials induced by the stimulation. They also studied the extent that the blood brain barrier (BBB) was opened by the prolonged stimulation and whether that played a role in the plasticity. They found that there was potentiation of the amplitude and area under the curve of the evoked potential after prolonged stimulation and this was long-lasting (>5 hrs). They also implicated extravasation of serum albumin, caveolae-mediated transcytosis, and TGFb signalling, as well as neuronal activity and upregulation of PSD95. Transcriptomics was done and implicated plasticity related genes in the changes after prolonged stimulation, but not proteins associated with the BBB or inflammation. Next, they address the application to humans using a squeeze ball task. They imaged the brain and suggest that the hand activity led to an increased permeability of the vessels, suggesting modulation of the BBB.

Strengths:

The strengths of the paper are the novelty of the idea that stimulation of the limb can induce cortical plasticity in a normal condition, and it involves opening of the BBB with albumin entry. In addition, there are many datasets and both rat and human data.

Weaknesses:

The conclusions are not compelling however because of a lack of explanation of methods. The explanation of why prolonged stimulation in the rat was considered relevant to normal conditions should be as clear in the paper as it is in the rebuttal. The authors need to ensure other aspects of the rebuttal are as clear in the paper as in the rebuttal too. The only remaining concern that is significant is that it is hard to understand the figures.

eLife assessment

This important study by Yogesh and Keller provides a set of results describing the response properties of cholinergic input and its functional impacts in the mouse visual cortex. They found that cholinergic inputs are elevated by locomotion in a binary manner regardless of locomotor speeds, and activation of cholinergic input differently modulated the activity of Later 2/3 and Layer 5 visual cortex neurons induced by bottom-up (visual stimuli) and top-down (visuomotor mismatch) inputs. The reviewers found that the experiments are cutting-edge and well executed, and the results to be mostly convincing.

Reviewer #1 (Public Review):

The paper submitted by Yogesh and Keller explores the role of cholinergic input from the basal forebrain (BF) in the mouse primary visual cortex (V1). The study aims to understand the signals conveyed by BF cholinergic axons in the visual cortex, their impact on neurons in different cortical layers, and their computational significance in cortical visual processing. The authors employed two-photon calcium imaging to directly monitor cholinergic input from BF axons expressing GCaMP6 in mice running through a virtual corridor, revealing a strong correlation between BF axonal activity and locomotion. This persistent activation during locomotion suggests that BF input provides a binary locomotion state signal. To elucidate the impact of cholinergic input on cortical activity, the authors conducted optogenetic and chemogenetic manipulations, with a specific focus on L2/3 and L5 neurons. They found that cholinergic input modulates the responses of L5 neurons to visual stimuli and visuomotor mismatch, while not significantly affecting L2/3 neurons. Moreover, the study demonstrates that BF cholinergic input leads to decorrelation in the activity patterns of L2/3 and L5 neurons.

This topic has garnered significant attention in the field, drawing the interest of many researchers actively investigating the role of BF cholinergic input in cortical activity and sensory processing. The experiments and analyses were thoughtfully designed and conducted with rigorous standards, leading to convincing results which align well with findings in previous studies. In other words, some of the main findings, such as the correlation between cholinergic input and locomotor activity and the effects of cholinergic input on V1 cortical activity, have been previously demonstrated by other labs (Goard and Dan, 2009; Pinto et al., 2013; Reimer et al., 2016). However, the study by Yogesh and Keller stands out by combining cutting-edge calcium imaging and optogenetics to provide compelling evidence of layer-specific differences in the impact of cholinergic input on neuronal responses to bottom-up (visual stimuli) and top-down inputs (visuomotor mismatch).

Reviewer #2 (Public Review):

The manuscript investigates the function of basal forebrain cholinergic axons in mouse primary visual cortex (V1) during locomotion using two-photon calcium imaging in head-fixed mice. Cholinergic modulation has previously been proposed to mediate the effects of locomotion on V1 responses. The manuscript concludes that the activity of basal forebrain cholinergic axons in visual cortex provides a signal which is more correlated with binary locomotion state than locomotion velocity of the animal. Cholinergic axons did not seem to respond to grating stimuli or visuomotor prediction error. Optogenetic stimulation of these axons increased the amplitude of responses to visual stimuli and decreased the response latency of layer 5 excitatory neurons, but not layer 2/3 neurons. Moreover, optogenetic or chemogenetic stimulation of cholinergic inputs reduced pairwise correlation of neuronal responses. These results provide insight into the role of cholinergic modulation to visual cortex and demonstrate that it affects different layers of visual cortex in a distinct manner. The experiments are well executed and the data appear to be of high quality. However, further analyses are required to fully support some of the study's conclusions.

The manuscript concludes that cholinergic axons convey a binary locomotion signal and are not tuned to running speed. Getting head-fixed animals to run at the speeds typical of freely moving animals can require training, which was not undertaken in this study. Consequently, the typically low running velocity of mice is a potential limitation of this study.

The analyses of the effects of locomotion and stimulation of cholinergic inputs present grand averages of responses across all neurons, and therefore may mask heterogeneity across layer 2/3 and layer 5 neurons.

eLife assessment

This important study examined the mechanisms underlying reduced excitability of ventral tegmental area dopamine neurons in mice that underwent a chronic mild unpredictable stress treatment. The authors identify NALCN and TRPC6 channels as key mechanisms that regulate spontaneous firing of ventral tegmental area dopamine neurons and examined their roles in reduced firing in mice that underwent a chronic mild unpredictable stress treatment. The authors' conclusions on neurophysiological data are supported by multiple approaches and convincing, although the relevance of the behavioral results to human depression remains unclear.

Reviewer #1 (Public Review):

Wang et al., present a paper aiming to identify NALCN and TRPC6 channels as key mechanisms regulating VTA dopaminergic neuron spontaneous firing and investigating whether these mechanisms are disrupted in a chronic unpredictable stress model mouse.

Major strengths:

This paper uses multiple approaches to investigate the role of NALCN and TRPC6 channels in VTA dopaminergic neurons.

Major weaknesses:<br /> In this revision, the authors have addressed the concerns about non-selective pharmacological tools.

Are the author's claims supported by the data?

The multimodal approach including shRNA knockdown experiments alleviates much of the concern about the non-specific pharmacological agents. Therefore, the author's claim that NALCN is involved in VTA dopaminergic neuron pacemaking is well-supported.

The claim that TRPC6 channels in the VTA are involved in the depressive-like symptoms of CMUS is supported.

Impact:

It is important to compare pacemaking mechanisms in VTA and SNc neurons and this paper convincingly shows that NALCN contributes to VTA pacemaking, as it is known to contribute to SNc pacemaking. It also shows that TRPC6 channels in VTA dopamine neurons contribute to the depressive-like symptoms associated with CMUS.

Additional context:

One of the only demonstrations of the expression and physiological significance of TRPCs in VTA DA neurons was published by (Rasmus et al., 2011; Klipec et al., 2016) which are not cited in this paper. In their study, TRPC4 expression was detected in a uniformly distributed subset of VTA DA neurons, and TRPC4 KO rats showed decreased VTA DA neuron tonic firing and deficits in cocaine reward and social behaviors.

Update: The authors say they have added a discussion of these papers, but I do not see it in the updated manuscript.

Reviewer #2 (Public Review):

This paper describes the results of a set of complementary and convergent experiments aimed at describing roles for the non-selective cation channels NALCN and TRPC6 in mediating subthreshold inward depolarizing currents and action potential generation in VTA DA neurons under normal physiological conditions. In general, the authors have responded satisfactorily to reviewer comments, and the revised manuscript is improved. The manuscript could still benefit from additional revision, including the following:

1. From the previous review, we mentioned that " 'The HCN' as written in line 69 is a bit misleading, as HCN channels in the heart and brain are different members of a family of channels, although as written in the text, it seems that they are identical." This is still the case (now line 73).

2. The authors state in line 112 that "most of the experiments were also repeated in female mice" - this is true in the case of most electrophysiological experiments, although not behavioral experiments. Authors should amend the statement in line 112 and clarify in the Discussion section which findings are generalizable between sexes; e.g.:<br /> a. Discussion of HCN contribution to VTA DA activity (beginning line 453) should clarify male mice.<br /> b. Similarly, any discussion of behavioral findings should clarify male mice.

3. The authors' statement in lines 179-183 ("In contrast, fewer GABAergic neuronal markers (Glutamic acid decarboxylase, GAD1/2 and vesicular GABA transporter, VGAT) co-expressed with the DA neurons, which is consistent with previous studies that VTA DA neurons co-expressing GABAergic neuronal markers mainly project to the lateral habenula") is a little confusing - as stated, it seems that the authors are confirming DA/GABA coexpression in VTA-LHb neurons, which is not the case.

4. Additional information could be included in the Methods section description of Western Blotting procedures - e.g., what thickness of tissue and what size gauge were used to dissect VTA for these experiments?

eLife assessment

Using state-of-the-art single-nucleus RNA sequencing, Yao et al. investigate the transcriptomic features of neural stem cells (NSCs) in the human hippocampus to address how they vary across different age groups and stroke conditions. The authors report alterations in NSC subtype proportions and gene expression profiles after stroke and an exemplary gene elevated in NSCs and reactive astrocytes in stroke patients. Although the study is valuable, the significance is restricted by technical limitations and the incomplete evidence supporting the main conclusions.

Reviewer #1 (Public Review):

In this manuscript, Yao et al. explored the transcriptomic characteristics of neural stem cells (NSCs) in the human hippocampus and their changes under different conditions using single-nucleus RNA sequencing (snRNA-seq). They generated single-nucleus transcriptomic profiles of human hippocampal cells from neonatal, adult, and aging individuals, as well as from stroke patients. They focused on the cell groups related to neurogenesis, such as neural stem cells and their progeny. They revealed genes enriched in different NSC states and performed trajectory analysis to trace the transitions among NSC states and towards astroglial and neuronal lineages in silico. They also examined how NSCs are affected by aging and injury using their datasets and found differences in NSC numbers and gene expression patterns across age groups and injury conditions. One major issue of the manuscript is questionable cell type identification. For example, more than 50% of the cells in the astroglial lineage clusters are NSCs, which is extremely high and inconsistent with classic histology studies.

While the authors have made efforts to address previous critics, major concerns have not been adequately addressed, including a very limited sample size and with poor patient information. In addition, some analytical approaches are still questionable and the authors acknowledged that some they cannot address. Therefore, while the topic is interesting, some results are preliminary and some conclusions are not fully supported by the data presented.

Reviewer #2 (Public Review):

In this manuscript, Yao et al. present a series of experiments aiming at generating a cellular atlas of the human hippocampus across aging, and how it may be affected by injury, in particular, stroke. Although the aim of the study is interesting and relevant for a larger audience, due to the ongoing controversy around the existence of adult hippocampal neurogenesis in humans, a number or technical weaknesses result in a poor support for many of the conclusions made from the results of these experiments.<br /> In particular, a recent meta analysis of five previous studies applying similar techniques to human samples has identified different aspects of sample size as main determinants of the statistical power needed to make significant conclusions. Some of this aspects are the number of nuclei sequenced and subject stratification. These two aspects are of concern in Yao's study. First, the number of sequenced nuclei is lower than the calculated numbers of nuclei required for detecting rare cell types. However, Yao et al. report succeeding in detecting rare populations, including several types of neural stem cells in different proliferation states, which have been demonstrated to be extremely scarce by previous studies. It would be very interesting to read how the authors interpret these differences. Secondly, the number of donors included in some of the groups is extremely low (n=1) and the miscellaneous information provided about the donors is practically inexistent. As individual factors such as chronic conditions, medication, lifestyle parameters, etc... are considered determinant for the variability of adult hippocampal neurogenesis levels across individuals, this represents a series limitation of the current study. Overall, several technical weaknesses severely limit the relevance of this study and the ability of the authors to achieve their experimental aims.

After a first review round, the manuscript is still lacking a clear discussion of its several technical limitations, which will help the audience to grasp the relevance of the findings. In particular, detailed information about individual patients health status and relevant lifestyle parameters that may have affected it is lacking. The authors make the point themselves that the discrepancies among studies might be caused by health state differences across hippocampi, which subsequently lead to different degrees of hippocampal neurogenesis.". So, even in the authors own interpretation this is a serious limitation to the manuscript, that however out of the authors control, impacts on the quality of their findings.

eLife assessment

This important multicenter study provides convincing evidence that the auditory noise emitted during online transcranial ultrasound stimulation (TUS) protocols can pose a considerable confound and is able to explain corticospinal excitability changes as measured with Motor Evoked Potentials (MEP). The findings lay the ground for future studies optimising protocols and control conditions to leverage TUS as a meaningful experimental and clinical tool. A clear strength of the study is the multitude of control conditions (i.e., control sites, acoustic masking, acoustic stimulation). These findings will be of interest to neuroscience researchers using brain stimulation approaches.

Reviewer #1 (Public Review):

Summary: The authors have used transcranial magnetic stimulation (TMS) and motor evoked potentials (MEPs) to determine whether the peripheral auditory confound arising from TUS can drive motor inhibition on its own. They gathered data from three international centers in four experiments testing:

- Experiment 1 (n = 11), two different TUS durations and intensities under sound masking or without.<br /> - Experiment 2 (n = 27) replicates Exp 1 with different intensities and a fixed TUS duration of 500ms.<br /> - Experiment 3 ( n = 16) studies the effect of various auditory stimuli testing different duration and pitches while applying TUS in an active site, on-target or no TUS.<br /> - Experiment 4 (n = 12) uses an inactive control site to reproduce the sound without effective neuromodulation, while manipulating the volume of the auditory confound at different US intensities with and without continuous sound masking.

Strengths: This study comes from three very strong groups in noninvasive brain stimulation with long experience in neuromodulation, multimodal and electrophysiological recordings. Although complex to understand due to slightly different methodologies across centers, this study provides quantitative evidence relating to the potential auditory confound in online TUS. The results are in line with reductions seen in motor-evoked responses during online 1kHz TUS, and remarkable efforts were made to isolate peripheral confounds from actual neuromodulation factors, highlighting the confounding effect of sound itself.

Weaknesses: However, there are some points that need attention. In my view, the most important are:

1. Despite the main conclusion of the authors stating that there is no dose-response effect of TUS on corticospinal inhibition, the point estimates for change in MEP and Ipssa indicate a more complex picture. The present data and analyses cannot rule out that there is a dose-response function which cannot be fully attributed to difference in sound (since the relationship in inversed, lower intracranial Isppa leads to higher MEP decrease). These results suggest that dose-response function needs to be further studied in future studies.

2. Other methods to test or mask the auditory confound are possible (e.g., smoothed ramped US wave) which could substantially solve part of the sound issue in future studies or experiments in deaf animals etc.

Reviewer #2 (Public Review):

Summary:

This study aims to test auditory confounds during transcranial ultrasound stimulation (TUS) protocols that rely on audible frequencies. In several experiments, the authors show that a commonly observed suppression of motor-evoked potentials (MEP) during TUS can be explained by acoustic stimulation. For instance, not only target TUS, but also stimulation of a control site and acoustic stimulation led to suppressed MEP.

The authors have convincingly addressed all of my comments and provided useful additional details. I believe that this is a strong study that will impact the field. Thanks also for making the sound stimuli open-source.

eLife assessment

This important study utilizes a virus-mediated short hairpin RNA (shRNA) approach to investigate in a novel way the role of the wild-type PHOX2B transcription factor in critical chemosensory neurons in the brainstem retrotrapezoid nucleus (RTN) region for maintaining normal CO2 chemoreflex control of breathing in adult rats. The solid results presented show blunted ventilation during elevated inhaled CO2 (hypercapnia) with knockdown of PHOX2B, accompanied by a reduction in expression of Gpr4 and Task2 mRNA for the proposed RTN neuron proton sensor proteins GPR4 and TASK2. These results suggest that maintained expression of wild-type PHOX2B affects respiratory control in adult animals, which complements previous studies showing that PHOX2B-expressing RTN neurons may be critical for chemosensory control throughout the lifespan and with implications for neurological disorders involving the RTN. When some methodological, data interpretation, and prior literature reference issues further highlighting novelty are adequately addressed, this study will be of interest to neuroscientists studying respiratory neurobiology as well as the neurodevelopmental control of motor behavior.

Reviewer #1 (Public Review):

Summary:<br /> This important study investigated the role of the PHOX2B transcription factor in neurons in the key brainstem chemosensory structure, the retrotrapezoid nucleus (RTN), for maintaining proper CO2 chemoreflex responses of breathing in the adult rat in vivo. PHOX2B has an important transcriptional role in neuronal survival and/or function, and mutations of PHOX2B severely impair the development and function of the autonomic nervous system and RTN, resulting in the developmental genetic disease congenital central hypoventilation syndrome (CCHS) in neonates, where the RTN may not form and is functionally impaired. The function of the wild-type PHOX2B protein in adult RTN neurons that continue to express PHOX2B is not fully understood. By utilizing a viral PHOX2B-shRNA approach for knockdown of PHOX2B specifically in RTN neurons, the authors' solid results show impaired ventilatory responses to elevated inspired CO2, measured by whole-body plethysmography in freely behaving adult rats, that develop progressively over a four-week period in vivo, indicating effects on RTN neuron transcriptional activity and associated blunting of the CO2 ventilatory response. The RTN neuronal mRNA expression data presented suggests the impaired hypercapnic ventilatory response is possibly due to the decreased expression of key proton sensors in the RTN. This study will be of interest to neuroscientists studying respiratory neurobiology as well as the neurodevelopmental control of motor behavior.

Strengths:<br /> 1. The authors used a shRNA viral approach to progressively knock down the PHOX2B protein, specifically in RTN neurons to determine whether PHOX2B is necessary for the survival and/or chemosensory function of adult RTN neurons in vivo.

2. To determine the extent of PHOX2B knockdown in RTN neurons, the authors combined RNAScope® and immunohistochemistry assays to quantify the subpopulation of RTN neurons expressing PHOX2B and neuromedin B (Nmb), which has been proposed to be key chemosensory neurons in the RTN.

3. The authors demonstrate that knockdown efficiency is time-dependent, with a progressive decrease in the number of Nmb-expressing RTN neurons that co-express PHOX2B over a four-week period.

4. Their results convincingly show hypoventilation particularly in 7.2% CO2 only for PHOX2B-shRNA RTN-injected rats after four weeks as compared to naïve and non-PHOX2B-shRNA targeted (NT-shRNA) RTN injected rats, suggesting a specific impairment of chemosensitive properties in RTN neurons with PHOX2B knockdown.

5. Analysis of the association between PHOX2B knockdown in RTN neurons and the attenuation of the hypercapnic ventilatory response (HCVR), by evaluating the correlation between the number of Nmb+/PHOX2B+ or Nmb+/PHOX2B- cells in the RTN and the resulting HCVR, showed a significant correlation between HCVR and number of Nmb+/PHOX2B+ and Nmb+/PHOX2B- cells, suggesting that the number of PHOX2B-expressing cells in the RTN is a predictor of the chemoreflex response and the reduction of PHOX2B protein impairs the CO2-chemoreflex.

6. The data presented indicate that PHOX2B knockdown not only causes a reduction in the HCVR but also a reduction in the expression of Gpr4 and Task2 mRNAs, suggesting that PHOX2B knockdown affects RTN neurons transcriptional activity and decreases the CO2 response, possibly by reducing the expression of key proton sensors in the RTN.

7. Results of this study show that independent of the role of PHOX2B during development, PHOX2B is still required to maintain proper CO2 chemoreflex responses in the adult brain, and its reduction in CCHS may contribute to the respiratory impairment in this disorder.

Weaknesses:<br /> 1. The authors found a significant decrease in the total number of Nmb+ RTN neurons (i.e., Nmb+/PHOX2B+ plus Nmb+/ PHOX2B-) in NT-shRNA rats at two weeks post viral injection, and also at the four-week period where the impairment of the chemosensory function of the RTN became significant, suggesting some inherent cell death possibly due to off-target toxic effects associated with shRNA procedures that may affect the experimental results.

2. The tissue sampling procedures for quantifying numbers of cells expressing proteins/mRNAs throughout the extended RTN region bilaterally have not been completely validated to accurately represent the full expression patterns in the RTN under experimental conditions.

3. The inferences about RTN neuronal expression of NMB, GPR4, or TASK2 are based on changes in mRNA levels, so it remains speculation that the observed reduction in Gpr4 and Task2 mRNA translates to a reduction in the protein levels and associated reduction of RTN neuronal chemosensitive properties.

Reviewer #2 (Public Review):

Summary:<br /> The authors used a short hairpin RNA technique strategy to elucidate the functional activity of neurons in the retrotrapezoid nucleus (RTN), a critical brainstem region for central chemoreception. Dysfunction in this area is associated with the neuropathology of congenital central hypoventilation syndrome (CCHS). The subsequent examination of these rats aimed to shed light on the intricate aspects of RTN and its implications for central chemoreception and disorders like CCHS in adults. They found that using the short hairpin RNA (shRNA) targeting Phox2b mRNA, a reduction of Phox2b expression was observed in Nmb neurons. In addition, Phox2b knockdown did not affect breathing in room air or under hypoxia, but the hypercapnia ventilatory response was significantly impaired. They concluded that Phox2b in the adult brain has an important role in CO2 chemoreception. They thought that their findings provided new evidence for mechanisms related to CCHS neuropathology. The conclusions of this paper are well supported by data, but careful discussion seems to be required for comparison with the results of various previous studies performed by different genetic strategies for the RTN neurons.

Strengths:<br /> The most exciting aspect of this work is the modelling of the Phox2b knockdown in one element of the central neuronal circuit mediating respiratory reflexes, that is in the RTN. To date, mutations in the PHOX2B gene are commonly associated with most patients diagnosed with CCHS, a disease characterized by hypoventilation and absence of chemoreflexes, in the neonatal period, which in severe cases can lead to respiratory arrest during sleep. In the present study, the authors demonstrated that the role of Phox2b extends beyond the developmental period, and its reduction in CCHS may contribute to the respiratory impairment observed in this disorder.

Weaknesses:<br /> Whereas the most exciting part of this work is the knockdown of the Phox2b in the RTN in adult rodents, the weakness of this study is the lack of a clear physiological, developmental, and anatomical distinction between this approach and similar studies already reported elsewhere (Ruffault et al., 2015, DOI: 10.7554/eLife.07051; Ramanantsoa et al., 2011, DOI: 10.1523/JNEUROSCI.1721-11.2011; Huang et al., 2017, DOI: 10.1016/j.neuron.2012.06.027; Hernandez-Miranda et al., 2018, DOI: 10.1073/pnas.1813520115; Ferreira et al., 2022 DOI: 10.7554/eLife.73130; Takakura et al., 2008 DOI: 10.1113/jphysiol.2008.153163; Basting et al., 2015 DOI: 10.1523/JNEUROSCI.2923-14.2015; Marina et al., 2010 DOI: 10.1523/JNEUROSCI.3141-10.2010). In addition, several conclusions presented in this work are not directly supported by the provided data.

Reviewer #3 (Public Review):

A brain region called the retrotrapezoid nucleus (RTN) regulates breathing in response to changes in CO2/H+, a process termed central chemoreception. A transcription factor called PHOX2B is important for RTN development and mutations in the PHOX2B gene result in a severe type of sleep apnea called Congenital Central Hypoventilation Syndrome. PHOX2B is also expressed throughout life, but its postmitotic functions remain unknown. This study shows that knockdown of PHOX2B in the RTN region in adult rats decreased expression of Task2 and Gpr4 in Nmb-expressing RTN chemoreceptors and this corresponded with a diminished ventilatory response to CO2 but did not impact baseline breathing or the hypoxic ventilatory response. These results provide novel insight regarding the postmitotic functions of PHOX2B in RTN neurons.

Main issues:<br /> 1) The experimental approach was not targeted to Nmb+ neurons and since other cells in the area also express Phox2b, conclusions should be tempered to focus on Phox2b expressing parafacial neurons NOT specifically RTN neurons

2) It is not clear whether PHOX2B is important for the transcription of pH sensing machinery, cell health, or both. If knockdown of PHOX2B knockdown results in loss of RTN neurons this is also expected to decrease Task2 and Gpr4 levels, albeit by a transcription-independent mechanism.

eLife assessment

This study on the effects of fasting on safety learning rests on basic premises and concepts that both reviewers found difficult to follow. If these can be clarified, the findings may well be useful and of some utility for the field of emotional learning as well as experimental clinical psychology. However, the main claims of the study are only partially supported and are therefore incomplete.

Reviewer #2 (Public Review):

The authors repeated a previous behavioural study on the effects of overnight fasting on avoidance and extinction learning in healthy female participants in the 3T MRI scanner. Previous behavioural findings were replicated only in part. Fasting related changes of fMRI signals were less than expected.

This paper is not without interest. Anxiety disorders are very frequent, and there is still a need to better understand ways to improve extinction and reduced avoidance. The authors follow up on previous observations of their group using overnight fasting. The findings, however, were largely negative, and it is difficult to tell how robust the observed positive findings are. The paradigm did not work as well as expected in the MR scanner.

Introduction/main hypothesis: The reviewer does not understand why a smaller reward prediction error should result in faster extinction learning? The opposite should be the case. Plus, how much of a reward prediction error is expected in the CS- condition in extinction training? Here the US omission is expected. The reviewer may miss a key concept of the study.

Results: A major part of the behavioural data of a previous pure behavioural study was not reproduced (avoidance learning), plus many of the MRI findings did not show a difference between the fasting and re-feed groups. Given the large amount of comparisons it makes one wonder how robust the presented findings are. The advances to the field are therefore limited.

eLife assessment

This potentially valuable study uses classic neuroanatomical techniques and synchrotron X-ray tomography to investigate the mapping of the trunk within the brainstem nuclei of the elephant brain. Given its unique specializations, understanding the somatosensory projections from the elephant trunk would be of general interest to evolutionary neurobiologists, comparative neuroscientists, and animal behavior scientists. However, the anatomical analysis is inadequate to support the authors' conclusion that they have identified the elephant trigeminal sensory nuclei rather than a different brain region, specifically the inferior olive.

Reviewer #1 (Public Review):

Summary:<br /> This fundamental study provides compelling neuroanatomical evidence underscoring the sensory function of the trunk in African and Asian elephants. Whereas myelinated tracts are classically appreciated as mediating neuronal connections, the authors speculate that myelinated bundles provide functional separation of trunk folds and display elaboration related to the "finger" projections. The authors avail themselves of many classical neuroanatomical techniques (including cytochrome oxidase stains, Golgi stains, and myelin stains) along with modern synchrotron X-ray tomography. This work will be of interest to evolutionary neurobiologists, comparative neuroscientists, and the general public, with its fascinating exploration of the brainstem of an icon sensory specialist.

Strengths:<br /> - The authors made excellent use of the precious sample materials from 9 captive elephants.<br /> - The authors adopt a battery of neuroanatomical techniques to comprehensively characterize the structure of the trigeminal subnuclei and properly re-examine the "inferior olive".<br /> - Based on their exceptional histological preparation, the authors reveal broadly segregated patterns of metabolic activity, similar to the classical "barrel" organization related to rodent whiskers.

Weaknesses:<br /> - As the authors acknowledge, somewhat limited functional description can be provided using histological analysis (compared to more invasive techniques).<br /> - The correlation between myelinated stripes and trunk fold patterns is intriguing, and Figure 4 presents this idea beautifully. I wonder - is the number of stripes consistent with the number of trunk folds? Does this hold for both species?

Reviewer #2 (Public Review):

The authors describe what they assert to be a very unusual trigeminal nuclear complex in the brainstem of elephants, and based on this, follow with many speculations about how the trigeminal nuclear complex, as identified by them, might be organized in terms of the sensory capacity of the elephant trunk.

The identification of the trigeminal nuclear complex/inferior olivary nuclear complex in the elephant brainstem is the central pillar of this manuscript from which everything else follows, and if this is incorrect, then the entire manuscript fails, and all the associated speculations become completely unsupported.

The authors note that what they identify as the trigeminal nuclear complex has been identified as the inferior olivary nuclear complex by other authors, citing Shoshani et al. (2006; 10.1016/j.brainresbull.2006.03.016) and Maseko et al (2013; 10.1159/000352004), but fail to cite either Verhaart and Kramer (1958; PMID 13841799) or Verhaart (1962; 10.1515/9783112519882-001). These four studies are in agreement, but the current study differs.

Let's assume for the moment that the four previous studies are all incorrect and the current study is correct. This would mean that the entire architecture and organization of the elephant brainstem is significantly rearranged in comparison to ALL other mammals, including humans, previously studied (e.g. Kappers et al. 1965, The Comparative Anatomy of the Nervous System of Vertebrates, Including Man, Volume 1 pp. 668-695) and the closely related manatee (10.1002/ar.20573). This rearrangement necessitates that the trigeminal nuclei would have had to "migrate" and shorten rostrocaudally, specifically and only, from the lateral aspect of the brainstem where these nuclei extend from the pons through to the cervical spinal cord (e.g. the Paxinos and Watson rat brain atlases), the to the spatially restricted ventromedial region of specifically and only the rostral medulla oblongata. According to the current paper, the inferior olivary complex of the elephant is very small and located lateral to their trigeminal nuclear complex, and the region from where the trigeminal nuclei are located by others appears to be just "lateral nuclei" with no suggestion of what might be there instead.

Such an extraordinary rearrangement of brainstem nuclei would require a major transformation in the manner in which the mutations, patterning, and expression of genes and associated molecules during development occur. Such a major change is likely to lead to lethal phenotypes, making such a transformation extremely unlikely. Variations in mammalian brainstem anatomy are most commonly associated with quantitative changes rather than qualitative changes (10.1016/B978-0-12-804042-3.00045-2).

The impetus for the identification of the unusual brainstem trigeminal nuclei in the current study rests upon a previous study from the same laboratory (10.1016/j.cub.2021.12.051) that estimated that the number of axons contained in the infraorbital branch of the trigeminal nerve that innervate the sensory surfaces of the trunk is approximately 400 000. Is this number unusual? In a much smaller mammal with a highly specialized trigeminal system, the platypus, the number of axons innervating the sensory surface of the platypus bill skin comes to 1 344 000 (10.1159/000113185). Yet, there is no complex rearrangement of the brainstem trigeminal nuclei in the brain of the developing or adult platypus (Ashwell, 2013, Neurobiology of Monotremes), despite the brainstem trigeminal nuclei being very large in the platypus (10.1159/000067195). Even in other large-brained mammals, such as large whales that do not have a trunk, the number of axons in the trigeminal nerve ranges between 400,000 and 500,000 (10.1007/978-3-319-47829-6_988-1). The lack of comparative support for the argument forwarded in the previous and current study from this laboratory, and that the comparative data indicates that the brainstem nuclei do not change in the manner suggested in the elephant, argues against the identification of the trigeminal nuclei as outlined in the current study. Moreover, the comparative studies undermine the prior claim of the authors, informing the current study, that "the elephant trigeminal ganglion ... point to a high degree of tactile specialization in elephants" (10.1016/j.cub.2021.12.051). While clearly, the elephant has tactile sensitivity in the trunk, it is questionable as to whether what has been observed in elephants is indeed "truly extraordinary".

But let's look more specifically at the justification outlined in the current study to support their identification of the unusually located trigeminal sensory nuclei of the brainstem.

(1) Intense cytochrome oxidase reactivity.<br /> (2) Large size of the putative trunk module.<br /> (3) Elongation of the putative trunk module.<br /> (4) The arrangement of these putative modules corresponds to elephant head anatomy.<br /> (5) Myelin stripes within the putative trunk module that apparently match trunk folds.<br /> (6) Location apparently matches other mammals.<br /> (7) Repetitive modular organization apparently similar to other mammals.<br /> (8) The inferior olive described by other authors lacks the lamellated appearance of this structure in other mammals.

Let's examine these justifications more closely.

(1) Cytochrome oxidase histochemistry is typically used as an indicative marker of neuronal energy metabolism. The authors indicate, based on the "truly extraordinary" somatosensory capacities of the elephant trunk, that any nuclei processing this tactile information should be highly metabolically active, and thus should react intensely when stained for cytochrome oxidase. We are told in the methods section that the protocols used are described by Purkart et al (2022) and Kaufmann et al (2022). In neither of these cited papers is there any description, nor mention, of the cytochrome oxidase histochemistry methodology, thus we have no idea of how this histochemical staining was done. To obtain the best results for cytochrome oxidase histochemistry, the tissue is either processed very rapidly after buffer perfusion to remove blood or in recently perfusion-fixed tissue (e.g., 10.1016/0165-0270(93)90122-8). Given: (1) the presumably long post-mortem interval between death and fixation - "it often takes days to dissect elephants"; (2) subsequent fixation of the brains in 4% paraformaldehyde for "several weeks"; (3) The intense cytochrome oxidase reactivity in the inferior olivary complex of the laboratory rat (Gonzalez-Lima, 1998, Cytochrome oxidase in neuronal metabolism and Alzheimer's diseases); and (4) The lack of any comparative images from other stained portions of the elephant brainstem; it is difficult to support the justification as forwarded by the authors. The histochemical staining observed is likely background reactivity from the use of diaminobenzidine in the staining protocol. Thus, this first justification is unsupported.

Justifications (2), (3), and (4) are sequelae from justification (1). In this sense, they do not count as justifications, but rather unsupported extensions.

(4) and (5) These are interesting justifications, as the paper has clear internal contradictions, and (5) is a sequelae of (4). The reader is led to the concept that the myelin tracts divide the nuclei into sub-modules that match the folding of the skin on the elephant trunk. One would then readily presume that these myelin tracts are in the incoming sensory axons from the trigeminal nerve. However, the authors note that this is not the case: "Our observations on trunk module myelin stripes are at odds with this view of myelin. Specifically, myelin stripes show no tapering (which we would expect if axons divert off into the tissue). More than that, there is no correlation between myelin stripe thickness (which presumably correlates with axon numbers) and trigeminal module neuron numbers. Thus, there are numerous myelinated axons, where we observe few or no trigeminal neurons. These observations are incompatible with the idea that myelin stripes form an axonal 'supply' system or that their prime function is to connect neurons. What do myelin stripe axons do, if they do not connect neurons? We suggest that myelin stripes serve to separate rather than connect neurons." So, we are left with the observation that the myelin stripes do not pass afferent trigeminal sensory information from the "truly extraordinary" trunk skin somatic sensory system, and rather function as units that separate neurons - but to what end? It appears that the myelin stripes are more likely to be efferent axonal bundles leaving the nuclei (to form the olivocerebellar tract). This justification is unsupported.

(6) The authors indicate that the location of these nuclei matches that of the trigeminal nuclei in other mammals. This is not supported in any way. In ALL other mammals in which the trigeminal nuclei of the brainstem have been reported they are found in the lateral aspect of the brainstem, bordered laterally by the spinal trigeminal tract. This is most readily seen and accessible in the Paxinos and Watson rat brain atlases. The authors indicate that the trigeminal nuclei are medial to the facial nerve nucleus, but in every other species, the trigeminal sensory nuclei are found lateral to the facial nerve nucleus. This is most salient when examining a close relative, the manatee (10.1002/ar.20573), where the location of the inferior olive and the trigeminal nuclei matches that described by Maseko et al (2013) for the African elephant. This justification is not supported.

(7) The dual to quadruple repetition of rostrocaudal modules within the putative trigeminal nucleus as identified by the authors relies on the fact that in the neurotypical mammal, there are several trigeminal sensory nuclei arranged in a column running from the pons to the cervical spinal cord, these include (nomenclature from Paxinos and Watson in roughly rostral to caudal order) the Pr5VL, Pr5DM, Sp5O, Sp5I, and Sp5C. However, these nuclei are all located far from the midline and lateral to the facial nerve nucleus, unlike what the authors describe in the elephants. These rostrocaudal modules are expanded upon in Figure 2, and it is apparent from what is shown that the authors are attributing other brainstem nuclei to the putative trigeminal nuclei to confirm their conclusion. For example, what they identify as the inferior olive in Figure 2D is likely the lateral reticular nucleus as identified by Maseko et al (2013). This justification is not supported.

(8) In primates and related species, there is a distinct banded appearance of the inferior olive, but what has been termed the inferior olive in the elephant by other authors does not have this appearance, rather, and specifically, the largest nuclear mass in the region (termed the principal nucleus of the inferior olive by Maseko et al, 2013, but Pr5, the principal trigeminal nucleus in the current paper) overshadows the partial banded appearance of the remaining nuclei in the region (but also drawn by the authors of the current paper). Thus, what is at debate here is whether the principal nucleus of the inferior olive can take on a nuclear shape rather than evince a banded appearance. The authors of this paper use this variance as justification that this cluster of nuclei could not possibly be the inferior olive. Such a "semi-nuclear/banded" arrangement of the inferior olive is seen in, for example, giraffe (10.1016/j.jchemneu.2007.05.003), domestic dog, polar bear, and most specifically the manatee (a close relative of the elephant) (brainmuseum.org; 10.1002/ar.20573). This justification is not supported.

Thus, all the justifications forwarded by the authors are unsupported. Based on methodological concerns, prior comparative mammalian neuroanatomy, and prior studies in the elephant and closely related species, the authors fail to support their notion that what was previously termed the inferior olive in the elephant is actually the trigeminal sensory nuclei. Given this failure, the justifications provided above that are sequelae also fail. In this sense, the entire manuscript and all the sequelae are not supported.

What the authors have not done is to trace the pathway of the large trigeminal nerve in the elephant brainstem, as was done by Maseko et al (2013), which clearly shows the internal pathways of this nerve, from the branch that leads to the fifth mesencephalic nucleus adjacent to the periventricular grey matter, through to the spinal trigeminal tract that extends from the pons to the spinal cord in a manner very similar to all other mammals. Nor have they shown how the supposed trigeminal information reaches the putative trigeminal nuclei in the ventromedial rostral medulla oblongata. These are but two examples of many specific lines of evidence that would be required to support their conclusions. Clearly, tract tracing methods, such as cholera toxin tracing of peripheral nerves cannot be done in elephants, thus the neuroanatomy must be done properly and with attention to detail to support the major changes indicated by the authors.

So what are these "bumps" in the elephant brainstem?

Four previous authors indicate that these bumps are the inferior olivary nuclear complex. Can this be supported?

The inferior olivary nuclear complex acts "as a relay station between the spinal cord (n.b. trigeminal input does reach the spinal cord via the spinal trigeminal tract) and the cerebellum, integrating motor and sensory information to provide feedback and training to cerebellar neurons" (https://www.ncbi.nlm.nih.gov/books/NBK542242/). The inferior olivary nuclear complex is located dorsal and medial to the pyramidal tracts (which were not labelled in the current study by the authors but are clearly present in Fig. 1C and 2A) in the ventromedial aspect of the rostral medulla oblongata. This is precisely where previous authors have identified the inferior olivary nuclear complex and what the current authors assign to their putative trigeminal nuclei. The neurons of the inferior olivary nuclei project, via the olivocerebellar tract to the cerebellum to terminate in the climbing fibres of the cerebellar cortex.

Elephants have the largest (relative and absolute) cerebellum of all mammals (10.1002/ar.22425), this cerebellum contains 257 x109 neurons (10.3389/fnana.2014.00046; three times more than the entire human brain, 10.3389/neuro.09.031.2009). Each of these neurons appears to be more structurally complex than the homologous neurons in other mammals (10.1159/000345565; 10.1007/s00429-010-0288-3). In the African elephant, the neurons of the inferior olivary nuclear complex are described by Maseko et al (2013) as being both calbindin and calretinin immunoreactive. Climbing fibres in the cerebellar cortex of the African elephant are clearly calretinin immunopositive and also are likely to contain calbindin (10.1159/000345565). Given this, would it be surprising that the inferior olivary nuclear complex of the elephant is enlarged enough to create a very distinct bump in exactly the same place where these nuclei are identified in other mammals?

What about the myelin stripes? These are most likely to be the origin of the olivocerebellar tract and probably only have a coincidental relationship with the trunk. Thus, given what we know, the inferior olivary nuclear complex as described in other studies, and the putative trigeminal nuclear complex as described in the current study, is the elephant inferior olivary nuclear complex. It is not what the authors believe it to be, and they do not provide any evidence that discounts the previous studies. The authors are quite simply put, wrong. All the speculations that flow from this major neuroanatomical error are therefore science fiction rather than useful additions to the scientific literature.

What do the authors actually have?<br /> The authors have interesting data, based on their Golgi staining and analysis, of the inferior olivary nuclear complex in the elephant.

Reviewer #3 (Public Review):

Summary:<br /> The study claims to investigate trunk representations in elephant trigeminal nuclei located in the brainstem. The researchers identified large protrusions visible from the ventral surface of the brainstem, which they examined using a range of histological methods. However, this ventral location is usually where the inferior olivary complex is found, which challenges the author's assertions about the nucleus under analysis. They find that this brainstem nucleus of elephants contains repeating modules, with a focus on the anterior and largest unit which they define as the putative nucleus principalis trunk module of the trigeminal. The nucleus exhibits low neuron density, with glia outnumbering neurons significantly. The study also utilizes synchrotron X-ray phase contrast tomography to suggest that myelin-stripe-axons traverse this module. The analysis maps myelin-rich stripes in several specimens and concludes that based on their number and patterning they likely correspond with trunk folds; however, this conclusion is not well supported if the nucleus has been misidentified.

Strengths:<br /> The strength of this research lies in its comprehensive use of various anatomical methods, including Nissl staining, myelin staining, Golgi staining, cytochrome oxidase labeling, and synchrotron X-ray phase contrast tomography. The inclusion of quantitative data on cell numbers and sizes, dendritic orientation and morphology, and blood vessel density across the nucleus adds a quantitative dimension. Furthermore, the research is commendable for its high-quality and abundant images and figures, effectively illustrating the anatomy under investigation.

Weaknesses:<br /> While the research provides potentially valuable insights if revised to focus on the structure that appears to be the inferior olivary nucleus, there are certain additional weaknesses that warrant further consideration. First, the suggestion that myelin stripes solely serve to separate sensory or motor modules rather than functioning as an "axonal supply system" lacks substantial support due to the absence of information about the neuronal origins and the termination targets of the axons. Postmortem fixed brain tissue limits the ability to trace full axon projections. While the study acknowledges these limitations, it is important to exercise caution in drawing conclusions about the precise role of myelin stripes without a more comprehensive understanding of their neural connections.

Second, the quantification presented in the study lacks comparison to other species or other relevant variables within the elephant specimens (i.e., whole brain or brainstem volume). The absence of comparative data for different species limits the ability to fully evaluate the significance of the findings. Comparative analyses could provide a broader context for understanding whether the observed features are unique to elephants or more common across species. This limitation in comparative data hinders a more comprehensive assessment of the implications of the research within the broader field of neuroanatomy. Furthermore, the quantitative comparisons between African and Asian elephant specimens should include some measure of overall brain size as a covariate in the analyses. Addressing these weaknesses would enable a richer interpretation of the study's findings.

eLife assessment

This study investigated the role of specific proteins in a mouse model of developmental epilepsy. The significance of the work is important because a new mouse model was used to simulate a type of developmental epilepsy. The work is also significant because the deletion of two proteins together, but not separately, improved the symptoms, and data were convincing.

Reviewer #1 (Public Review):

Hyperactivation of mTOR signaling causes epilepsy. It has long been assumed that this occurs through overactivation of mTORC1, since treatment with the mTORC1 inhibitor rapamycin suppresses seizures in multiple animal models. However, the recent finding that genetic inhibition of mTORC1 via Raptor deletion did not stop seizures while inhibition of mTORC2 did, challenged this view (Chen et al, Nat Med, 2019). In the present study, the authors tested whether mTORC1 or mTORC2 inhibition alone was sufficient to block the disease phenotypes in a model of somatic Pten loss-of-function (a negative regulator of mTOR). They found that inactivation of either mTORC1 or mTORC2 alone normalized brain pathology but did not prevent seizures, whereas dual inactivation of mTORC1 and mTORC2 prevented seizures. As the functions of mTORC1 versus mTORC2 in epilepsy remain unclear, this study provides important insight into the roles of mTORC1 and mTORC2 in epilepsy caused by Pten loss and adds to the emerging body of evidence supporting a role for both complexes in the disease development.

Strengths:<br /> The animal models and the experimental design employed in this study allow for a direct comparison between the effects of mTORC1, mTORC2, and mTORC1/mTORC2 inactivation (i.e., same animal background, same strategy and timing of gene inactivation, same brain region, etc.). Additionally, the conclusions on brain epileptic activity are supported by analysis of multiple EEG parameters, including seizure frequencies, sharp wave discharges, interictal spiking, and total power analyses.

Weaknesses:<br /> The original concerns regarding the hippocampal contribution to the seizure phenotypes in this Pten loss-of-function model have been addressed with the inclusion of new data in the revised manuscript.

The issue of sample sizes being small and do not allow for the assessment of whether mTORC1 or mTORC2 inactivation reduces seizure frequency or incidence remains a limitation of the study. However, the study's main conclusion that spontaneous seizures and epileptiform activity persist following inactivation of mTORC1 or mTORC2 alone while it is rescued following inactivation of both mTORC1 and mTORC2 is supported by the provided data and remains valid.

Reviewer #2 (Public Review):

Summary: The study by Cullen et al presents intriguing data regarding the contribution of mTOR complex 1 (mTORC1) versus mTORC2 or both in Pten-null induced macrocephaly and epileptiform activity. The role of mTORC2 in mTORopathies, and in particular Pten loss-off-function (LOF)-induced pathology and seizures, is understudied and controversial. In addition, recent data provided evidence against the role of mTORC1 in PtenLOF-induced seizures. To address these controversies and the contribution off these mTOR complexes in PtenLOF-induced pathology and seizures, the authors injected a AAV9-Cre into the cortex of conditional single, double and triple transgenic mice at postnatal day 0 to remove Pten, Pten+Raptor or Rictor, and Pten+raptor+rictor. Raptor and Rictor are essentially binding partners of mTORC1 and mTORC2, respectively. One major finding is that despite preventing the mild macrocephaly and increased cell size, Raptor knockout (KO, decrease mTORC1 activity) did not prevent the occurrence of seizures and the rate of SWD event, and aggravated seizure duration. Similarly, Rictor KO (decreased mTORC2 activity) partially prevented the mild macrocephaly and increased cell size but did not prevent the occurrence of seizures and did not affect seizure duration. However, Rictor KO reduced the rate of SWD events. Finally, the pathology and seizure/SWD activity were fully prevented in the double KO. These data suggest the contribution of both increased mTORC1 and mTORC2 in the pathology and epileptic activity of Pten LOF mice, emphasizing the importance of blocking both complexes for seizure treatment. Whether these data apply to other mTORopathies due to Tsc1, Tsc2, mTOR, AKT or other gene variants remain to be examined.

Strengths: The strengths are as follow: 1) they address an important and controversial question that has clinical application, 2) the study uses a reliable and relatively easy method to KO specific genes in cortical neurons, based on AAV9 injections in pups. 2) they perform careful video-EEG analyses correlated with some aspects of cellular pathology.

Weaknesses: the study has nevertheless a few weaknesses: 1) the conclusions are perhaps a bit overstated. The data do not show that increased mTORC1 or mTORC2 are sufficient to cause epilepsy. But the data clearly show that both increased mTORC1 and mTORC2 activity contribute to the pathology and seizure activity and as such are necessary for seizures to occur. 2) the data related to the EEG would benefit from having more mice. Adding more mice would have help determine whether there is a decrease in seizure activity with the Rictor or Raptor KO. 3) it would have been interesting to examine the impact of mTORC2 and mTORC1 overexpression related to point #1 above.

The authors properly addressed my comments. Number 3 above was only a suggestion that could be a follow-up in another study.

Reviewer #3 (Public Review):

Summary: This study investigated the role of mTORC1 and 2 in a mouse model of developmental epilepsy which simulates the epilepsy in cortical malformations. Given activation of genes such as PTEN activate TORC1, and this is considered to be excessive in cortical malformations, the authors asked whether inactivating mTORC1 and 2 would ameliorate the seizures and malformation in the mouse model. The work is highly significant because a new mouse model is used where Raptor and Rictor, which regulate mTORC1 and 2 respectively, were inactivated in one hemisphere of the cortex. The work is also significant because the deletion of both Raptor and Rictor improved the epilepsy and malformation. In the mouse model, the seizures were generalized or there were spike wave discharges (SWD). They also examined the interictal EEG. The malformation was manifested by increased cortical thickness and soma size.

Strengths: The presentation and writing is strong. Quality of data are strong. The data support the conclusions for the most part. The results are significant: Generalized seizures and SWDs were reduced when both Torc1 and 2 were inactivated but not when one was inactivated.

Weaknesses: One of the limitations is a somewhat small sample size. Another is that there was hippocampal expression. A third is that recordings of seizures were not continuous and different for each mouse. Another concern is they only measured layer II/III neurons.

eLife assessment

The authors used an innovative modified 10X genomic sequencing method to detect cPCDHg is-forms in pyramidal neurons. With solid electrophysiological recordings, they showed that neurons expressing the same sets of cPCDHg isoforms are less likely to form synapses with each other. These valuable findings confirms previous results and extend our understanding of cPCDHg diversity and neuronal connectivity.

Reviewer #1 (Public Review):

The manuscript by Zhu and colleagues aimed to clarify the importance of isoform diversity of PCDHg in establishing cortical synapse specificity. The authors optimized 5' single-cell sequencing to detect cPCDHg isoforms and showed that the pyramidal cells express distinct combinations of PCDHg isoforms. Then, the authors conducted patch-clamp recordings from cortical neurons whose PCDHg diversity was disrupted. In the elegant experiment in Figure 3, the authors demonstrated that the neurons expressing the same sets of cPCDHg isoforms are less likely to form synapses with each other, suggesting that identical cPCDHg isoforms may have a repulsive effect on synapse formation. Importantly, this phenomenon was dependent on the similarity of the isoforms present in neurons but not on the amount of proteins expressed.

The authors have addressed most criticisms raised in the initial review and the manuscript has improved significantly. One of the major concerns in the first review was whether PCDHg isoforms, which are expressed at a much lower level than C-type isoforms, have true physiological significance. The authors conducted additional experiments to address this point by using PCDHg cKO and provided convincing data supporting their conclusion. The results from PCDHg C4 overexpression, showing no impact on synaptic connectivity, further clarified the importance of isoforms. The limitation of the paper is that most experiments relied on overexpression of isoforms. Whether the isoform diversity is necessary for the synapse refinement in a physiological condition remains further clarification.

Reviewer #2 (Public Review):

This short manuscript by Zhu et al. describes an investigation into the role of gamma protocadherins in synaptic connectivity in the mouse cerebral cortex. First, the authors conduct a single-cell RNA-seq survey of postnatal day 11 mouse cortical neurons, using an adapted 10X Genomics method to capture the 5' sequences that are necessary to identify individual gamma protocadherin isoforms (all 22 transcripts share the same three 3' "constant" exons, so standard 3'-biased methods can't distinguish them). This method adaptation is an advance for examining individual clustered protocadherin transcripts, and it is helpful to publish the method in this manuscript. The results largely confirm what was known from other approaches, which is that a few of the 19 A and B subtype gamma protocadherins are expressed in an apparently stochastic and combinatorial fashion in each cortical neuron, while the 3 C subtype genes are expressed by most neurons. Second, using elegant paired electrophysiological recordings, the authors show that in gamma protocadherin knockout cortical slices, the likelihood of two neurons on layers 2/3 being synaptically connected is increased. That suggests that gamma protocadherins generally inhibit synaptic connectivity in the cortex; again, this has been reported previously using morphological assays, but it is helpful to see it confirmed here with physiology. Finally, the authors use an impressive sequential in utero electroporation method to provide evidence that the degree of isoform matching between two neurons negatively regulates their reciprocal synaptic connectivity. These are difficult experiments to do, and while some caveats remain (e.g., lack of demonstration of protein levels in electroporated neurons, lack of resolution of the differences between the present results and those of other papers, a focus on C4 rather than C3 or C5 when considering the highly expressed C-type isoforms), the main result is consistent. Strengths of this manuscript include the impressive methodology and improved demonstration of the previously-reported finding that gamma protocadherins work via homophilic matching to put a brake on synapse formation in the cortex. Because of the unique organization and expression pattern of the gamma protocadherins, it is not likely that these results will be broadly applicable to the general understanding of the role of cell adhesion molecules in synapse development. However, the methodology, which is now better described, should be applicable more broadly and the improved demonstration of the role of gamma protocadherin's negative role in cortical synaptogenesis is helpful in confirming earlier studies. There are several differences between the results here and those of other papers on the cortex, as well as those examining other neuronal populations such as spinal cord. The present findings do not resolve them, but adopting genetic approaches rather than overexpression in the future should help.

Reviewer #1 (Public Review):

Gazula and co-workers presented in this paper a software tool for 3D structural analysis of human brains, using slabs of fixed or fresh brains. This tool will be included in Freesurfer, a well-known neuroimaging processing software. It is possible to reconstruct a 3D surface from photographs of coronal sliced brains, optionally using a surface scan as model. A high-resolution segmentation of 11 brain regions is produced, independent of the thickness of the slices, interpolating information when needed. Using this method, the researcher can use the sliced brain to segment all regions, without the need of ex vivo MRI scanning.

The software suite is freely available and includes 3 modules. The first accomplishes preprocessing steps, for correction of pixel sizes and perspective. The second module is a registration algorithm that registers a 3D surface scan obtained prior to sectioning (reference) to the multiple 2D slices. It is not mandatory to scan the surface, -a probabilistic atlas can also be used as reference- however the accuracy is lower. The third module uses machine learning to perform the segmentation of 11 brain structures in the 3D reconstructed volume. This module is robust, dealing with different illumination conditions, cameras, lens and camera settings. This algorithm ("Photo-SynthSeg") produces isotropic smooth reconstructions, even in high anisotropic datasets (when the in-plane resolution of the photograph is much higher than the thickness), interpolating the information between slices.

To verify the accuracy and reliability of the toolbox, the authors reconstructed 3 datasets, using real and synthetic data. Real data of 21 postmortem confirmed Alzheimer's disease cases from the Massachusetts Alzheimer's Disease Research Center (MADRC)and 24 cases from the AD Research at the University of Washington(who were MRI scanned prior to processing)were employed for testing. These cases represent a challenging real-world scenario. Additionally, 500 subjects of the Human Connectome project were used for testing error as a continuous function of slice thickness. The segmentations were performed with the proposed deep-learning new algorithm ("Photo-SynthSeg") and compared against MRI segmentations performed to "SAMSEG" (an MRI segmentation algorithm, computing Dice scores for the segmentations. The methods are sound and statistically showed correlations above 0.8, which is good enough to allow volumetric analysis. The main strengths of the methods are the datasets used (real-world challenging and synthetic) and the statistical treatment, which showed that the pipeline is robust and can facilitate volumetric analysis derived from brain sections and conclude which factors can influence in the accuracy of the method (such as using or not 3D scan and using constant thickness).

Although very robust and capable of handling several situations, the researcher has to keep in mind that processing has to follow some basic rules in order for this pipeline to work properly. For instance, fiducials and scales need to be included in the photograph, and the slabs should be photographed against a contrasting background. Also, only coronal slices can be used, which can be limiting for certain situations.

The authors achieved their aims, and the statistical analysis confirms that the machine learning algorithm performs segmentations comparable to the state-of-the-art of automated MRI segmentations.<br /> Those methods will be particularly interesting to researchers who deal with post-mortem tissue analysis and do not have access to ex vivo MRI. Quantitative measurements of specific brain areas can be performed in different pathologies and even in the normal aging process. The method is highly reproducible, and cost-effective since allows the pipeline to be applied by any researcher with small pre-processing steps.

eLife assessment

This important study tests the hypothesis that a high autism quotient in neurotypical adults is strongly associated with suboptimal motor planning and visual updating after eye movements, which in turn, is related to a disrupted efference copy mechanism. The implication is that such abnormal behavior would be exaggerated in those with ASD and may contribute to sensory overload - a key symptom in this condition. The evidence presented is convincing, with significant effects in both visual and motor domains, adequate sample sizes, and consideration of alternatives. However, the study would be strengthened with minor but necessary corrections to methods and statistics, as well as a moderation of claims regarding direct application to ASD in the absence of testing such patients.

Reviewer #1 (Public Review):

Summary:<br /> This study examines a hypothesized link between autism symptomatology and efference copy mechanisms. This is an important question for several reasons. Efference copy is both a critical brain mechanism that is key to rapid sensorimotor behaviors, and one that has important implications for autism given recent empirical and theoretical work implicating atypical prediction mechanisms and atypical reliance on priors in ASD.

The authors test this relationship in two different experiments, both of which show larger errors/biases in spatial updating for those with heightened autistic traits (as measured by AQ in neurotypical (NT) individuals).

Strengths:<br /> The empirical results are convincing - effects are strong, sample sizes are sufficient, and the authors also rule out alternative explanations (ruling out differences in motor behavior or perceptual processing per se).

Weaknesses:<br /> My main concern is that the paper should be more transparent about both (1) that this study does not include individuals with autism, and (2) acknowledging the limitations of the AQ.

On the first point, and I don't think this is intentional, there are several instances where the line between heightened autistic traits in the NT population and ASD is blurred or absent. For example, in the second sentence of the abstract, the authors state "Here, we examine the idea that sensory overload in ASD may be linked to issues with efference copy mechanisms". I would say this is not correct because the authors did not test individuals with ASD. I don't see a problem with using ASD to motivate and discuss this work, but it should be clear in key places that this was done using AQ in NT individuals.

For the second issue, the AQ measure itself has some problems. For example, reference 38 in the paper (a key paper on AQ) also shows that those with high AQ skew more male than modern estimates of ASD, suggesting that the AQ may not fully capture the full spectrum of ASD symptomatology. Of course, this does not mean that the AQ is not a useful measure (the present data clearly show that it captures something important about spatial updating during eye movements), but it should not be confused with ASD, and its limitations need to be acknowledged. My recommendation would be to do this in the title as well - e.g. note impaired visuomotor updating in individuals with "heightened autistic traits".

Suggestions for improvement:<br /> - Figure 5 is really interesting. I think it should be highlighted a bit more, perhaps even with a model that uses the results of both tasks to predict AQ scores.<br /> - Some discussion of the memory demands of the tasks will be helpful. The authors argue that memory is not a factor, but some support for this is needed.<br /> - With 3 sessions for each experiment, the authors also have data to look at learning. Did people with high AQ get better over time, or did the observed errors/biases persist throughout the experiment?

Reviewer #2 (Public Review):

Summary:<br /> The idea that various clinical conditions may be associated, at least partially, with a disrupted corollary discharge mechanism has been present for a long time.

In this paper, the authors draw a link between sensory overload, a characteristic of autism spectrum disorder, and a disturbance in the corollary discharge mechanism. The authors substantiate their hypothesis with strong evidence from both the motor and perceptual domains. As a result, they broaden the clinical relevance of the corollary discharge mechanism to encompass autism spectrum disorder.

The authors write:<br /> "Imagine a scenario in which you're watching a video of a fast-moving car on a bumpy road. As the car hits a pothole, your eyes naturally make quick, involuntary saccades to keep the car in your visual field. Without a functional efference copy system, your brain would have difficulty accurately determining the current position of your eye in space, which in turn affects its ability to anticipate where the car should appear after each eye movement."

I appreciate the use of examples to clarify the concept of efference copy. However, I believe this example is more related to a gain-field mechanism, informing the system about the position of the eye with respect to the head, rather than an example of efference copy per se.

Without an efference copy mechanism, the brain would have trouble accurately determining where the eyes will be in space after an eye movement, and it will have trouble predicting the sensory consequences of the eye movement. However it can be argued that the gain-field mechanism would be sufficient to inform the brain about the current position of the eyes with respect to the head.

The authors write:<br /> "In the double-step paradigm, two consecutive saccades are made to briefly displayed targets 21, 22. The first saccade occurs without visual references, relying on internal updating to determine the eye's position."

Maybe I have missed something, but in the double-step paradigm the first saccade can occur without the help of visual references if no visual feedback is present, that is, when saccades are performed in total darkness. Was this the case for this experiment? I could not find details about room conditions in the methods. Please provide further details.

In case saccades were not performed in total darkness, then the first saccade can be based on the remembered location of the first target presented, which can be derived from the retinotopic trace of the first stimuli, as well as the contribution from the surroundings, that is: the remembered relative location of the first target with respect to the screen border along the horizontal meridian (i.e. allocentric cues).

A similar logic could be applied to the second saccade. If the second saccade were based only on the retinotopic trace, without updating, then it would go up and 45 deg to the right, based on the example shown in Figure 1. With appropriate updating, the second saccade would go straight up. However, if saccades were not performed in total darkness, then the location of the second target could also be derived from its relationship with the surroundings (for example, the remembered distance from screen borders, i.e. allocentric cues).

If saccades were not performed in total darkness, the results shown in Figures 2 and 3 could then be related to i) differences in motor updating between AQ score groups; ii) differences in the use of allocentric cues between AQ score groups; iii) a combination of i) and ii). I believe this is a point worth mentioning in the discussion."

The authors write:<br /> "According to theories of saccadic suppression, an efference copy is necessary to predict the occurrence of a saccade."

I would also refer to alternative accounts, where saccadic suppression appears to arise as early as the retina, due to the interaction between the visual shift introduced by the eye movement, and the retinal signal associated with the probe used to measure saccadic suppression. This could potentially account for the scaling of saccadic suppression magnitude with saccade amplitude.

Idrees, S., Baumann, M.P., Franke, F., Münch, T.A. and Hafed, Z.M., 2020. Perceptual saccadic suppression starts in the retina. Nature communications, 11(1), p.1977.

Reviewer #3 (Public Review):

Summary:<br /> This work examined efference copy related to eye movements in healthy adults who have high autistic traits. Efference copies allow the brain to make predictions about sensory outcomes of self-generated actions, and thus serve important roles in motor planning and maintaining visual stability. Consequently, disrupted efference copies have been posited as a potential mechanism underlying motor and sensory symptoms in psychopathology such as Autism Spectrum Disorder (ASD), but so far very few studies have directly investigated this theory. Therefore, this study makes an important contribution as an attempt to fill in this knowledge gap. The authors conducted two eye-tracking experiments examining the accuracy of motor planning and visual perception following a saccade and found that participants with high autistic traits exhibited worse task performance (i.e., less accurate second saccade and biased perception of object displacement), consistent with their hypothesis of less impact of efference copies on motor and visual updating. Moreover, the motor and visual biases are positively correlated, indicative of a common underlying mechanism. These findings are promising and can have important implications for clinical intervention if they can be replicated in a clinical sample.

Strengths:<br /> The authors utilized well-established and rigorously designed experiments and sound analytic methods. This enables easy translations between similar work in non-human primates and humans and readily points to potential candidates for underlying neural circuits that could be further examined in follow-up studies (e.g., superior colliculus, frontal eye fields, mediodorsal thalamus). The finding of no association between initial saccade accuracy and level of autistic trait in both experiments also serves as an important control analysis and increases one's confidence in the conclusion that the observed differences in task performance were indeed due to disrupted efference copies, not confounding factors such as basic visual/motor deficits or issues with working memory. The strong correlation between the observed motor and visual biases further strengthens the claim that the findings from both experiments may be explained by the same underlying mechanism - disrupted efference copies. Lastly, the authors also presented a thoughtful and detailed mechanistic theory of how efference copy impairment may lead to ASD symptomatology, which can serve as a nice framework for more research into the role of efference copies in ASD.

Weaknesses:<br /> Although the paper has a lot of strengths, the main weakness of the paper is that a direct link with ASD symptoms (i.e., sensory overload and motor inflexibility as the authors suggested) cannot be established. First of all, the participants are all healthy adults who do not meet the clinical criteria for an ASD diagnosis. Although they could be considered a part of the broader autism phenotype, the results cannot be easily generalized to the clinical population without further research. Secondly, the measure used to quantify the level of autistic traits, Autistic Quotient (AQ), does not actually capture any sensory or motor symptoms of ASD. Therefore, it is unknown whether those who scored high on AQ in this study experienced high, or even any, sensory or motor difficulties. In other words, more evidence is needed to demonstrate a direct link between disrupted efference copies and sensory/motor symptoms in ASD.

eLife assessment

This study provides a valuable contribution to understanding the neural mechanisms underlying age-related changes in attention and speech understanding. The large dataset (N=105) provides convincing evidence for how speech recognition behaviour and neural tracking of speech separately evolve in about 2 years. The work would be of interest to psychologists, neuroscientists, and audiologists.

Reviewer #1 (Public Review):

Summary:

This study investigated behavioural performance on a competing speech task and neural attentional filtering over the course of two years in a group of middle-aged to older adults. Neural attentional filtering was quantified using EEG by comparing neural envelope tracking to an attended vs. an unattended sentence. This dataset was used to examine the stability of the link between behavior and neural filtering over time. They found that neural filtering and behavior were correlated during each measurement, but EEG measures at the first timepoint did not predict behavioural performance two years later. Further, while behavioural measures showed relatively high test-retest reliability, the neural filtering reliability was weak with an r value of 0.21. The authors conclude that neural tracking-based metrics have limited ability to predict longitudinal changes in listening behavior.

Strengths:

This study is novel in its tracking of behavioural performance and neural envelope tracking over time, and it includes an impressively large dataset of 105 participants. The manuscript is clearly written.

Weaknesses:

The weaknesses are minor, primarily concerning how the reviewers interpret their data. Specifically, the envelope tracking measure is often quite low, close to the noise floor, and this may affect test-retest reliability. Furthermore, the trajectories may be affected by accelerated age-related declines that are more apparent in neural tracking than in behaviour.

Comments on revised version:

The authors have satisfactorily addressed my previous comments and they present a strong case for the interpretation of their findings.

Reviewer #2 (Public Review):

Summary:<br /> This study examined the longitudinal brain-behaviour link between attentional neural filtering and listening behaviour among a sample of aging individuals. The results based on the latent change score modeling showed that neither attentional neural filtering at T1 nor its T1-T2 change predicted individual two-year listening performance change. The findings suggest that neural filtering and listening behaviour may follow independent developmental trajectories. This study focuses on an interesting topic and has the potential to contribute a better understanding of the neurobiological mechanisms of successful communication across the lifespan.

Strengths:<br /> Although research suggests that speech comprehension is neurally supported by an attention-guided filter mechanism, the evidence on their causal association is limited. This study addresses this gap by testing longitudinal stability of neural filtering as a neural mechanism upholding listening performance, potentially shedding lights on translational efforts aiming at the preservation of speech comprehension abilities among aging individuals.

The latent change score modeling approach is appropriately used as a tool to examine key developmental questions and distinguish the complex processes underlying lifespan development in brain and behaviour with longitudinal data.

Weaknesses:<br /> Although the paper does have strengths in principle, the weaknesses of the paper are that the findings are merely based on a single listening task. Since both neural and behavioral indicators are derived from the same task, the results may be applicable only to this specific task, and it is difficult to extrapolate them to cognitive and listening abilities measured by the other tasks. Therefore, more listening tasks are required to comprehensively measure speech comprehension and neural markers.

The age span of the sample is relatively large. Although no longitudinal change from T1 to T2 was found at the group-level, from the cross-sectional and longitudinal change results (see Figure 3), individuals of different age groups showed different development pattern. Particularly, individuals over the age of 70 show a clear downward trend in both neural filtering index and accuracy. Therefore, different results may be found based on different age groups, especially older groups. However, due to sample limitations, this study was unable to examine whether age has a moderating effect on this brain-behaviour link.

In the Dichotic listening task, valid and invalid cues were manipulated. According to the task description, the former could invoke selective attention, whereas the latter could invoke divided attention. It is possible that under the two conditions, the neural filtering index may reflect different underlying cognitive processes, and thus may differ in its predictive effect on behavioral performance. The author could perform a more in-depth data analysis on indicators under different conditions.

Reviewer #1 (Public Review):

Summary:

Walsh and colleagues investigated how cued probabilistic expectations about future stimuli may influence different stages of decision-making as implemented in the human brain. In their study, participants were provided with cues that could correctly (or incorrectly) cue which visual stimulus would be presented. These cues also predicted the motor action that would likely produce a correct judgment for that trial. In addition a 'neutral' cue was included that did not predict any particular stimulus. They report that measures of steady-state visual evoked potentials (SSVEPs, proposed to index the magnitude of visual neural activity in favour of the correct response) were smaller when the cue incorrectly predicted the upcoming image, compared to when an accurate cue or a neutral cue was presented. Their primary finding adds to an ongoing debate in the field of decision-making research about how cued expectations may influence how we make decisions.

Strengths:

This study uses a carefully-constructed experiment design and decision-making task that allows separation of multiple electroencephalographic (EEG) signals thought to track different stages of decision-making. For example, the steady-state visual evoked potential measures can be cleanly dissociated from more anterior beta-band activity over motor cortex. They also allow evaluation of how cued expectancy effects may unfold over a number of testing sessions. This is important because the most consistent evidence of expectation-related modulations of electrophysiological measures (using EEG, local field potentials or single neuron firing rates) is from studies of non-human primates that involved many days of cue-stimulus contingency learning, and there is a lack of similar work using several testing sessions in humans. Although there were several experimental conditions included in the study, careful trial-balancing was conducted to minimise biases due to incidental differences in the numbers of trials included for analyses across each condition. Performance for each individual was also carefully calibrated to maximise the possibility of identifying subtle changes in task performance by expectation and avoid floor or ceiling effects.

Weaknesses:

Although the experiment and analysis methods are cohesive and well-designed, there are some shortcomings that limit the inferences that can be drawn from the presented findings.

The first relates to the measures of SSVEPs and their relevance for decision-making in the task. In order to eliminate the influence of sporadic pulses of contrast changes that occurred during stimulus presentation, a time window of 680-975 ms post stimulus onset was used to measure the SSVEPs. As shown in the response time quantile plot in Supplementary Figure S1, a substantial portion of response times are earlier than all, or a portion of, the time period included in the SSVEP measurement window. It has also been estimated to require 70-100 ms to execute a motor action (e.g., a keypress response) following the commitment to a decision. This raises some concerns about the proportion of trials in which the contrast-dependent visual responses (indexed by the stimulus-locked SSVEPs) indexed visual input that was actually used to make the decision in a given trial. While response-locked SSVEP plots are provided, statistical analyses testing for differences during the pre-response period were not performed. Standard errors in Figure 4D (depicting differences in SSVEPs for validly and invalidly cued trials) partly overlap with zero during the pre-response time window. There is no strong evidence for clear SSVEP modulations in any specific time windows leading to the response.

In addition, an argument is made for changes in the evidence accumulation rate (called the drift rate) by stimulus expectancy, corresponding to the observed changes in SSVEP measures and differences in the sensory encoding of the stimulus. As the authors acknowledge, this inference is limited by the fact that evidence accumulation models (such as the Diffusion Decision Model) were not used to test for drift rate changes as could be determined from the behavioural data (by modelling response time distributions). Plots of response quantiles in Supplementary Figure S1 also do not show a typical pattern that indicates changes in the drift rate (i.e., larger differences between validly and invalidly cued trials for relatively slower response time quantiles). There appear to be ample numbers of trials per participant to test for drift rate changes in addition to the starting point bias captured in earlier models. Due to the very high number of trials, models could potentially be evaluated for each single participant, although modelling would be substantively complicated by effects of the pulses of contrast changes, as noted by the authors. This could be done in future work (in experiments without contrast pulses) and would provide more direct evidence for drift rate changes than the findings based on the SSVEPs, particularly due to the issues with the measurement window relating to the response times as mentioned above.

In addition, there is some uncertainty regarding how to interpret the SSVEP effects in relation to phenomena such as expectation suppression enabled via sharpening or dampening effects. The measure used in this study is marginal SSVEPs, indexing the difference in SSVEP amplitudes between relatively higher- and lower-contrast gratings (termed target and non-target gratings). The observed increase in marginal SSVEPs for validly as compared to invalidly cued trials could arise due to an increase in SSVEP amplitudes for target grating orientations, a decrease for non-target orientations, a combination of these two, or even an increase or decrease for both target and non-target SSVEPs (with a larger increase/decrease for the target or non-target orientation). Some analyses were performed to investigate predictive cueing effects on target as compared to non-target SSVEPs, but these did not provide clear evidence that favoured a specific interpretation. This should be considered when interpreting the SSVEP effects in relation to different variants of expectation suppression that have been proposed in the literature.

Reviewer #2 (Public Review):

Summary:

We often have prior expectations about how the sensory world will change, but it remains an open question as to how these expectations are integrated into perceptual decisions. In particular, scientists have debated whether prior knowledge principally changes the decisions we make about the perceptual world, or directly alters our perceptual encoding of incoming sensory evidence.

The authors aimed to shed light on this conundrum by using a novel psychophysical task while measuring EEG signals that have previously been linked to either the sensory encoding or response selection phase of perceptual choice. The results convincingly demonstrate that both features of perceptual decision making are modulated by prior expectations - but that these biases in neural process emerge over different time courses (i.e., decisional signals are shaped early in learning, but biases in sensory processing are slower to emerge).

Another interesting observation unearthed in the study - though not strictly linked to this perceptual/decisional puzzle - is that neural signatures of focused attention are exaggerated on trials where participants are given neutral (i.e. uninformative) cues. This is consistent with the idea that observers are more attentive to incoming sensory evidence when they cannot rely on their expectations.

In general, I think the study makes a strong contribution to the literature, and does an excellent job of separating 'perceiving' from 'responding'. More perhaps could have been done though to separate 'perceiving' and 'responding' from 'deciding' (see below).

Strengths:

The work is executed expertly and focuses cleverly on two features of the EEG signals that can be closely connected to specific loci of the perceptual decision making process - the SSVEP which connects closely to sensory (visual) encoding, and Mu-Beta lateralisation which connects closely to movement preparation. This is a very appropriate design choice given the authors' research question.

Another advantage of the design is the use of an unusually long training regime (i.e., for humans) - which makes it possible to probe the emergence of different expectation biases in the brain over different timecourses, and in a way that may be more comparable to work with nonhuman animals (who are routinely trained for much longer than humans).

Weaknesses:

In my view, the principal shortcoming of this study is that the experimental task confounds expectations about stimulus identity with expectations about to-be-performed responses. That is, cues in the task don't just tell participants what they will (probably) see, but what they (probably) should do.

In many respects, this feature of the paradigm might seem inevitable, as if specific stimuli are not connected to specific responses, it is not possible to observe motor preparation of this kind (e.g., de Lange, Rahnev, Donner & Lau, 2013 - JoN).

However, the theoretical models that the authors focus on (e.g., drift diffusion models) are models of decision (i.e., commitment to a proposition about the world) as much as they are models of choice (i.e., commitment to action). Expectation researchers interested in these models are often interested in asking whether predictions influence perceptual processing, perceptual decision and/or response selection stages (e.g., Feuerriegel, Blom & Hoogendorn, 2021 - Cortex), and other researchers have shown that parameters like drift bias and start point bias can be shifted in paradigms where observers cannot possibly prepare a response (e.g., Thomas, Yon, de Lange & Press, 2020 - Psych Sci).

The present paradigm used by Walsh et al makes it possible to disentangle sensory processing from later decisional processes, but it blurs together the processes of deciding about the stimulus and choosing/initiating the response. This ultimately limits the insights we can draw from this study - as it remains unclear whether rapid changes in motor preparation we see reflect rapid acquisition of new decision criterion or simple cue-action learning. I think this would be important for comprehensively testing the models the authors target - and a good avenue for future work.

In revising the manuscript after an initial round of revisions, the authors have done a good job of acknowledging these complexities - and I don't think that any of these outstanding scientific puzzles detract from the value of the paper as a whole.

Reviewer #3 (Public Review):

Observers make judgements about expected stimuli faster and more accurately. How expectations facilitate such perceptual decisions remains an ongoing area of investigation, however, as expectations may exert their effects in multiple ways. Expectations may directly influence the encoding of sensory signals. Alternatively (or additionally), expectations may influence later stages of decision-making, such as motor preparation, when they bear on the appropriate behavioral response.

In the present study, Walsh and colleagues directly measured the effect of expectations on sensory and motor signals by making clever use of the encephalogram (EEG) recorded from human observers performing a contrast discrimination task. On each trial, a predictive cue indicated which of two superimposed stimuli would likely be higher contrast and, therefore, whether a left or right button press was likely to yield a correct response. Deft design choices allowed the authors to extract both contrast-dependent sensory signals and motor preparation signals from the EEG. The authors provide compelling evidence that, when predictive cues provide information about both a forthcoming stimulus and the appropriate behavioral response, expectation effects are immediately manifest in motor preparation signals and only emerge in sensory signals after extensive training.

Future work should attempt to reconcile these results with related investigations in the field. As the authors note, several groups have reported expectation-induced modulation of sensory signals (using both fMRI and EEG/MEG) on shorter timescales (e.g. just one or two sessions of a few hundred trials, versus the intensive multi-session study reported here). One interesting possibility is that perceptual expectations are not automatic but demand the deployment of feature-based attention, while motor preparation is comparatively less effortful and so dominates when both sources of information are available, as in the present study. This hypothesis is consistent with the authors' thoughtful analysis showing decreased neural signatures of attention over posterior electrodes following predictive cues. Therefore, observing the timescale of sensory effects using the same design and methods (facilitating direct comparison with the present work), but altering task demands slightly such that cues are no longer predictive of the appropriate behavioral response, could be illuminating.

eLife assessment

This paper explores the relationships among evolutionary and epidemiological quantities in influenza, and presents fundamental findings that substantially advance our understanding of the drivers of influenza epidemics. The authors use a rich set of data sources to gather and analyze compelling evidence on the roles of genetic distance, other influenza dynamics and epidemiological indicators in predicting influenza epidemics. The central findings highlight the significant influence of genetic distance on A(H3N2) virus epidemiology and emphasize the role of A(H1N1) virus incidence in shaping A(H3N2) epidemics, suggesting subtype interference as a key factor. This paper also makes relevant data available to the research community.

Reviewer #1 (Public Review):

Summary:<br /> The authors aimed to investigate the contribution of antigenic drift in the HA and NA genes of seasonal influenza A(H3N2) virus to their epidemic dynamics. Analyzing 22 influenza seasons before the COVID-19 pandemic, the study explored various antigenic and genetic markers, comparing them against indicators characterizing the epidemiology of annual outbreaks. The central findings highlight the significant influence of genetic distance on A(H3N2) virus epidemiology and emphasize the role of A(H1N1) virus incidence in shaping A(H3N2) epidemics, suggesting subtype interference as a key factor.

Major Strengths:<br /> The paper is well-organized, written with clarity, and presents a comprehensive analysis. The study design, incorporating a span of 22 seasons, provides a robust foundation for understanding influenza dynamics. The inclusion of diverse antigenic and genetic markers enhances the depth of the investigation, and the exploration of subtype interference adds valuable insights.

Major Weaknesses:<br /> While the analysis is thorough, some aspects require deeper interpretation, particularly in the discussion of certain results. Clarity and depth could be improved in the presentation of findings. Furthermore, the evolving dynamics of H3N2 predominance post-2009 need better elucidation.

Reviewer #2 (Public Review):

Summary: This paper aims to achieve a better understanding of how the antigenic or genetic compositions of the dominant influenza A viruses in circulation at a given time are related to key features of seasonal influenza epidemics in the US. To this end, the authors analyse an extensive dataset with a range of statistical, data science and machine learning methods. They find that the key drivers of influenza A epidemiological dynamics are interference between influenza A subtypes and genetic divergence, relative to the previous one or two seasons, in a broader range of antigenically related sites than previously thought.

Strengths: A thorough investigation of a large and complex dataset.

Weaknesses: The dataset covers a 21 year period which is substantial by epidemiological standards, but quite small from a statistical or machine learning perspective. In particular, it was not possible to follow the usual process and test predictive performance of the random forest model with an independent dataset.

Reviewer #3 (Public Review):

Summary:<br /> This paper explores the relationships among evolutionary and epidemiological quantities in influenza, using a wide range of datasets and features, and using both correlations and random forests to examine, primarily, what are the drivers of influenza epidemics. It's a strong paper representing a thorough and fascinating exploration of potential drivers, and it makes a trove of relevant data readily available to the community.

Strengths:<br /> This paper makes links between epidemiological and evolutionary data for influenza. Placing each in the context of the other is crucial for understanding influenza dynamics and evolution and this paper does a thorough job of this, with many analyses and nuances. The results on the extent to which evolutionary factors relate to epidemic burden, and on interference among influenza types, are particularly interesting. The github repository associated with the paper is clear, comprehensive, and well-documented.

Weaknesses:<br /> The format of the results section can be hard to follow, and we suggest improving readability by restructuring and simplifying in some areas. There are a range of choices made about data preparation and scaling; the authors could explore sensitivity of the results to some of these.

eLife assessment

In this important study, the authors develop a promising experimental approach to a central question in ecology: What are the contributions of resource use and interactions in the shaping of an ecosystem? For this, they develop a synthetic ecosystem set-up, a variant of SELEX that allows very detailed control over ecological variables. The evidence is convincing, and the work should be of broad interest to the ecology community, leading to further quantitative studies.

Reviewer #1 (Public Review):

This work describes a new and powerful approach to a central question in ecology: what are the relative contributions of resource utilisation vs interactions between individuals in the shaping of an ecosystem? This approach relies on a very original quantitative experimental set-up whose power lies in its simplicity, allowing an exceptional level of control over ecological parameters and of measurement accuracy.

In this experimental system, the shared resource corresponds to 10^12 copies of a fixed single stranded target DNA molecule to which 10^15 random single stranded DNA molecules (the individuals populating the ecosystem) can bind. The binding process is cycled, with a 1000x-PCR amplification step between successive binding steps. The composition of the population is monitored via high-throughput DNA sequencing. Sequence data analysis describes the change of population diversity over cycles. The results are interpreted using estimated binding interactions of individuals with the target resource, as well as estimated binding interactions between individuals and also self-interactions (that can all be directly predicted as they correspond to DNA-DNA interactions). A simple model provides a framework to account for ecosystem dynamics over cycles. Finally, the trajectory of some individuals with high frequency in late cycles is traced back to the earliest cycles at which they are detected by sequencing. Their propensities to bind the resource, to form hairpins or to form homodimers suggest how different interaction modes shape the composition of the population over cycles.

The authors report a shift from selection for binding to the resource to interactions between individuals and self-interactions over the course of cycles as the main driver of their ecosystem. The outcome of the experiment is far from trivial as the individual-resource binding energy initially determines the relative enrichment of individuals, and then seems to saturate. The richness of the population dynamics observed with this simple system is thus comparable to that found in some natural ecosystems. The findings obtained with this new approach will likely guide the exploration of natural ecosystems in which parameters and observables are much less accessible.

My review focuses mainly on experimental aspects of this work given my own expertise. The introduction exposes very convincingly the scientific context of this work, justifying the need for such an approach to address questions pertaining to ecology. The manuscript describes very clearly and rigorously the experimental set-up. The main strengths of this work are (i) the outstanding originality of the experimental approach and (ii) its simplicity. With this setup, central questions in ecology can be addressed in a quantitative manner, including the possibility to run trajectories in parallel to generalize the findings, as reported here. Technical aspects have been carefully implemented, from the design of random individuals bearing flanking regions for PCR amplification, binding selection and (low error) amplification protocols, and sequencing read-out whose depth is sufficient to capture the relevant dynamics. With this setup one can tune the relative contributions of binding selection vs amplification for instance (to disentangle forces that shape the ecosystem). One can also run cycles with new DNA individuals, designed with arbitrarily chosen resource binding vs self-binding, that are predicted to dominate depending on chosen ecological parameters. These exciting perspectives underlie the strong potential of the new approach described in the current study.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors introduced ADSE, a SELEX-based protocol to explore the mechanism of emergency of species. They used DNA hybridization (to the bait pool, "resources") as the driving force for selection and quantitatively investigated the factors that may contribute to the survival during generation evolve (progress of SELEX cycle), revealing that besides individual-resource binding, the inter- and intra-individual interactions were also important features along with mutualism and parasitism.

Strengths:<br /> The design of using pure biochemical affinity assay to study eco-evolution is interesting, providing an important viewpoint to partly explain the molecular mechanism of evolution.

Reviewer #2 (Public Review):

Pheochromocytoma (PCC), a rare neuroendocrine tumor, is currently considered malignant, but non-surgical treatment options are very limited and there is an urgent need for more basic research to support the development of new therapeutic approaches. In the present work, the authors described the intra- and inter-tumor heterogeneity by performing scRNA-seq on tumor samples from five patients with PCC, and evaluated the corresponding PASS scores.

Strengths: The tumor microenvironment of PCC was characterized and potential molecular classification criteria based on single-cell transcriptomics were proposed, offering new theoretical possibilities for the treatment of PCC. The article is logically written and the results are clearly presented.

Weaknesses: I still have concerns about some of the article's content. My main concerns are: In this study, the authors seem to have demonstrated the inaccuracy of a subjective score (PASS) by another objective means (scRNA-seq). In fact, the multiparametric scoring systems such as PASS are no longer endorsed in the 2022 WHO guidelines. The PASS scoring system does not have a high positive predictive value for risk stratification of PCC metastasis, but "rule-out" of metastasis risk with a PASS score of <4 seems to be fairly reliable. Could the authors please explain why the PASS scores were chosen rather than the GAPP, m-GAPP, or COPPS scoring systems? If possible, please try to emphasize the importance and necessity of using the PASS scoring system, either by replacing it with a more acceptable scoring system or by deleting the relevant part, which does not seem to be very relevant to the subject of the article.

Moreover, I noted the following statement in the text "There are no studies reporting the composition of immune cells in PCCs. The few published studies investigating the immune microenvironment of PCCs have been limited to the expression of PDL1 at the histological level and to assessment of the tumor mutation burden (TMB) at the genomic level, and these results only seem to suggest that PCCs are immune-cold (Bratslavsky et al, 2019; Guo et al, 2019; Pinato et al, 2017)." This statement is very wrong. The reason for this error may be that the authors did not adequately search and read the relevant literature. I noticed that almost all references in this paper are dated 2021 and earlier, which is surprising. Please update the references cited in this paper in a comprehensive and detailed manner; referring to literature published too early may lead to inadequate discussion or even one-sided or incorrect conclusions and conjectures.

For example, the text statement "Combined with previously reported negative regulatory effects of kinases (such as RET, ALK, and MEK) on HLA-I expression on tumor cells (Brea et al., 2016; Oh et al., 2019), we speculate that the possible reason for inability in recruiting CD8+ T cells of kinase-type PCCs is the downregulation of HLA-I in tumor cells regulated by RET, while the mechanism of immune escape in metabolism-type PCCs (with antigen presentation ability) needs to be further explored. Our results also indicate that the application of immunotherapy to metabolism-type PCCs is likely unsuitable, while kinase-type PCCs may have the potential of combined therapy with kinase inhibitors and immunotherapy." is rather one-sided; in fact, the presence of immune escape in PCC, as the malignancy with the lowest tumor mutation compliance, has been well characterized, and the low number of infiltrating T cells in tumor tissue may be influenced by a variety of factors, such as the release of catecholamines, the expression of inhibitory receptors on the surface of T cells, and so on, although genetic mutation still plays the most crucial role. The Discussion section also has a lot of information that needs to be updated or corrected and expanded, so please rewrite the above section with sufficiently updated references.

Below I have listed some references for the authors to read:

Tufton N, Hearnden RJ, Berney DM, et al. The immune cell infiltrate in the tumour microenvironment of phaeochromocytomas and paragangliomas. Endocr Relat Cancer. 2022;29(11):589-598. Published 2022 Sep 19. doi:10.1530/ERC-22-0020<br /> Jin B, Han W, Guo J, et al. Initial characterization of immune microenvironment in pheochromocytoma and paraganglioma. Front Genet. 2022;13:1022131. Published 2022 Dec 7. doi:10.3389/fgene.2022.1022131<br /> Celada L, Cubiella T, San-Juan-Guardado J, et al. Pseudohypoxia in paraganglioma and pheochromocytoma is associated with an immunosuppressive phenotype. J Pathol. 2023;259(1):103-114. doi:10.1002/path.6026<br /> Calsina B, Piñeiro-Yáñez E, Martínez-Montes ÁM, et al. Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma. Nat Commun. 2023;14(1):1122. Published 2023 Feb 28. doi:10.1038/s41467-023-36769-6

Reviewer #3 (Public Review):

The main findings of this study are as follows: (1) The authors defined "metabolism-type" and "kinase-type" in unclassified sporadic PCC patients through the single-cell transcriptomics-based differentially expressed genes and functional enrichment analyses. (2) They identified the limitation of Pheochromocytoma of the Adrenal gland Scaled Score (PASS) system and suggested the combination of molecular diagnostic methods like scRNA-seq with pathological tools like PASS in aiding the clinical evaluation of PCCs. (3) Analysis of the PCC microenvironment revealed a lack of immune cell infiltration in both metabolism-type and kinase-type PCCs, while only the kinase-type PCC patient exhibited the low expression of HLA-Ⅰ that potentially regulated by RET, providing clues for the combined therapy with kinase inhibitors and immunotherapy in kinase-type PCC patients.

The main strength of this manuscript is that it involves scRNA-seq analysis of an extremely rare tumor type-PCCs, which presents a single-cell transcriptomics-based molecular classification and microenvironment characterization of PCCs and further provides clues for potential therapeutic strategies to treat PCCs. The authors also validated the scRNA-seq analysis results (such as the expression levels of marker genes and the distribution of immune cells in the PCC microenvironment) with immunocytochemistry and multispectral immunofluorescent staining. In summary, the findings in this manuscript are quite interesting and significant, which will potentially be valuable for the molecular classification of PCCs.

eLife assessment

This valuable study describes mice with a knock out of the IQ motif-containing H (IQCH) gene, to model a human loss-of-function mutation in IQCH associated with male sterility. The infertility is reproduced in the mouse, making it a compelling model, but some of the mechanistic experiments provide only indirect and thus incomplete evidence for interaction between IQCH and potential RNA binding proteins. With more rigorous approaches, the paper should be of interest to cell biologists and male reproductive biologists working on the sperm flagellar cytoskeleton and mitochondrial structure.

Reviewer #1 (Public Review):

By identifying a loss of function mutant of IQCH in infertile patient, Ruan et al. shows that IQCH is essential for spermiogenesis by generating a knockout mouse model of IQCH. Similar to infertile patient with mutant of IQCH, Iqch knockout mice are characterized by a cracked flagellar axoneme and abnormal mitochondrial structure. Mechanistically, IQCH regulates the expression of RNA-binding proteins (especially HNRPAB), which are indispensable for spermatogenesis.

Although this manuscript contains a potentially interesting piece of work that delineates a mechanism of IQCH that associates with spermatogenesis, this reviewer feels that a number of issues require clarification and re-evaluation for a better understanding of the role of IQCH in spermatogenesis. With the shortage of logics and supporting data, causal relationships are still not clear among IQCH, CaM, and HNRPAB. The most serious point in this manuscript could be that the authors try to generalize their interpretations with too simplified model from limited pieces of their data. The way the data and the logic are presented needs to be largely revised, and several interpretations should be supported by direct evidence.

Reviewer #2 (Public Review):

The manuscript of "IQCH regulates spermatogenesis by interacting with CaM to promote RNA-binding proteins' expression" from Ruan et al. identified a homozygous variant affect the splicing of IQCH in two infertile men from a Chinese family. The authors also generated a Iqch knockout mouse model to confirm the abnormal sperm phenotypes associated with IQCH deficiency. Further molecular biological assays supported the important role and mechanism of IQCH in spermatogenesis. This manuscript is informative for the clinical and basic research of male infertility.

Reviewer #3 (Public Review):

In this study, Ruan et al. investigate the role of the IQCH gene in spermatogenesis, focusing on its interaction with calmodulin and its regulation of RNA-binding proteins. The authors examined sperm from a male infertility patient with an inherited IQCH mutation as well as Iqch CRISPR knockout mice. The authors found that both human and mouse sperm exhibited structural and morphogenetic defects in multiple structures, leading to reduced fertility in Ichq-knockout male mice. Molecular analyses such as mass spectrometry and immunoprecipitation indicated that RNA-binding proteins are likely targets of IQCH, with the authors focusing on the RNA-binding protein HNRPAB as a critical regulator of testicular mRNAs. The authors used in vitro cell culture models to demonstrate an interaction between IQCH and calmodulin, in addition to showing that this interaction via the IQ motif of IQCH is required for IQCH's function in promoting HNRPAB expression. In sum, the authors concluded that IQCH promotes male fertility by binding to calmodulin and controlling HNRPAB expression to regulate the expression of essential mRNAs for spermatogenesis. These findings provide new insight into molecular mechanisms underlying spermatogenesis and how important factors for sperm morphogenesis and function are regulated.

The strengths of the study include the use of mouse and human samples, which demonstrate a likely relevance of the mouse model to humans; the use of multiple biochemical techniques to address the molecular mechanisms involved; the development of a new CRISPR mouse model; ample controls; and clearly displayed results. There are some minor weaknesses in that more background details could be provided to the reader regarding the proteins involved; some assays could benefit from more rigorous quantification; some of the mouse testis images and analyses could be improved; and larger sample sizes, especially for the male mouse breeding tests, could be increased. Overall, the claims made the authors in this manuscript are well-supported by the data provided, but there some technical issues that, if addressed, could increase the robustness and rigor of the study.

1. More background details are needed regarding the proteins involved, in particular IQ proteins and calmodulin. The authors state that IQ proteins are not well-represented in the literature, but do not state how many IQ proteins are encoded in the genome. They also do not provide specifics regarding which calmodulins are involved, since there are at least 5 family members in mice and humans. This information could help provide more granular details about the mechanism to the reader and help place the findings in context.

2. The mouse fertility tests could be improved with more depth and rigor. There was no data regarding copulatory plug rate; data was unclear regarding how many WT females were used for the male breeding tests and how many litters were generated; the general methodology used for the breeding tests in the Methods section was not very explicitly or clearly described; the sample size of n=3 for the male breeding tests is rather small for that type of assay; and, given that ICHQ appears to be expressed in testicular interstitial cells (Fig. S10) and somewhat in other organs (Fig. S2), another important parameter of male fertility that should be addressed is reproductive hormone levels (e.g., LH, FSH, and testosterone). While normal epididymal size in Fig. S3 suggests that hormone (testosterone) levels are normal, epididymal size and/or weight were not rigorously quantified.

3. The Western blots in Figure 6 should be rigorously quantified from multiple independent experiments so that there is stronger evidence supporting claims based on those assays.

4. Some of the mouse testis images could be improved. For example, the PNA and PLCz images in Figure S7 are difficult to interpret in that the tubules do not appear to be stage-matched, and since the authors claimed that testicular histology is unaffected in knockout testes, it should be feasible to stage-match control and knockout samples. Also, the anti-ICHQ and CaM immunofluorescence in Figure S10 would benefit from some cell-type-specific co-stains to more rigorously define their expression patterns, and they should also be stage-matched.

eLife assessment

This study presents a valuable examination into the role Notch-RBP-J signalling in regulating monocyte subset homeostasis. The data were collected and analysed using solid and validated methodology and can be used as a starting point for exploring the mechanisms involved in RBP-J signalling in non-classical monocytes. The data presented strongly confirm the authors conclusions. However, this paper primarily focuses on providing a description, and additional studies are necessary to fully elucidate the mechanisms through which RBP-J deficiency contributes to the specific increase in Ly6Clo monocyte numbers in both the blood and lungs.

Reviewer #1 (Public Review):

Kou and Kang et al. investigated the role of Notch-RBP-J signaling in regulating monocyte homeostasis. Specifically, they examined how a conditional knockout of Rbpj expression in monocytes though a Rbpjfl/fl Lyz2cre/cre mouse affects the homeostasis of Ly6Chi versus Ly6Clo monocytes. They discovered that Rbpj deficiency did not affect the percentage of Ly6Chi monocytes but instead, led to an accumulation of Ly6Clo monocytes in the peripheral blood. Using a comprehensive number of in vivo techniques to investigate the origin of this increase, the authors revealed that the accumulation of Rbpj deficient Ly6Clo monocytes was not due to an increase in bone marrow egress and homing and that this defect was cell intrinsic. However, EdU-labelling and apoptosis assays revealed that this defect was not due to an increase in proliferation nor conversion of Ly6Chi to Ly6Clo monocytes. Interestingly, it was revealed that Rbpj deficient Ly6Clo monocytes had increased expression of CCR2 and ablation of CCR2 expression reversed the accumulation of these cells in the periphery. Lastly, they discovered that Rbpj deficiency also led to downstream effects such as an accumulation of Ly6Clo monocytes in the lung tissue and increased CD16.2+ interstitial macrophages, presumably due to dysregulated monocyte differentiation and function.

Their findings are interesting and highlight a previously unexplored association between Notch-RBP-J signaling and CCR2 expression in monocyte homeostasis, providing further insight into the distinct pathways that regulate Ly6Chi vs Ly6Clo monocyte subsets individually.

The strengths of this paper include the use of multiple conditional genetic knock out mouse models to explore their hypothesis and the use of sophisticated in vivo techniques to study the major mechanisms involved in monocyte homeostasis. However, a major weakness of the paper is the exact role of how CCR2 compensates for the increase in Ly6Clo monocytes in the circulation in the RBP-J knockout mice as the authors showed no differences in their conversion, egress or homing back to the bone marrow. The authors were also unable to show that RBP-J knockout mice were functionally different in their response to CCL2 due to technical difficulties, which makes it challenging to conclude how CCR2 compensates for their trafficking patterns. Consequently the link between CCR2 and RBP-J remains correlative based on the data presented in the paper.

The conclusions of this paper are mostly well substantiated from the experimental data but as mentioned above, the mechanism of how CCR2 relates to the increase in Ly6Clo monocytes in RBP-J knockout mice is still unclear. Nevertheless, this work will be of interest to immunologists and biologists working on Notch-signalling in diseases. In addition, the methods and data would be useful for researchers who are seeking to use the Rbpjfl/fl Lyz2cre/cre mouse model for their studies.

Reviewer #2 (Public Review):

The authors provide a compelling data to demonstrate that the Notch-related transcription factor RBP-J can influence the number of circulating and recruited monocytes. The authors first delete the Rbpj gene in the myeloid lineage (Lyz2) and show that, as a proportion, only Ly6Clo monocytes are increased in the blood. The authors then attempted to identify why these cells were increased in proportion but ruled out proliferation or reduced apoptosis. Next, they investigated the gene signature of Rbpj null monocytes using RNA-sequencing and identified elevated Ccr2 as a defining feature. Crossing the Rbpj null mice to Ccr2 null mice showed reduced numbers of Ly6Clo monocytes compared with Rbpj null alone. Finally, the authors identify that an increased burden of blood Ly6Clo monocytes is correlated with increased lung recruitment and expansion of lung interstitial macrophages.

The main conclusion of the authors, that there is a 'cell intrinsic requirement of RBP-J for controlling blood Ly6CloCCR2hi monocytes' is strongly supported by the data. However, other claims and aspects of the study require clarification and further analysis of the data generated.

Strengths<br /> The paper is well written and structured logically. The major strength of this study is the multiple technically challenging methods used to reinforce the main finding (e.g. parabiosis, adoptive transfer). The finding reinforces the fact that we still know little about how immune cell subsets are maintained in situ, and this study opens the way for novel future work. Importantly, the authors have generated an RNA-sequencing dataset that will prove invaluable for identifying the mechanism - they have promised public access to this data via GEO - it is expected this will be made accessible upon publication.

Weaknesses - The main weakness of the study, is that although the main result is solidly supported, as written it is mostly descriptive in nature. For instance, there is no given mechanism by which RBP-J increases Ly6Clo monocytes. The authors conclude this is dependent on CCR2, however CCR2 deletion has a global effect on monocyte numbers and importantly in this study, it does not remove the Ly6Clo bias of cell proportions, if anything it seems to enhance the difference between the ly6C low and high populations in Rbpj null mice (figure 5C). This oversight in data interpretation likely occurred because: i) this experiment is missing a potentially important control (Lyz2cre/cre Ccr2RFP/RFP or RBP-J variations), and ii) lack of statistical comparisons between Ly6Clow and high subsets (e.g. two-way ANOVA design). In general, there seemed to be a focus on the Ly6C low cells, where the mechanism may be more identifiable in their precursors - likely the Ly6C high monocytes. Furthermore, the lack of this mechanism and data comparison may also be important, because it is possible that RBP-J signalling merely maintains the expression of Ly6C, rather than controls non-classical monocyte differentiation. In this case the comparison made for the sequencing data would be between Ly6C low non classical monocytes and 'artificially' Ly6C low classical monocytes. The basis of a population based on one marker is currently a widespread flaw in the field.

Other specific weaknesses were identified (note these are in addition to the more important comments above):<br /> 1) The confirmation of knockout in supplemental figure 1A shows only a two third knockdown when this should be almost totally gone. The authors have confirmed this is perhaps poor primer design and cite a study which shows almost complete reduction in protein levels (though this could be made more clear).<br /> 2) Many figures (e.g. 1A) only show proportional data (%) when the addition of cell numbers would also be informative - for example, what if Ly6Chigh cells were decreasing, thus artificially increasing the proportion of Ly6Clo cells? Looking at figure 7B - where cell numbers are shown, it is clear that cell proportion differences often do not match number data - here RBP-J knockout also increases Ly6C high cells in number (but not %).<br /> 3) It was noted previously that many figures only have an n of 1 or 2 (e.g. 2B, 2C), the authors clarified that some of these displayed one dot to represent an experiment of multiple n.<br /> 4) There is incomplete analysis (e.g. Network analysis, comparison to subset-restricted gene expression) and interpretation of RNA-sequencing results (figure 4), additionally the difference between the genotypes in both monocyte subsets would provide a more complete picture and potentially reveal mechanisms<br /> 6) The experiments in figure 5 are missing a control (Lyz2cre/cre Ccr2RFP/RFP or the Rbpj+/+ versions) and may have been misinterpreted. For example if the control (RBP-J WT, CCR2 KO) was used then it would almost certainly show falling Ly6C low numbers compared to RBP-J WT CCR2 WT, but RBP-J KO CCR2 KO would still have more Ly6c low monocytes than RBP-J WT, CCR2 KO - meaning that the RBP-J function is independent of CCR2. I.e. Ly6c low numbers are mostly dependent on CCR2 but this is irrespective of RBP-J. Explained in another way, the normal ratio of Ly6C high to low is around 1.5 Ly6Chigh cells for every one Ly6Clow cell, this is flipped in the RBP-J knockout to 1 high to 1.25 low (the main finding of the paper), but when CCR2 is removed it actually becomes 1 high to 5 low (actual numbers 0.2% vs around 1%) - in which case all CCR2 removal is doing is lowering the number of monocytes and RBP-J's mechanism is independent of CCR2.<br /> 7) Figure 6 was difficult to interpret because of the lack of shown gating strategy. The authors state they copied the strategy from Schyns et al. however in order to review this correctly the authors should show a supplemental figure of their own gating.<br /> 8) Figure 7 has the same problem as figure 5, but this time has the correct control. CCR2 ablation has a global suppression of monocyte numbers however the increased ly6c low monocyte ratio is most likely still present in the DKO mice - the lower numbers reduce the clarity of the data. Additionally in Lung IM macrophages depletion of CCR2 in the DKO only had a partial effect in some cell types - so CCR2 is playing a role, but it is not fully dependent. A good comparison would be if they blocked PU.1 expression - the effect of RBP-J would also be muted but it doesn't mean anything in terms of mechanism. Statements about the origin of the cells may need to be removed due to lack of compelling evidence.<br /> 9) Even after being notified and acknowledging the study, the authors still have not referred to or cited a similar 2020 study in their manuscript. This study also investigated myeloid deletion of Rbpj (Zhang et al. 2020 - https://doi.org/10.1096/fj.201903086RR). Zhang et al identified that Ly6Clo alveolar macrophages were decreased in this model - it is intriguing to synthesise these two studies and hypothesise that the ly6c low monocytes steal the lung niche, but this was not discussed. The authors also indicated they looked at AM but saw no difference - perhaps they should look specifically at Ly6Clow AMs in their data to compare with this study?

Reviewer #3 (Public Review):

In this study, the authors investigate the role of the Notch signalling regulator RBP-J on Ly6Clow monocyte biology starting with the observation that RBP-J-deficient mice have increased circulating Ly6low monocytes. Using myeloid specific conditional mouse models, the authors investigate how RBP-J deficiency effects circulating monocytes and lung interstitial macrophages.<br /> A major strength of this study is that it provides compelling evidence that RBP-J is a novel, critical factor regulating Ly6Clow monocyte cell frequency in the blood. The authors demonstrate that RBP-J deficiency leads to increased Ly6Clow monocytes in the blood and lung and CD16.2+ interstitial macrophages in steady state. The authors use a number of different techniques to confirm this finding including bone marrow transplantation experiments and parabiosis.

The main conclusion of the paper is that RBP-J controls the fate of Ly6ClowCCR2hi monocytes in a cell-intrinsic manner. This conclusion is strongly supported by the data provided. However, this paper is predominantly descriptive and further research is required to fully uncover the mechanisms by which RBP-J deficiency leads to Ly6Clo monocyte numbers increasing specifically in the blood and lungs and the consequence of RBP-J deficiency on Ly6C-low monocyte functionality.

The authors have performed RNA-seq and more in-depth analysis of this sequencing may provide clues for uncovering the thus far elusive mechanism.

Joint Public Review:

TGN46 is a prominent TGN protein that cycles to the plasma membrane. It has been used as a TGN marker for many years, but its function has been unknown. This manuscript provides evidence that the luminal domain of TGN46 serves as a cargo receptor for incorporation of the soluble secretory protein PAUF into a class of TGN-derived carriers called CARTS. Interestingly, the luminal domain also plays an important role in the intracellular and intra-Golgi localization of TGN46, and it contains a positive signal for Golgi export in CARTS. They demonstrate that TGN46 loading into CARTS is not dependent on its cytosolic terminus using a deltaCT mutant. A speculative part of the manuscript proposes that the luminal domain of TGN46 might form biomolecular condensates that help to capture cargo proteins for export.

This is a very nice study that makes a significant contribution to the field. New insights are obtained regarding the function of TGN46 and the role of its various domains. Various potential interpretations of the data are presented in a balanced and constructive way.

eLife assessment

This study provides an important finding that the local abundance of metabolites impacts the biology of the tumor microenvironment by utilizing kidney tumors from patients and adjacent normal tissues. The evidence supporting the claims of the authors is convincing although certain caveats need to be taken into consideration as the authors acknowledged in the paper. The work will be of interest to the research community working on metabolism and on kidney cancer especially.

Reviewer #1 (Public Review):

Summary:<br /> The present study addresses how the local abundance of metabolites impacts the biology of the tumor microenvironment. The authors enroll patients harboring kidney tumors and use freshly resected tumor material for metabolic studies. Specifically, the authors separate the adjacent normal kidney tissue from the tumor material and then harvest the interstitial fluid from the normal kidney (KIF) or the tumor (TIF) for quantitative metabolomics. The plasma samples from the patient are used for comparison. Additionally, the authors also compare metabolite levels in the plasma of patients with kidney versus lung cancer (or healthy donors) to address how specific tumor types might contribute to circulating levels of metabolites. Altogether, the authors find that the metabolite levels in the KIF and TIF, although vastly different than plasma, are largely overlapping. These findings indicate that tissue of origin appears to have a stronger role in determining the local metabolic environment of tumors than the genetics or biochemistry of the tumor itself.

Strengths:<br /> The biggest strength of the current study is the use of human patient-derived samples. The cohort size (~50 patients) is relatively large, which adds to the rigor of the work. The work also relies on a small pool of metabolites that can be quantitatively measured using methods developed by the authors. Focusing on a smaller metabolic pool also likely increases the signal-to-noise ratio and enables the more rigorous determination of any underlying differences. The manuscript is well-written and highlights both the significance of the findings and also acknowledges many of the caveats. The recognition of the metabolic contributions of surrounding normal tissue as the primary driver of local nutrient abundance is a novel finding in the work, which can be leveraged in future studies.

Weaknesses:<br /> The work has certain caveats, some of which have been already recognized by the authors. These include the use of steady-state metabolites and the possibility of cross-contamination of some TIF into the adjacent KIF. This study is also unable to distinguish the mechanisms driving the metabolic changes in KIF/TIF relative to circulating levels in plasma.

The relative similarity of KIF and TIF is quite surprising. However, this interpretation is presently based on a sampling of only ~100 polar metabolites and ~200 lipid molecules. It is, perhaps, possible that future technological developments that enable more comprehensive quantitative metabolic profiling might distinguish between KIF and TIF composition.

In vitro, tissue culture is recognized to suffer from 'non-physiological' nutrient dependencies, which are impacted by the composition of culture media. Thus, in vivo studies remain our current gold-standard in mechanistic studies of tumor metabolism. It is presently unclear whether the findings of this work will be recapitulated in any of the kidney cancer in vivo models and thus be functionally testable.

Reviewer #2 (Public Review):

The study employs quantitative metabolomic and lipidomic analyses to scrutinize tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples from renal cell carcinoma (RCC) patients. The authors delve into the intricate world of renal cell carcinoma and its tumor microenvironment, shedding light on the factors that shape nutrient availability in both cancerous and adjacent normal tissues. The authors prove that non-cancer-driven tissue factors play a dominant role in shaping nutrient availability in RCC. This finding opens up new avenues for research, suggesting that the tumor microenvironment is profoundly influenced by factors beyond the presence of cancer cells. This study not only contributes valuable insights into RCC metabolism but also prompts a reevaluation of the factors governing nutrient availability in tumor microenvironments more broadly. Overall, it represents a significant step forward in our understanding of the intricate interplay between cancer and its surrounding milieu.

The study is overall well-constructed, including appropriate analysis. Likewise, the manuscript is written clearly and supported by high-quality figures. Since the authors exclusively employed samples from RCC patients and did not include kidney interstitial fluid and plasma samples from healthy individuals, we cannot accurately assess the true significance and applicability of the results until the role of cancer cells in reshaping KIF is understood. In essence, some metabolite levels in the tumor interstitial fluid did not show an increase or decrease compared to the adjacent normal kidney interstitial fluid. However, the levels of these metabolites in both TIF and KIF might be higher or lower than those in kidney interstitial fluid from healthy individuals, and the roles of these metabolites should not be overlooked. Similar concerns extend to plasma levels, emphasizing the importance of metabolites that synchronously change in RCC TIF, KIF, and plasma-whether elevated or reduced.

Reviewer #3 (Public Review):

In this study, the authors utilized mass spectrometry-based quantification of polar metabolites and lipids in normal and cancerous tissue interstitial fluid and plasma. This showed that nutrient availability in tumor interstitial fluid was similar to that of interstitial fluid in adjacent normal kidney tissue, but that nutrients found in both interstitial fluid compartments were different from those found in plasma. This suggests that the nutrients in kidney tissue differ from those found in blood and that nutrients found in kidney tumors are largely dictated by factors shared with normal kidney tissue. Those data could be useful as a resource to support further study and modeling of the local environment of RCC and normal kidney physiology.

In Figures 1D and 1E, there were about 30% of polar metabolites and 25% of lipids significantly different between TIF and KIF, which could be key factors for RCC tumors. This reviewer considers that the authors should make comments on this.

Author Response

Reviewer #1 (Public Review):

The manuscript entitled 'Safb1 regulates cell fate determination in adult neural stem cells by enhancing Drosha cleavage of NFIB mRNA' by Iffländer et al, represents a solid piece of work addressing a non-canonical function of Drosha on NFIB mRNA processing via a newly identified Drosha partner, Safb1. The authors provide particularly systematic and convincing evidence on the biochemical interactions among the key players in this cascade. However, the significance of these interactions for NSC fate determination is not adequately supported by the data, hence, I have some remarks that would need to be addressed in order to clarify the impact of these events on NSC biology.

1) One of my main concerns is related to the nature of the DG NSCs used in all in vitro assays. The authors refer to their previous work on how these cells are isolated using a Hes5 mouse reporter line. However, both recent scRNAseq data (http://linnarssonlab.org/dentate/ from Hochgerner et al) and the authors' own immunostainings (Fig. 7A), clearly show that Hes5 does not label only adult NSCs in the DG, but also (if not primarily) astrocytes. Considering that the initial cultures could contain a high proportion of mature astrocytes, most of the major conclusions and hypotheses should be reformulated.

We thank the reviewer for their comment. We think that there is a misunderstanding about how the DG neural stem cells were isolated and cultured. In this manuscript we did not use the Hes5::GFP allele to isolate the stem cells. We isolated DG neural stem cells from C57Bl6 mice according to the protocol of Babu et al. (Babu et al. 2007 doi: 10.1371/journal.pone.0000388) and maintained and differentiated these according to our previous manuscripts (Ronaldo et al. 2016). This was not clear in the methods section of the original manuscript and, therefore, we have added the reference Babu et al. In order to address potential contamination with astrocytes, we have added images of the stem cells and their progeny immunostained with astrocytic markers (GFAP and S100b) in undifferentiated and differentiated states. These new data show that these neurogenic cells and their progeny do not express astrocytic markers until differentiation is induced.

2) Along these lines, Safb1 expression is quite widespread in the mouse DG (Fig. 7A) and does not display any specificity towards any type of progenitor cells compared to its expression in DGCs within the GCL. The authors should discuss this and integrate this expression information into their conclusions and interpretations, highlighting all pertinent limitations.

We appreciate and agree with the reviewer’s comment. SAFB1 is indeed broadly expressed by most if not all cells in the hippocampus. We quantified levels of SAFB1 expression across progenitors, astrocytes and neurons in the adult DG and in the SVZ, and show that SAFB1 levels differ across different neural stem cell populations and neural cells. We believe that our data show both in vitro and in vivo that the levels of SAFB1 are critical for determining the function of SAFB1 in regulating neural stem cell fate. We also showed that elevating SAFB1 levels in SVZ-derived neural stem cells suppresses their differentiation into oligodendrocytes, This we have made clearer in the text. However, how cells sense the levels of SAFB1 remains to be shown and it is difficult to speculate on the mechanism.

Reviewer #2 (Public Review):

In this manuscript, the authors uncover a variety of macromolecular Drosha complexes in NSCs and propose that they might exert specific functions in adult neurogenesis. This is an interesting and important area of research, the proteomics data are very useful, and the manuscript is well written and easy to understand. Overall, this manuscript has many strengths. The authors identify 165 proteins, several of them enriched in NSCs, and potentially specific for miRNA dependent or independent Drosha macromolecular complexes. Moreover, the authors convincingly show that Safb1 binds and post-transcriptionally destabilizes NFIB transcript in complex with Drosha, in vitro. With that said, most of the functional evidence are based on Safb1 overexpression in vitro, and in some cases with immortalized cell lines. This is a major limitation of the study. Further experiments should be done to convincingly demonstrate that Safb1 regulates cell fate determination in adult neural stem cells by enhancing Drosha cleavage of NFIB mRNA.

Reviewer #1 (Public Review):

The manuscript entitled 'Safb1 regulates cell fate determination in adult neural stem cells by enhancing Drosha cleavage of NFIB mRNA' by Iffländer et al, represents a solid piece of work addressing a non-canonical function of Drosha on NFIB mRNA processing via a newly identified Drosha partner, Safb1. The authors provide particularly systematic and convincing evidence on the biochemical interactions among the key players in this cascade. However, the significance of these interactions for NSC fate determination is not adequately supported by the data, hence, I have some remarks that would need to be addressed in order to clarify the impact of these events on NSC biology.

1. One of my main concerns is related to the nature of the DG NSCs used in all in vitro assays. The authors refer to their previous work on how these cells are isolated using a Hes5 mouse reporter line. However, both recent scRNAseq data (http://linnarssonlab.org/dentate/ from Hochgerner et al) and the authors' own immunostainings (Fig. 7A), clearly show that Hes5 does not label only adult NSCs in the DG, but also (if not primarily) astrocytes. Considering that the initial cultures could contain a high proportion of mature astrocytes, most of the major conclusions and hypotheses should be reformulated.

2. Along these lines, Safb1 expression is quite widespread in the mouse DG (Fig. 7A) and does not display any specificity towards any type of progenitor cells compared to its expression in DGCs within the GCL. The authors should discuss this and integrate this expression information into their conclusions and interpretations, highlighting all pertinent limitations.

eLife assessment

This manuscript addresses a non-canonical function of the Class 2 ribonuclease III Drosha in the regulation of adult neural stem cell fate, important for understanding how these cells generate neurons or oligodendrocytic cells.<br /> Overall, this manuscript has many strengths. The authors identify 165 proteins, several of them enriched in neural stem cells, and potentially specific for miRNA dependent or independent Drosha macromolecular complexes.<br /> While the authors provide systematic and convincing evidence on the biochemical interactions among the key players in this cascade, the significance of these interactions for neural stem cell fate determination in vivo remains unclear, as the in vitro cellular systems used to document most of the data reported in the paper may not (fully) represent resident neural stem cells in the adult hippocampus. The in vivo function mediated by Drosha/ Safb1 needs to be substantiated by more evidence and/or complementary approaches.

Author Response

Reviewer #1 (Public Review):

In this analysis derived from the BLADE study, a Phase IV investigation using the LHRH antagonist Degarelix, the authors revealed additional insights into the relationship between FSH and body composition.

The primary strength of the study lies in its prospective nature and the utilization of human subjects.

We thank the reviewer for the positive evaluation.

However, some weaknesses exist in the study.

First, the authors presented results from a simple correlation study without accounting for potential confounding factors in fat metabolism. Particularly, readers may be intrigued to understand how testosterone or estradiol interact with FSH in relation to fat mass.

As for the evaluation of circulating levels of testosterone and estradiol, unfortunately the protocol did not include the dosage for these hormones. The evaluation of testosterone, in particular, would have required mass photometry as the values of testosterone during therapy with degarelix are reduced below the sensitivity of the methods used in clinical practice. Therefore, the correlation/association analysis between testosterone and body composition would not have been reliable and would not have been useful for the study. All patients were considered to have hypogonadism due to the significant decrease in PSA values and the limited testosterone data available.

The inverse relationship between ALBI/FBM was previously documented in a paper by the same group (Palumbo et al, Prostate Cancer Prostatic Dis 2021). In that earlier publication, the authors reported no correlation between FSH and lean mass or ALBI, suggesting the significance of the correlation between FSH and ALBI/FBM arising from changes in fat body mass-a factor somehow not included in the prior paper, not necessarily from sarcopenia.

The referee is correct, as there is no correlation between lean mass and FSH, nor between lean mass variations and FSH variations. The correlation between ALMI/FBM and FSH is mostly due to the effect on fat mass. The text now includes a statement that emphasizes this concept (see Discussion page 8, lines 19-22).

Reviewer #2 (Public Review):

This manuscript reports the results of an ancillary study of a prospective trial assessing the effects of androgen deprivation therapy (ADT) with Dagarelix (a GnRH antagonist) on body composition in patients with prostate cancer. An interesting relationship between FSH levels, that were suppressed by Dagarelix treatment, and body composition parameters (particularly fat body mass) was described after 12 months of therapy. Therefore, the authors conclude that FSH could be a promising marker to monitor the risk of sarcopenic obesity and cardiovascular complications in prostate cancer patients undergoing ADT. As acknowledged by the Authors the main limitation of the study is the limited sample of patients. However, since testosterone levels were not assessed it is not possible to firmly establish whether the changes in fat mass observed with treatment are directly or indirectly associated with a reduction in FSH (and therefore in the latter case mediated by testosterone). Moreover, it is not clear whether the effect of the change in FSH levels during the study and the body composition parameters achieved at 12 months was evaluated (instead of assessing the relationship between FSH changes and changes in body composition parameters). Finally, tests on bone muscle mass and strength were not performed, so the hypothesis that variation of FSH levels in prostate cancer patients in ADT may affect sarcopenia remains speculative.

We appreciate the reviewer's positive assessment of our manuscript. We evaluated the correlation between FSH changes and body composition values after 12 months of Degarelix, as requested by the reviewer. No significant correlation was observed, see the attached table. Therefore we have decided not to insert this last statistical analysis in the revised paper.

eLife assessment

The authors observed a positive correlation between FSH and fat mass, as well as a negative association with the appendicular lean mass/fat mass ratio. These valuable findings in male subjects within a hypogonadal setting following Degarelix treatment imply that FSH might function as a predictor, similar to observations in women. However, it's important to note that the analysis is incomplete, as other major confounding factors such as testosterone were not included.

Reviewer #1 (Public Review):

In this analysis derived from the BLADE study, a Phase IV investigation using the LHRH antagonist Degarelix, the authors revealed additional insights into the relationship between FSH and body composition.

The primary strength of the study lies in its prospective nature and the utilization of human subjects

However, some weaknesses exist in the study.

First, the authors presented results from a simple correlation study without accounting for potential confounding factors in fat metabolism. Particularly, readers may be intrigued to understand how testosterone or estradiol interact with FSH in relation to fat mass.

The inverse relationship between ALBI/FBM was previously documented in a paper by the same group (Palumbo et al, Prostate Cancer Prostatic Dis 2021). In that earlier publication, the authors reported no correlation between FSH and lean mass or ALBI, suggesting the significance of the correlation between FSH and ALBI/FBM arising from changes in fat body mass-a factor somehow not included in the prior paper, not necessarily from sarcopenia.

Reviewer #2 (Public Review):

This manuscript reports the results of an ancillary study of a prospective trial assessing the effects of androgen deprivation therapy (ADT) with Dagarelix (a GnRH antagonist) on body composition in patients with prostate cancer. An interesting relationship between FSH levels, that were suppressed by Dagarelix treatment, and body composition parameters (particularly fat body mass) was described after 12 months of therapy. Therefore, the authors conclude that FSH could be a promising marker to monitor the risk of sarcopenic obesity and cardiovascular complications in prostate cancer patients undergoing ADT. As acknowledged by the Authors the main limitation of the study is the limited sample of patients. However, since testosterone levels were not assessed it is not possible to firmly establish whether the changes in fat mass observed with treatment are directly or indirectly associated with a reduction in FSH (and therefore in the latter case mediated by testosterone). Moreover, it is not clear whether the effect of the change in FSH levels during the study and the body composition parameters achieved at 12 months was evaluated (instead of assessing the relationship between FSH changes and changes in body composition parameters). Finally, tests on bone muscle mass and strength were not performed, so the hypothesis that variation of FSH levels in prostate cancer patients in ADT may affect sarcopenia remains speculative.

Author Response

Reviewer #1 (Public Review):

Using a HFD mouse model, the authors examined the H3K4me3 mark in sperm and placental tissues followed by correlation to the transcriptomic changes in the placental tissues of the male and female offspring. The hypothesis that the authors tried to test was that sperm histone epimutations affect placental function, thereby leading to metabolic disorders in offspring. The strength of this work includes the interesting idea and the initial data generated. However, the entire study remains purely correlative without any validation experiment to support the correlation. The conclusion needs to be further supported by bigger sample size and more functional analyses demonstrating the causal relationship among the histone epimutations detected, the dysregulated mRNA expression in the placenta, and the phenotypes in offspring.

Functional data: We appreciate that we should have emphasized and written more clearly that we had indeed phenotyped the placentas and offspring metabolic health from the same model we derived the placenta tissue from as we reported in (Jazwiec et al., 2022)(PMID: 35377412). This was referenced in our submitted manuscript (Lines 105-107; 131-133; 135-139; 147-150; 232-235; 270-273; 297-300; 384-386; 433-435; 441-448; 507-514). We have made this more apparent in the manuscript by expanding our description of the offspring phenotypes in the introduction and clarified that it was from this model that the placenta’s used in this study were derived from (Jazwiec et al., 2022) (PMID: 35377412).

Regarding effect and sample size: It appears that on review the animal numbers used for the ChIP-seq were confused with the number of replicates by the reviewers. These details were in Supplementary file 1a. There were 3 replicates per experimental group and each replicate contained sperm from pooled samples that was equalized in cell number and comprised of sperm from n=7 control males, or n=16 HFD males. For the RNA-seq n=4 placentas were used from each experimental group from both males and females for a total N of 16. Although the sample size is moderate, we followed the Canadian Council of Animal Care guideline which calls for the use of the lowest animal number that elicits significant effects (CCAC guidelines p6 “Consideration must also be given to reduction, to determine the fewest number of animals appropriate to provide valid information and statistical power, while still minimizing the welfare impact for each animal”).

Validation: We used a high standard of computational validation and visualization strategies, to ensure confidence in genomic data. This also allowed for a comprehensive understanding of the biological and physiological impacts of paternal obesity on the sperm epigenome and placenta transcriptome. In our experimental design we also included biological and technical replicates. Together these methods provide robustness checks of the experimental data and support our conclusions. These are the validation strategies we used:

Technical and experimental validation

• We evaluated the quality of sequencing data using metrics of read quality, alignment and coverage. These are summarized in Supplementary file 1a.

• Visualized and performed statistical analysis of data to check for anomalies and discrepancies, Pearson correlation analysis shown on heatmap to look for variance and patterns in samples- all here highly correlated (Figure 2 – Figure supplement 1 B and Figure 4 – Figure supplement 1 A). We checked for batch effects and normalized the data (Figure 4 – Figure supplement 1 B) we used PCA plot analysis as a second check for sample behaving oddly (Figure 2 – Figure supplement 1 C and Figure 4 – Figure supplement 1 C).

• We used a deconvolution approach to improve the biological meaning of our bulk RNA-seq data (Figure 6, Figure 5 – Figure supplement 1 and 2).

• Performed functional enrichment analysis to gain insight into biological functions, pathways, and genome ontology and visualized individual regions identified to be altered as a confirmation (Figure 2 D and 2 E; Figure 4 E and F; Figure 6, Figure 2 – Figure supplement 1 E; Figure 3 – Figure supplement 1). Comparison to external data sets:

• We compared our data with external data sets using the same tissues and cell and to our prior studies: a) We compared ChIP-seq data from this obesity model with our former obesity ChIP-seq data (Figure 2 – Figure supplement 1); b) re-analyzed and compared placenta RNA-seq data from an in utero exposure hypoxia model that shared similar offspring and placenta phenotypes as we observed in the obesity model (Figure 6 and Figure 6 – Figure supplement 1).

• We used a deconvolution approach to improve the biological meaning of our bulk RNA-seq data (Figure 6, Figure 5 – Figure supplement 1 and 2). Statistical Significance and False Discovery Rate (FDR):

• We applied statistical tests and multiple testing corrections to reduce the likelihood of false positives (See also response 1 for additional testing added to the revised manuscript)

Causation versus correlation: We agree that the relationship between the sperm epigenome and placenta transcriptome is correlative, however this is the current state of the field for studies of paternal epigenetic transmission of environmental information. To take this study to the point where causation can be implied would require the generation of a sperm epigenome edited mouse model where we target genes implicated in placental function. Indeed, this targeting approach is well underway in our research program.

Reviewer #2 (Public Review):

This study follows up on previous work from this group, and others, relating paternal diet to changes in sperm epigenetics, and offspring phenotypes. The authors focus on paternal diet (high-fat diet versus a control chow), sperm chromatin, and molecular changes in the placenta associated with offspring development.

The text is well written and the figures are generally well presented and clear. The sperm epigenetic analyses and analysis of the placenta epigenetics and gene expression are generally well performed. The study provides new insight into how paternally mediated intergenerational epigenetic inheritance could involve placenta-embryo signaling.

A major weakness is that the high-fat diet used was from a different manufacturer than the control (lower fat) diet. Therefore, it is difficult to judge whether the effects are due to a change in fat levels, or the many other molecules that are likely to differ in chow between different manufacturers. Other weaknesses include lack of methodological detail in parts, low n values for some experiments, and the need for more mechanistic data.

Diets: It is worth reminding that we are studying the effects of obesity and not diet. Indeed, HFD induces metabolic dysfunction while the control does not. Although it is fair to point out that the composition of the control diet should be kept in mind, considering the desired outcomes within the scope of the study, the diets elicited the desired phenotypic effects serving as a model for obesity. We see this experimental design as a strength, as in this study we compared this model to our previous published obesity model (Pepin, Lafleur, Lambrot, Dumeaux, & Kimmins, 2022) (PMID: 35183795), and there was significant overlap in the regions of differential enrichment detected between both models even though they were conducted in different research settings, with different mouse substrain and different diet combinations. In our opinion this demonstrates that we are measuring robust effects of paternal obesity that can be replicated under different conditions. This comparative study design has been lacking in the field of epigenetic inheritance.

Animal numbers and replicates: It appears that on review the animal numbers used for the ChIP-seq were confused with the number of replicates by the reviewers. These details were in Supplementary file 1a. There were 3 replicates per experimental group and each replicate contained sperm from pooled samples that was equalized in cell number and comprised of sperm from n=7 control males, or n=16 HFD males. For the RNA-seq n=4 placentas were used from each experimental group from both males and females for a total N of 16. Although the sample size is moderate, we followed the Canadian Council of Animal Care guideline which calls for the use of the lowest animal number that elicits significant effects (CCAC guidelines p6 “Consideration must also be given to reduction, to determine the fewest number of animals appropriate to provide valid information and statistical power, while still minimizing the welfare impact for each animal”).

Whilst the authors may have achieved their aims, more data is needed to inform a potential mechanism.

It is difficult in studies on paternal epigenetic inheritance to attribute a mechanism and we agree that the relationship between the obesity altered sperm epigenome and the placenta abnormalities are correlative. However, the novelty in our study is that we postulate a new mechanism for paternal transmission of metabolic disease that implicates the placenta and demonstrate this via an altered placenta transcriptome and placenta developmental abnormalities described here and in our previous paper on this model ((Jazwiec et al., 2022); PMID: 35377412). The next steps for the field to address causation/mechanism requires generation of a sperm epigenome edited mouse model where we induce and track histone methylation changes at specific genes to the tissues in the next generation. Indeed, this targeting approach is underway in our research program.

Reviewer #3 (Public Review):

This study represents a useful addition to the authors' previous study examining the effects of paternal high-fat diet on offspring metabolism and gene expression in offspring (PMID: 35183795). It differs from the previous study in some of the details of the experimental model (age of sire when exposed to the diet manipulation, mouse substrain, and the nature of the control diet) and the results are largely in line with previous findings. The major finding is that many genes at which sperm H3K4me3 signal is altered also have altered expression in the placenta; some of these genes are paternally imprinted, providing a paternal-specific epigenetic signature. Strengths of the study include establishment of an important dataset correlating the sperm epigenome with gene expression in placental tissue, leading to an interesting and provocative conclusion. Weaknesses include a relatively superficial analysis of the dataset, revealing broad patterns but few specific conclusions, reliance on correlative analysis to draw conclusions, and absence of validation studies. Deconvolution analysis of bulk RNA-seq data helps to account for differences in cell composition between placental datasets, but does not add additional insight toward the central question of how sperm epigenetic state contributes to offspring gene expression. Overall the advance over previous work is relatively small.

Specific points:

1) The analysis as it stands is limited. To compare sperm H3K4me3 and placental expression, numbers of overlapping genes are provided, but no statistical analysis is done to indicate the significance of the overlap.

Fisher’s exact test to overlap paternal obesity-associated differentially enriched regions of H3K4me3 deH3K4me3) with female and male placenta differentially enriched genes (Figure 4 – Figure supplement 1 Di and ii).

2) There is little direct connection to biological systems or validation of differential enrichment/expression analysis. Gene ontology enrichments for genes differentially enriched for H3K4me3 in sperm or differentially expressed in placenta (broken up by sex) are performed, but the biological significance of these categories is not clear.

We used a high standard of computational validation and visualization strategies, to ensure confidence in genomic data. This also allowed for a comprehensive understanding of the biological and physiological impacts of paternal obesity on the sperm epigenome and placenta transcriptome. In our experimental design we also included biological and technical replicates. Together these methods provide robustness checks of the experimental data and support our conclusions. The validation strategies we used are detailed in response 17.

We revised the text to expand discussion on the observed enriched gene ontology terms, as well as the biological significance and functions of the genes we refer to in this section:

Lines 222-227: “The placenta is a rich source of hormone production, is highly vascularized, and secretes neurotransmitters (Hemberger, Hanna, & Dean, 2020; Rosenfeld, 2021). Disruption in these functions is suggested in the significantly enriched pathways that included genes involved in the transport of cholesterol, angiogenesis, and neurogenesis (Figure 4 C-D, Supplementary file 1e-f). Other significantly enriched processes included genes implicated in nutrient and vitamin transport (Figure 4 C-D).”

Lines 441-463:“Many of the DEGs in the paternal obese-sired placentas were involved in the regulation of the heart and brain. This is in line with paternal obesity associated to the developmental origins of neurological, cardiovascular, and metabolic disease in offspring (Andescavage & Limperopoulos, 2021; Binder, Beard, et al., 2015; Binder et al., 2012; Chambers et al., 2016; Cropley et al., 2016; de Castro Barbosa et al., 2016b; T. Fullston et al., 2012; Tod Fullston et al., 2013; Grandjean et al., 2015; Huypens et al., 2016; Jazwiec et al., 2022; Mitchell, Bakos, & Lane, 2011; Ng et al., 2010; Pepin et al., 2022; Perez-Garcia et al., 2018; Terashima et al., 2015; Thornburg et al., 2016; Thornburg & Marshall, 2015; Ueda et al., 2022; Wei et al., 2014). The brain-placenta and heart-placenta axes refer to their developmental linkage to the trophoblast which produces various hormones, neurotransmitters, and growth factors that are central to brain and heart development (Parrettini, Caroli, & Torlone, 2020; Rosenfeld, 2021). This is further illustrated in studies where placental pathology is linked to cardiovascular and heart abnormalities (Andescavage & Limperopoulos, 2021; Thornburg et al., 2016; Thornburg & Marshall, 2015). For example, in a study of the relationship between placental pathology and neurodevelopment of infants, possible hypoxic conditions were a significant predictor of lower Mullen Scales of Early Learning (Ueda et al., 2022). A connecting factor between the neural and cardiovascular phenotypes is the neural crest cells which make a critical contribution to the developing heart and brain (Hemberger et al., 2020; Perez-Garcia et al., 2018). Notably, neural crest cells are of ectodermal origin which arises from the TE (Prasad, Charney, & García-Castro, 2019), which is in turn governed by paternally-driven gene expression. It is worth considering the routes by which TE dysfunction may be implicated in the paternal origins of metabolic and cardiovascular disease. First, altered placenta gene expression beginning in the TE could influence the specification of neural crest cells which are a developmental adjacent cell lineage in the early embryo. TE signaling to neural crest cells could alter their downstream function. Second, altered trophoblast endocrine function will influence cardiac and neurodevelopment (Hemberger et al., 2020).”

3) The overall effect size is small. In most cases the magnitude of differences is minor, and it is not clear which of these changes are significant over noise. For example, the y-axis for the metagene plots in Figure 2B does not start at zero, so the total range of the difference in H3K4me3 is small. In Figure 6C, DEGs detected in hypoxic placenta after deconvolution analysis do not look very different compared to control.

Thank-you for pointing out that the scales were different in Figure 2 Bi and ii. They have been revised to show the same Y axis scale beginning at zero for comparison of regions that gained and lost H3K4me3 making the differences in H3K4me3 more readily visible. The heatmap shown in Figure 6 C visualizes the DEGs in hypoxic vs control placenta where 1477 DEGS were identified in our re-analysis using a convolution approach applied to the bulk-seq data set from Chu et al., 2019. We do not share the view that they are not well visualized in the heat map.

4) Deconvolution analysis was done on bulk RNA-seq data from placenta, and the numbers of DEGs identified with this analysis compared to the original analysis are shown, but is not clear how the deconvolution analysis changes the specific biological conclusions. In addition, the reference dataset for deconvolution is a published dataset generated in another lab, and it is unclear how comparable the reference sample is to the samples analyzed in this study, or how robust this analysis is when using a dataset generated under different conditions.

The deconvolution analysis allows to infer cellular composition within a tissue and suggests that there are changes in cell-type proportion that could change placenta function and improves the detection of differentially expressed genes (Aliee & Theis, 2021; Campbell et al., 2023; Kuhn, Thu, Waldvogel, Faull, & Luthi-Carter, 2011) (PMID: 34293324; 36914823; 21983921).

As per the published dataset used as a reference sample for the deconvolution analysis, it was ideal -we specifically chose this dataset for this analysis as the tissue of origin matched for the same mouse strain and developmental type points as our samples and those used in the Chu et al., 2019 analysis. We used the Chu et al., 2019 data set for comparative validation, and to further explore whether the biological effects of paternal obesity were like those of a hypoxic placenta. We have revised the text to more clearly show the biological relevance and interpretation of this analysis (see author response 12)

We revised the text to clarify the biological implications of this analysis:

Lines 282-290: “This reduction in the number of detected DEGs before versus after accounting for cellular composition suggests that changes in cell-type proportions at least partly drive tissue-level differential expression. This is consistent with the recent finding that preeclampsia-associated cellular heterogeneity in human placentas mediates previously detected bulk gene expression differences (Campbell et al., 2023). There were similarities between the bulk RNA-seq and deconvoluted analysis in that there was overlap of DEGs detected before and after adjusting for cell-type proportions (Figure 5 – Figure supplement 3 G and H, Fisher’s exact test P=1.8e-105 and P=0e+00, respectively). This differential gene expression analysis accounting for cellular composition provides insight into how paternal obesity may impact placental development and function and underscores the contribution of cellular heterogeneity in this process.”

Reviewer #4 (Public Review):

The members of the Kimmins lab perform a dietary study in mice to investigate the impact of obesity of fathers on the development of their offspring. To do so, they expose male mice to a high fat diet and determine the distribution and occupancy levels of the histone H3 lysine 4 trimethylation (H3K4me3) mark in spermatozoa and perform gene expression studies on placenta tissue obtained from mouse embryos during mid-gestation development. The authors report changes in H3K4me3 occupancy in sperm as well as in transcriptomes of placentas of male and female embryonic offspring. While the authors perform extensive computational analysis of the transcriptomic and chromatin immunoprecipitation data, the authors do not go much beyond making correlative statements at mainly the genome wide level between changes for H3K4me3 in sperm and transcriptional changes in placenta, the latter of which are in part related to changes in cellular composition (as deduced from transcriptional data). Given that both parental mice had the same genetic background, it was not possible to deduce parental specific contributions to transcriptional changes as observed in placentas of offspring. In all, the study falls short in increasing mechanistic insights into this important biological phenomenon.

It is difficult in studies on paternal epigenetic inheritance to attribute a mechanism and we agree that the relationship between the obesity altered sperm epigenome and the placenta abnormalities are correlative. However, the novelty in our study is that we postulate a new mechanism for paternal transmission of metabolic disease that implicates the placenta and demonstrate this via an altered placenta transcriptome and placenta developmental abnormalities described here and in our previous paper on this model ((Jazwiec et al., 2022); PMID: 35377412). The next steps for the field to address causation/mechanism requires generation of a sperm epigenome edited mouse model where we induce and track histone methylation changes at specific genes to the tissues in the next generation. Indeed, this targeting approach is underway in our research program.

eLife assessment

This important study presents data suggesting that HFD-induced histone epimutations in sperm may impact the transcriptome of the placenta, thereby contributing to the paternal transmission of paternal metabolic disorders to offspring. Although the hypothesis is interesting and the evidence presented is compelling, more careful statistical analyses and functional validation experiments are needed to further strengthen the conclusion.

Reviewer #1 (Public Review):

Using a HFD mouse model, the authors examined the H3K4me3 mark in sperm and placental tissues followed by correlation to the transcriptomic changes in the placental tissues of the male and female offspring. The hypothesis that the authors tried to test was that sperm histone epimutations affect placental function, thereby leading to metabolic disorders in offspring. The strength of this work includes the interesting idea and the initial data generated. However, the entire study remains purely correlative without any validation experiment to support the correlation. The conclusion needs to be further supported by bigger sample size and more functional analyses demonstrating the causal relationship among the histone epimutations detected, the dysregulated mRNA expression in the placenta, and the phenotypes in offspring.

Reviewer #2 (Public Review):

This study follows up on previous work from this group, and others, relating paternal diet to changes in sperm epigenetics, and offspring phenotypes. The authors focus on paternal diet (high-fat diet versus a control chow), sperm chromatin, and molecular changes in the placenta associated with offspring development.

The text is well written and the figures are generally well presented and clear. The sperm epigenetic analyses and analysis of the placenta epigenetics and gene expression are generally well performed. The study provides new insight into how paternally mediated intergenerational epigenetic inheritance could involve placenta-embryo signaling.

A major weakness is that the high-fat diet used was from a different manufacturer than the control (lower fat) diet. Therefore, it is difficult to judge whether the effects are due to a change in fat levels, or the many other molecules that are likely to differ in chow between different manufacturers. Other weaknesses include lack of methodological detail in parts, low n values for some experiments, and the need for more mechanistic data.

Whilst the authors may have achieved their aims, more data is needed to inform a potential mechanism.

This study adds to our understanding of how changes in paternal diet may alter sperm epigenetics and offspring development. The novelty is in the link to gene expression in the placenta associated with offspring development in utero.

Reviewer #3 (Public Review):

This study represents a useful addition to the authors' previous study examining the effects of paternal high-fat diet on offspring metabolism and gene expression in offspring (PMID: 35183795). It differs from the previous study in some of the details of the experimental model (age of sire when exposed to the diet manipulation, mouse substrain, and the nature of the control diet) and the results are largely in line with previous findings. The major finding is that many genes at which sperm H3K4me3 signal is altered also have altered expression in the placenta; some of these genes are paternally imprinted, providing a paternal-specific epigenetic signature. Strengths of the study include establishment of an important dataset correlating the sperm epigenome with gene expression in placental tissue, leading to an interesting and provocative conclusion. Weaknesses include a relatively superficial analysis of the dataset, revealing broad patterns but few specific conclusions, reliance on correlative analysis to draw conclusions, and absence of validation studies. Deconvolution analysis of bulk RNA-seq data helps to account for differences in cell composition between placental datasets, but does not add additional insight toward the central question of how sperm epigenetic state contributes to offspring gene expression. Overall the advance over previous work is relatively small.

Specific points:

1) The analysis as it stands is limited. To compare sperm H3K4me3 and placental expression, numbers of overlapping genes are provided, but no statistical analysis is done to indicate the significance of the overlap.

2) There is little direct connection to biological systems or validation of differential enrichment/expression analysis. Gene ontology enrichments for genes differentially enriched for H3K4me3 in sperm or differentially expressed in placenta (broken up by sex) are performed, but the biological significance of these categories is not clear.

3) The overall effect size is small. In most cases the magnitude of differences is minor, and it is not clear which of these changes are significant over noise. For example, the y-axis for the metagene plots in Figure 2B does not start at zero, so the total range of the difference in H3K4me3 is small. In Figure 6C, DEGs detected in hypoxic placenta after deconvolution analysis do not look very different compared to control.

4) Deconvolution analysis was done on bulk RNA-seq data from placenta, and the numbers of DEGs identified with this analysis compared to the original analysis are shown, but is not clear how the deconvolution analysis changes the specific biological conclusions. In addition, the reference dataset for deconvolution is a published dataset generated in another lab, and it is unclear how comparable the reference sample is to the samples analyzed in this study, or how robust this analysis is when using a dataset generated under different conditions.

Reviewer #4 (Public Review):

The members of the Kimmins lab perform a dietary study in mice to investigate the impact of obesity of fathers on the development of their offspring. To do so, they expose male mice to a high fat diet and determine the distribution and occupancy levels of the histone H3 lysine 4 trimethylation (H3K4me3) mark in spermatozoa and perform gene expression studies on placenta tissue obtained from mouse embryos during mid-gestation development. The authors report changes in H3K4me3 occupancy in sperm as well as in transcriptomes of placentas of male and female embryonic offspring. While the authors perform extensive computational analysis of the transcriptomic and chromatin immunoprecipitation data, the authors do not go much beyond making correlative statements at mainly the genome wide level between changes for H3K4me3 in sperm and transcriptional changes in placenta, the latter of which are in part related to changes in cellular composition (as deduced from transcriptional data). Given that both parental mice had the same genetic background, it was not possible to deduce parental specific contributions to transcriptional changes as observed in placentas of offspring. In all, the study falls short in increasing mechanistic insights into this important biological phenomenon.

eLife assessment

This study is useful as it provides further analysis of previously published data to address which specific genes are part of the masculinizing actions of E2 on female zebra finches, and where these key genes are expressed in the brain. However the data supporting the conclusion of masculinizing the song system are incomplete as the current manuscript is a re-analysis of differential gene expression modulated by E2 treatment between male/female zebra finches without manipulation of gene expression. The conclusions (and title) regarding song learning are not completely supported, with no gene manipulation or song analysis. The use of WGCNA for a question of sex-chromosome expression in species without dosage compensation is considered inadequate. As the experimental design did not include groups to directly test for song learning, and there was also no analysis of song performance, these data were also considered inadequate in that regard.

Author Response

The following is the authors’ response to the previous reviews.

We appreciate the constructive comments made by the editor and the reviewers. We have corrected errors and provided additional experimental data and analysis to address the latest criticisms raised by the reviewers and provided point-by-point response to the reviewers as below.

Reviewer #1 (Recommendations For The Authors):

I do acknowledge the work the authors put into this manuscript and I can accept the fact that the authors decided on a minimum of additional experiments. However, I would recommend the authors to be more concise by adding more information in the method and result sections about how they performed their experiments such as which Nav and AMPAR DNA constructs they used, the age of the mice, how long time they exposed the patches to quinidine, information on how many times they repeated their pull downs etc.

Answer: We thank the reviewer’s comments. we have incorporated the suggested modifications into our revised manuscript. Specifically, we have included detailed information on the NaV and AMPAR constructs in the Methods section. The age of the homozygous NaV1.6 knockout mice and the wild-type littermate controls is postnatal (P0-P1) (see in Results and Methods section). Prior to the application of step pulses, cells were subjected to the bath solution containing quinidine for approximately one minute (see in Methods section). Additionally, the co-immunoprecipitation assays for Slack and NaV1.6 were repeated three times (see in Methods section).

Minor detail in line 263: "...KCNT1 (Slack) have been identified to related to seizure..." I guess this should have been "...KCNT1 (Slack) have been identified and related to seizure..."?

Answer: We thank the reviewer for raising this point. We have corrected it in the revised manuscript.

Also, and again minor detail, I had a comment about the color coding in Fig 4 and by mistake, I added 4B, but I meant the use of colors in the entire figure, and mainly the use of colors in 4C, G and I.

Answer: We apologize for the confusion. We have changed the color coding of Figure 4 in the revised manuscript.

Reviewer #2 (Recommendations For The Authors):

While the paper is improved, several concerns do not seem to have been addressed. Some may have been missed because there is no response at all, but others may have been unclear because the response does not address the concern, but a related issue. Details are below.

Answer: We thank the reviewer for the criticisms. We have made changes of our manuscript to address the concerns.

Original issue:

3) Remove the term in vivo.

Answer: We thank the reviewer for raising this point. In our experiments, although we did not conduct experiments directly in living organisms, our results demonstrated the coimmunoprecipitation of NaV1.6 with Slack in homogenates from mouse cortical and hippocampal tissues (Fig. 3C). This result may support that the interaction between Slack and NaV1.6 occurs in vivo.

New comment from reviewer:

The argument to use the term in vivo is not well supported by what the authors have said. Just because tissues are used from an animal does not mean experiments were conducted in vivo. As the authors say, they did not conduct experiments in living organisms. Therefore the term in vivo should be avoided. This is a minor point.

Answer: We thank the reviewer for pointing this out. We have removed the term “in vivo” in the revised manuscript.

Original:

4) Figure 1C Why does Nav1.2 have a small inward current before the large inward current in the inset?

Answer: We apologize for the confusion. We would like to clarify that the small inward current can be attributed to the current of membrane capacitance (slow capacitance or C-slow). The larger inward current is mediated by NaV1.2.

New comment:

This is not well argued. Please note why the authors know the current is due to capacitance. Also, how do they know the larger current is due to NaV1.2? Please add that to the paper so readers know too.

Answer: We thank the reviewer’s comment. To provide a clearer representation of NaV1.2mediated currents in Fig. 1C, we have replaced the original example trace with a new one in which only one inward current is observed.

Original:

The slope of the rising phase of the larger sodium current seems greater than Nav1.6 or Nav1.5. Was this examined?

Answer: Additionally, we did not compare the slope of the rising phase of NaV subtypes sodium currents but primarily focused on the current amplitudes.

New comment:

This is not a strong answer. There seems to be an effect that the authors do not mention and evidently did not quantify that argues against their conclusion, which weakens the presentation.

Answer: We thank the reviewer’s comment. To assess the slope of the rising phase of NaV subtype currents, we compared the activation time constants of NaV1.2, NaV1.5, and NaV1.6 peak currents in HEK293 cells co-expressing NaV channel subtypes with Slack. The results have shown no significant differences (Author response image 1). We have included this analysis (see Fig. S9A) and the corresponding fitting equation (see in Methods section) in the revised manuscript.

Author response image 1.

The activation time constants of peak sodium currents in HEK293 cells co-expressing NaV1.2 (n=6), NaV1.5 (n=5), and NaV1.6 (n=5) with Slack, respectively. ns, p > 0.05, one-way ANOVA followed by Bonferroni’s post hoc test.

Original:

2D-E For Nav1.5 the sodium current is very large compared to Nav1.6. Is it possible the greater effect of quinidine for Nav1.6 is due to the lesser sodium current of Nav1.6?

Answer: We thank the reviewer for raising this point. We would like to clarify that our results indicate that transient sodium currents contribute to the sensitization of Slack to quinidine blockade (Fig. 2C,E). Therefore, it is unlikely that the greater effect observed for NaV1.6 in sensitizing Slack is due to its lower sodium currents.

New comment:

I am not sure the question I was asking was clear. How can the authors discount the possibility that quinidine is more effective on NaV1.6 because the NaV1.6 current is relatively weak?

Answer: We thank the reviewer for raising this point. We have examined the sodium current amplitudes of NaV1.5, NaV1.5/1.6 chimeras, and NaV1.6 upon co-expression of NaV with Slack. Our analysis revealed that there are no significant differences between NaV1.5 and NaV1.5/6N, with both exhibiting much larger current amplitudes compared to NaV1.6 (Author response image 2), but only NaV1.5/6N replicates the effect of NaV1.6 in sensitizing Slack to quinidine blockade (Fig. 4H-I), suggesting the observed differences between NaV1.5 and NaV1.6 in sensitizing Slack are unlikely to be attributed to NaV1.6's lower sodium currents but may instead involve NaV1.6's Nterminus-induced physical interaction. We have included this analysis in the revised manuscript (see Fig. S9B).

Author response image 2.

Comparison of peak sodium current amplitudes of NaV1.5 (n=9), NaV1.5/6NC (n=13), NaV1.5/6N (n=10), and NaV1.6 (n=8) upon co-expressed with Slack in HEK293 cells. ns, p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001; one-way ANOVA followed by Bonferroni’s post hoc test.

Original:

The differences between WT and KO in G -H are hard to appreciate. Could quantification be shown? The text uses words like "block" but this is not clear from the figure. It seems that the replacement of Na+ with Li+ did not block the outward current or effect of quinidine.

Answer: We apologize for the confusion. We would like to clarify the methods used in this experiment. The lithium ion (Li+) is a much weaker activator of sodium-activated potassium channel Slack than sodium ion (Na+)1,2.

1. Zhang Z, Rosenhouse-Dantsker A, Tang QY, Noskov S, Logothetis DE. The RCK2 domain uses a coordination site present in Kir channels to confer sodium sensitivity to Slo2.2 channels. J Neurosci. Jun 2 2010;30(22):7554-62. doi:10.1523/JNEUROSCI.0525-10.2010

2. Kaczmarek LK. Slack, Slick and Sodium-Activated Potassium Channels. ISRN Neurosci. Apr 18 2013;2013(2013)doi:10.1155/2013/354262 Therefore, we replaced Na+ with Li+ in the bath solution to measure the current amplitudes of sodium-activated potassium currents (IKNa)3.

3. Budelli G, Hage TA, Wei A, et al. Na+-activated K+ channels express a large delayed outward current in neurons during normal physiology. Nat Neurosci. Jun 2009;12(6):745-50. doi:10.1038/nn.2313

The following equation was used for quantification:

Furthermore, the remaining IKNa after application of 3 μM quinidine in the bath solution was measured as the following:

The quantification results were presented in Fig. 1K. The term "block" used in the text referred to the inhibitory effect of quinidine on IKNa.

New comment:

The fact remains that the term "block" is too strong for an effect that is incomplete. Also, the authors should add to the paper that Li+ is a weaker activator, so the reader knows some of the caveats to the approach.

Answer: We thank the reviewer for raising this point. We have added related citations and replaced the term “block” with “inhibit” in the revised manuscript.

Original:

1. In K, for the WT, why is the effect of quinidine only striking for the largest currents?

Answer: We thank the reviewer for raising this point. After conducting an analysis, we found no correlation between the inhibitory effect of quinidine and the amplitudes of baseline IKNa in WT neurons (p = 0.6294) (Author response image 3). Therefore, the effect of quinidine is not solely limited to targeting the larger currents.

Author response image 3.

The correlation between the inhibitory effect of quinidine and the amplitudes of baseline IKNa in WT neurons (data from manuscript Fig. 1K). r = 0.1555, p=0.6294, Pearson correlation analysis.

New comment:

Please add this to the paper and the figure as Supplemental.

Answer: We thank the reviewer for raising this point. We have added this figure as Fig.S3B in the revised manuscript.

Original:

5) Figure 2 A. The argument could be better made if the same concentration of quinidine were used for Slack and Slack + Nav1.6. It is recognized a greater sensitivity to quinidine is to be shown but as presented the figure is a bit confusing."

Answer: We apologize for the confusion. We would like to clarify that the presented concentrations of quinidine were chosen to be near the IC50 values for Slack and Slack+NaV1.6.

New comment:

Please add this to the paper.

Answer: We thank the reviewer for raising this point. We have added the clarification about the presented concentrations in the revised manuscript.

Original:

2C. Can the authors add the effect of quinidine to the condition where the prepulse potential was 90?"

Answer: We apologize for the confusion. We would like to clarify that the condition of prepulse potential at -90 mV is the same as the condition in Fig. 1. We only changed one experiment condition where the prepulse potential was changed to -40 mV from -90 mV.

New comment:

There was no confusion. The authors should consider adding the condition where the prepulse potential was -90.

Answer: We thank the reviewer for raising this point. We have added the clarification about the voltage condition in the revised manuscript (see in Fig. 2A caption).

Original:

2A. Clarify these 6 panels."

Answer: We thank the reviewer for raising this point. We have clarified the captions of Fig. 3A in the revised manuscript.

New comment: Clarification is needed. What is the blue? DAPI? What area of hippocamps? Please label cell layers. What area of cortex? Please label layers.

Answer: We thank the reviewer for raising this point. We have included the clarification in the Figure caption.

Original:

Figure 7. The images need more clarity. They are very hard to see. Text is also hard to see."

Answer: We apologize for the lack of clarity in the images and text. we would like to provide a concise summary of the key findings shown in this figure.

Figure 7 illustrates an innovative intervention for treating SlackG269S-induced seizures in mice by disrupting the Slack-NaV1.6 interaction. Our results showed that blocking NaV1.6-mediated sodium influx significantly reduced Slack current amplitudes (Fig. 2D,G), suggesting that the Slack-NaV1.6 interaction contributes to the current amplitudes of epilepsy-related Slack mutant variants, aggravating the gain-of-function phenotype. Additionally, Slack’s C-terminus is involved in the Slack-NaV1.6 interaction (Fig. 5D). We assumed that overexpressing Slack’s C-terminus can disrupt the Slack-NaV1.6 interaction (compete with Slack) and thereby encounter the current amplitudes of epilepsy-related Slack mutant variants.

In HEK293 cells, overexpression of Slack’s C-terminus indeed significantly reduced the current amplitudes of epilepsy-related SlackG288S and SlackR398Q upon co-expression with NaV1.5/6NC (Fig. 7A,B). Subsequently, we evaluated this intervention in an in vivo epilepsy model by introducing the Slack G269S variant into C57BL/6N mice using AAV injection, mimicking the human Slack mutation G288S that we previously identified (Fig. 7C-G).

New comment:

The images do not appear to have changed. Consider moving labels above the images so they can be distinguished better. Please label cell layers. Consider adding arrows to the point in the figure the authors want the reader to notice. The study design and timeline are unclear. What is (1) + (3), (2), etc.?

Answer: We thank the reviewer for pointing this out. We have modified Figure 7 in the revised manuscript and included the cell layer information in the Figure caption.

Original:

It is not clear how data were obtained because injection of kainic acid does not lead to a convulsive seizure every 10 min for several hours, which is what appears to be shown. Individual seizures are just at the beginning and then they merge at the start of status epilepticus. After the onset of status epilepticus the animals twitch, have varied movements, sometime rear and fall, but there is not a return to normal behavior. Therefore one can not call them individual seizures. In some strains of mice, however, individual convulsive seizures do occur (even if the EEG shows status epilepticus is occurring) but there are rarely more than 5 over several hours and the graph has many more. Please explain."

Answer: We apologize for the confusion. Regarding the data acquisition in relation to kainic acid injection, we initiated the timing following intraperitoneal injection of kainic acid and recorded the seizure scores of per mouse at ten-minute intervals, following the methodology described in previous studies4.

1. Huang Z, Walker MC, Shah MM. Loss of dendritic HCN1 subunits enhances cortical excitability and epileptogenesis. J Neurosci. Sep 2 2009;29(35):10979-88. doi:10.1523/JNEUROSCI.1531-09.2009

The seizure scores were determined using a modified Racine, Pinal, and Rovner scale5,6: (1) Facial movements; (2) head nodding; (3) forelimb clonus; (4) dorsal extension (rearing); (5) Loss of balance and falling; (6) Repeated rearing and failing; (7) Violent jumping and running; (8) Stage 7 with periods of tonus; (9) Dead.

1. Pinel JP, Rovner LI. Electrode placement and kindling-induced experimental epilepsy. Exp Neurol. Jan 15 1978;58(2):335-46. doi:10.1016/0014-4886(78)90145-0

2. Racine RJ. Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr Clin Neurophysiol. Mar 1972;32(3):281-94. doi:10.1016/00134694(72)90177-0

New comment:

This was clear. Perhaps my question was not clear. The question is how one can count individual seizures if animals have continuous seizures. It seems like the authors did not consider or observe status epilepticus but individual seizures. If that is true the data are hard to believe because too many seizures were counted. Animals do not have nearly this many seizures after kainic acid.

Answer: We appreciate the reviewer’s clarification. Our methodology involved assessing the maximum seizure scale during 10-minute intervals per mouse as previously described7, rather than counting individual seizures. For instance, a mouse exhibited the loss of balance and falling multiple times within 30-40 minute interval, we recorded the seizure scale as 5 for that time interval.

1. Kim EC, Zhang J, Tang AY, et al. Spontaneous seizure and memory loss in mice expressing an epileptic encephalopathy variant in the calmodulin-binding domain of Kv7.2. Proc Natl Acad Sci U S A. Dec 21 2021;118(51)doi:10.1073/pnas.2021265118

Reviewer #3 (Recommendations For The Authors):

While the authors have improved the manuscript, several outstanding issues still need to be addressed. Some may have been missed because there is no response at all, but others may have been unclear.

Answer: We thank the reviewer for the criticisms. We have added additional experimental data and analysis to address the concerns.

Original issue from Public Review:

1. Immunolabeling of the hippocampus CA1 suggests sodium channels as well as Slack colocalization with AnkG (Fig 3A). Proximity ligation assay for NaV1.6 and Slack or a super-resolution microscopy approach would be needed to increase confidence in the presented colocalization results. Furthermore, coimmunoprecipitation studies on the membrane fraction would bolster the functional relevance of NaV1.6-Slack interaction on the cell surface.

Answer: We thank the reviewer for good suggestions. We acknowledge that employing proximity ligation assay and high-resolution techniques would significantly enhance our understanding of the localization of the Slack-NaV1.6 coupling.

At present, the technical capabilities available in our laboratory and institution do not support highresolution testing. However, we are enthusiastic about exploring potential collaborations to address these questions in the future. Furthermore, we fully recognize the importance of conducting coimmunoprecipitation (Co-IP) assays from membrane fractions. While we have already completed Co-IP assays for total protein and quantified the FRET efficiency values between Slack and NaV1.6 in the membrane region, the Co-IP assays on membrane fractions will be conducted in our future investigations.

New comment from reviewer: so far, the authors have not demonstrated that Nav1.6 and Slack interact on the cell surface.

Answer: We thank the reviewer for pointing this out. We acknowledgement that our data did not directly demonstrate interaction between NaV1.6 and Slack on the cell surface and we have removed related terminology in the revised manuscript. Notably, our patch-clamp experiments in Fig. 2D,G and Fig. S10B showed a Na+-mediated membrane current coupling of Slack and NaV1.6. Additionally, the FRET efficiency values between Slack and NaV1.6 were quantified in the membrane region. These findings suggest that membrane-near Slack interacts with NaV1.6.

1. Although hippocampal slices from Scn8a+/- were used for studies in Fig. S8, it is not clear whether Scn8a-/- or Scn8a+/- tissue was used in other studies (Fig 1J & 1K). It will be important to clarify whether genetic manipulation of NaV1.6 expression (Fig. 1K) has an impact on sodiumactivated potassium current, level of surface Slack expression, or that of NaV1.6 near Slack.

Answer: We thank the reviewer for pointing this out. In Fig. 1G,J,K, primary cortical neurons from homozygous NaV1.6 knockout (Scn8a-/-) mice were used. We will clarify this information in the revised manuscript. In terms of the effects of genetic manipulation of NaV1.6 expression on IKNa and surface Slack expression, we compared the amplitudes of IKNa measured from homozygous NaV1.6 knockout (NaV1.6-KO) neurons and wild-type (WT) neurons. The results showed that homozygous knockout of NaV1.6 does not alter the amplitudes of IKNa (Author response image 4). The level of surface Slack expression will be tested further.

Author response image 4.

The amplitudes of IKNa in WT and NaV1.6-KO neurons (data from manuscript Fig. 1K). ns, p > 0.05, unpaired two-tailed Student’s t test.

New comment from reviewer: The current version of the manuscrip>t does not contain these pertinent details and needs to be updated to include the information pertaining homozygous NaV1.6 knockouts. What age were these homozygous NaV1.6 knockout mice? These details need to be clearly stated in the manuscript.

Answer: We thank the reviewer for pointing this out. We have included this analysis in the revised manuscript (see Fig. S3A). The age of homozygous NaV1.6 knockout mice are P0-P1 and we have added this detail in the revised manuscript.

1. Did the epilepsy-related Slack mutations have an impact on NaV1.6-mediated sodium current?

Answer: We thank the reviewer’s question. We examined the amplitudes of NaV1.6 sodium current upon expression alone or co-expression of NaV1.6 with epilepsy-related Slack mutations (K629N, R950Q, K985N). The results showed that the tested epilepsy-related Slack mutations do not alter the amplitudes of NaV1.6 sodium current (Author response image 5).

Author response image 5.

The amplitudes of NaV1.6 sodium currents upon co-expression of NaV1.6 with epilepsy-related Slack mutant variants (SlackK629N, SlackR950Q, and SlackK985N). ns, p>0.05, oneway ANOVA followed by Bonferroni’s post hoc test.

New comment from reviewer: Figure with the functional effect of co-expression of NaV1.6 with epilepsy-related Slack mutations should be included in the revised manuscript

Answer: We thank the reviewer for pointing this out. We have included this analysis in the revised manuscript (see Fig. S10A).

Original issue from Recommendations For The Authors:

1. A reference to homozygous knockout is made in the abstract; however, only heterozygous mice are mentioned in the methods section. The genotype of the mice needs to be made clear in the manuscript. Furthermore, at what age were these mice used in the study. Since homozygous knockout of NaV1.6 is lethal at a very young age (<4 wks), it would be important to clarify that point as well.

Answer: We thank the reviewer for pointing this out. In the revised manuscript, we have included information about the source of the primary cortical neurons used in our study. These neurons were obtained from postnatal homozygous NaV1.6 knockout C3HeB/FeJ mice and their wild-type littermate controls.

New comment from reviewer: The answer that postnatal homozygous NaV1.6 knockout C3HeB/FeJ mice were used is insufficient. What age were these mice? This needs to be clearly stated in the manuscript.

Answer: We thank the reviewer for pointing this out. The postnatal homozygous NaV1.6 knockout C3HeB/FeJ mice and their wild-type littermate controls are in P0-P1. We have included this information in the revised manuscript.

1. How long were the cells exposed to quinidine before the functional measurement were performed?

Answer: We thank the reviewer for pointing this out. The cells were exposed to the bath solution with quinidine for about one minute before applying step pulses.

New comment from reviewer: This needs to be clearly stated in the manuscript.

Answer: We thank the reviewer for pointing this out. We have included this information in the revised manuscript (see in Methods section).

1. In Fig. 6B-D, it is not clear to what extent co-expression of Slack mutants and NaV1.6 increases sodium-activated potassium current.

Answer: We thank the reviewer for pointing this out. We notice that the current amplitudes of Slack mutants exhibit a considerable degree of variation, ranging from less than 1 nA to over 20 nA (n =58). To accurately measure the effects of NaV1.6 on increasing current amplitudes of Slack mutants, we plan to apply tetrodotoxin in the bath solution to block NaV1.6 sodium currents upon coexpression of Slack mutants with NaV1.6.

New comment from reviewer: Were these experiments with TTX completed? If so, they should be added to the revised manuscript.

Answer: We thank the reviewer for pointing this out. We compared the current amplitudes of epilepsy-related Slack mutant (SlackR950Q) before and after bath-application of 100 nM TTX upon co-expression with NaV1.6 in HEK293 cells. The results showed that bath-application of TTX significantly reduced the current amplitudes of SlackR950Q at +100 mV by nearly 40% (Author response image 6), suggesting NaV1.6 contributes to the current amplitudes of SlackR950Q. We have included this data in the revised manuscript (see Fig. S10B).

Author response image 6.

The current amplitudes of SlackR950Q before and after bath-application of 100 nM TTX upon co-expression with NaV1.6 in HEK293 cells (n=5). ***p < 0.001, Two-way repeated measures ANOVA followed by Bonferroni’s post hoc test.

Additionally, we have corrected some errors in the methods and figure captions section:

1. Line 513, bath solution “5 glucose” should be “10 glucose.”

2. Figure 3A caption, the description “hippocampus CA1 (left) and neocortex (right)” was flipped and we have corrected it.

References

1. Zhang Z, Rosenhouse-Dantsker A, Tang QY, Noskov S, Logothetis DE. The RCK2 domain uses a coordination site present in Kir channels to confer sodium sensitivity to Slo2.2 channels. J Neurosci. Jun 2 2010;30(22):7554-62. doi:10.1523/JNEUROSCI.0525-10.2010

2. Kaczmarek LK. Slack, Slick and Sodium-Activated Potassium Channels. ISRN Neurosci. Apr 18 2013;2013(2013)doi:10.1155/2013/354262

3. Budelli G, Hage TA, Wei A, et al. Na+-activated K+ channels express a large delayed outward current in neurons during normal physiology. Nat Neurosci. Jun 2009;12(6):745-50. doi:10.1038/nn.2313

4. Huang Z, Walker MC, Shah MM. Loss of dendritic HCN1 subunits enhances cortical excitability and epileptogenesis. J Neurosci. Sep 2 2009;29(35):10979-88. doi:10.1523/JNEUROSCI.1531-09.2009

5. Pinel JP, Rovner LI. Electrode placement and kindling-induced experimental epilepsy. Exp Neurol. Jan 15 1978;58(2):335-46. doi:10.1016/0014-4886(78)90145-0

6. Racine RJ. Modification of seizure activity by electrical stimulation. II. Motor seizure. Electroencephalogr Clin Neurophysiol. Mar 1972;32(3):281-94. doi:10.1016/0013-4694(72)90177-0

7. Kim EC, Zhang J, Tang AY, et al. Spontaneous seizure and memory loss in mice expressing an epileptic encephalopathy variant in the calmodulin-binding domain of Kv7.2. Proc Natl Acad Sci U S A. Dec 21 2021;118(51)doi:10.1073/pnas.2021265118

Author Response

Reviewer #1 (Public Review):

Summary:

In this manuscript, Benner et al. identify OVO as a transcriptional factor instrumental in promoting the expression of hundreds of genes essential for female germline identity and early embryo development. Prior data had identified both ovo and otu as genes activated by OVO binding to the promoters. By combining ChIP-seq, RNA-seq, and analysis of prior datasets, the authors extend these data to hundreds of genes and therefore propose that OVO is a master transcriptional regulator of oocyte development. They further speculate that OVO may function to promote chromatin accessibility to facilitate germline gene expression. Overall, the data compellingly demonstrate a much broader role for OVO in the activation of genes in the female germline than previously recognized. By contrast, the relationship between OVO, chromatin accessibility, and the timing of gene expression is only correlative, and more work will be needed to determine the mechanisms by which OVO promotes transcription.

We fully agree with this summary.

Strengths:

Here Benner et al. convincingly show that OVO is a transcriptional activator that promotes expression of hundreds of genes in the female germline. The ChIP-seq and RNA-seq data included in the manuscript are robust and the analysis is compelling.

Importantly, the set of genes identified is essential for maternal processes, including egg production and patterning of the early embryo. Together, these data identify OVO as a major transcriptional activator of the numerous genes expressed in the female germline, deposited into the oocyte and required for early gene expression. This is an important finding as this is an essential process for development and prior to this study, the major drivers of this gene expression program were unknown.

We are delighted that this aspect of the work came across clearly. Understanding the regulation of maternal effect genes has been something of a black-box, despite the importance of this class of genes in the history of developmental genetics. The repertoire of essential oogenesis/embryonic development genes that are bound by and respond to OVO are well characterized in the literature, but nothing is known about how they are transcriptionally regulated. We feel the manuscript will be of great interest to readers working on these genes.

Weaknesses:

The novelty of the manuscript is somewhat limited as the authors show that, like two prior, well-studied OVO target genes, OVO binds to promoters of germline genes and activates transcription. The fact that OVO performs this function more broadly is not particularly surprising.

Clearly, transcription factors regulate more than one or two genes. Never-the-less we were surprised at how many of the aspects of oogenesis per se and maternal effect genes were OVO targets. It was our hypothesis that OVO would have a transcriptional effect genome-wide, however, it was less clear whether OVO would always bind at the core promoter, as is with the case of ovo and otu. Our results strongly support the idea that core promoter proximal binding is essential for OVO function; a conclusion of work done decades ago, which has not been revisited using modern techniques.

A major challenge to understanding the impact of this manuscript is the fact that the experimental system for the RNA-seq, the tagged constructs, and the expression analysis that provides the rationale for the proposed pioneering function of OVO are all included in a separate manuscript.

This is a case where we ended up with a very, very long manuscript which included a lot of revisiting of legacy data. It was a tough decision on how to break up all the work we had completed on ovo to date. In our opinion, it was too much to put everything into a single manuscript unless we wanted a manuscript length supplement (we were also worried that supplemental data is often overlooked and sometimes poorly reviewed). We therefore decided to split the work into a developmental localization/characterization paper and a functional genomics paper. As it stands both papers are long. Certainly, readers of this manuscript will benefit from reading our previous OVO paper, which we submitted before this one. The earlier manuscript is under revision at another journal and we hope that this improved manuscript will be published and accessible shortly.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Benner et al. interrogate the transcriptional regulator OVO to identify its targets in the Drosophila germline. The authors perform ChIP-seq in the adult ovary and identify established as well as novel OVO binding motifs in potential transcriptional targets of OVO. Through additional bioinformatic analysis of existing ATAC-seq, CAGE-seq, and histone methylation data, the authors confirm previous reports that OVO is enriched at transcription start sites and suggest that OVO does not act as part of the core RNA polymerase complex. Benner et al. then perform bulk RNA-seq in OVO mutant and "wildtype" (GAL4 mediated expression of OVO under the control of the ovo promoter in OVO mutants) ovaries to identify genes that are differentially expressed in the presence of OVO. This analysis supports previous reports that OVO likely acts at transcription start sites as a transcriptional activator. While the authors propose that OVO activates the expression of genes that are important for egg integrity, maturation, and for embryonic development (nanos, gcl, pgc, bicoid), this hypothesis is based on correlation and is not supported by in vivo analysis of the respective OVO binding sites in some of the key genes. A temporal resolution for OVO's role during germline development and egg chamber maturation in the ovary is also missing. Together, this manuscript contains relevant ChIP-seq and RNA-seq datasets of OVO targets in the Drosophila ovary alongside thorough bioinformatic analysis but lacks important in vivo experimental evidence that would validate the high-quality datasets.

We thank reviewer 2 for the appreciation of the genomics data and analysis. Some of the suggested in vivo experiments are clear next steps, which are well underway. These are beyond the scope of the current manuscript.

Temporal analysis of ovo function in egg chamber development is not easy, as only the weakest ovo alleles have any egg chambers to examine. However, we will also point out the long-known phenotypes of some of those weak alleles in the text (e.g. ventralized chambers in ovoD3/+). We will need better tools for precise rescue/degradation during egg chamber maturation.

Strengths:

The manuscript contains relevant ChIP-seq and RNA-seq datasets of OVO targets in the Drosophila ovary alongside thorough bioinformatic analysis

Thank you. We went to great lengths to do our highly replicated experiments in multiple ways (e.g. independent pull-down tags) and spent considerable time coming up with an optimized and robust informatic analysis.

Weaknesses:

1) The authors propose that OVO acts as a positive regulator of essential germline genes, such as those necessary for egg integrity/maturation and embryonic/germline development. Much of this hypothesis is based on GO term analysis (and supported by the authors' ChIP-seq data). However accurate interpretation of GO term enrichment is highly dependent on using the correct background gene set. What control gene set did the authors use to perform GO term analysis (the information was not in the materials and methods)? If a background gene set was not previously specified, it is essential to perform the analysis with the appropriate background gene set. For this analysis, the total set of genes that were identified in the authors' RNA-seq of OVO-positive ovaries would be an ideal control gene set for which to perform GO term analysis. Alternatively, the total set of genes identified in previous scRNA-seq analysis of ovaries (see Rust et al., 2020, Slaidina et al., 2021 among others) would also be an appropriate control gene set for which to perform GO term analysis. If indeed GO term analysis of the genes bound by OVO compared to all genes expressed in the ovary still produces an enrichment of genes essential for embryonic development and egg integrity, then this hypothesis can be considered.

We feel that this work on OVO as a positive regulator of genes like bcd, osk, nos, png, gnu, plu, etc., is closer to a demonstration than a proposition. These are textbook examples of genes required for egg and early embryonic development. Hopefully, this is not lost on the readers by an over-reliance on GO term analysis, which is required but not always useful in genome-wide studies.

We used GO term enrichment analysis as a tool to help focus the story on some major pathways that OVO is regulating. To the specific criticism of the reference gene-set, GO term enrichment analysis in this work is robust to gene background set. We will update the GO term enrichment analysis text to indicate this fact and add a table using expressed genes in our RNA-seq dataset to the manuscript and clarify gene set robustness in greater detail in the methods of the revision. We will also try to focus the reader’s attention on the actual target genes rather than the GO terms in the revised text.

2) The authors provide important bioinformatic analysis of new and existing datasets that suggest OVO binds to specific motifs in the promoter regions of certain germline genes. While the bioinformatic analysis of these data is thorough and appropriate, the authors do not perform any in vivo validation of these datasets to support their hypotheses. The authors should choose a few important potential OVO targets based on their analysis, such as gcl, nanos, or bicoid (as these genes have well-studied phenotypes in embryogenesis), and perform functional analysis of the OVO binding site in their promoter regions. This may include creating CRISPR lines that do not contain the OVO binding site in the target gene promoter, or reporter lines with and without the OVO binding site, to test if OVO binding is essential for the transcription/function of the candidate genes.

Exploring mechanism using in vivo phenotypic assays is awesome, so this is a very good suggestion. But, it is not essential for this work -- as has been pointed out in the reviews, in vivo validation of OVO binding sites has been comprehensively done for two target genes, ovo and otu. The “rules” appear similar for both genes. That said, we are already following up specific OVO target genes and the detailed mechanism of OVO function at the core promoter. We removed some of our preliminary in vivo figures from the already long current manuscript. We continue to work on OVO and expect to include this type of analysis in a new manuscript.

3) The authors perform de novo motif analysis to identify novel OVO binding motifs in their ChIP-seq dataset. Motif analysis can be significantly strengthened by comparing DNA sequences within peaks, to sequences that are just outside of peak regions, thereby generating motifs that are specific to peak regions compared to other regions of the promoter/genome. For example, taking the 200 nt sequence on either side of an OVO peak could be used as a negative control sequence set. What control sequence set did the authors use as for their de novo motif analysis? More detail on this is necessary in the materials and methods section. Re-analysis with an appropriate negative control sequence set is suggested if not previously performed.

We apologize for being unclear on negative sequence controls in the methods. We used shuffled OVO ChIP-seq peak sequences as the background for the de novo motif analysis, which we will better outline in the methods of the revision. This is a superior background set of sequences as it exactly balances GC content in the query and background sequences. We are not fond of the idea of using adjacent DNA that won’t be controlled for GC content and shadow motifs. Furthermore, the de novo OVO DNA binding motifs are clear, statistically significant variants of the characterized in vitro OVO DNA binding motifs previously identified (Lu et al., 1998; Lee and Garfinkel, 2000; Bielinska et al., 2005), which lends considerable confidence. We also show that the OVO ChIP-seq read density are highly enriched for all our identified motifs, as well as the in vitro motifs. We provide multiple lines of evidence, through multiple methods, that the core OVO DNA binding motif is 5’-TAACNGT-3’. We have high confidence in the motif data.

4) The authors mention that OVO binding (based on their ChIP-seq data) is highly associated with increased gene expression (lines 433-434). How many of the 3,094 peaks (conservative OVO binding sites), and what percentage of those peaks, are associated with a significant increase in gene expression from the RNA-seq data? How many are associated with a decrease in gene expression? This information should be added to the results section.

Not including the numbers of the overlapping ChIP peaks and expression changes in the text was an oversight on our part. The numbers that relate to this (666 peaks overlapping genes that significantly increased in expression, significant enrichment according to Fishers exact test, 564 peaks overlapping genes that significantly decreased in expression, significant depletion according to Fishers exact test) are found in figure 4C and will be added to the text.

5) The authors mention that a change in endogenous OVO expression cannot be determined from the RNA-seq data due to the expression of the OVO-B cDNA rescue construct. Can the authors see a change in endogenous OVO expression based on the presence/absence of OVO introns in their RNA-seq dataset? While intronic sequences are relatively rare in RNA-seq, even a 0.1% capture rate of intronic sequence is likely to be enough to determine the change in endogenous OVO expression in the rescue construct compared to the OVO null.

This is a good point. The GAL4 transcript is downstream of ovo expression in the hypomorphic ovoovo-GAL4 allele. We state in the text that there is a nonsignificant increase in GAL4 expression with ectopic rescue OVO, although the trend is positive. We calculated the RPKM of RNA-seq reads mapping to the intron spanning exon 3 and exon 4 in ovo-RA and found that there is also a nonsignificant increase in intronic RPKM with ectopic rescue OVO (we will add to the results in the revision). We would expect OVO to be autoregulatory and potentially increase the expression of GAL4 and/or intronic reads, but the ovoovo-GAL4>UASp-OVOB is not directly autoregulatory like the endogenous locus. It is not clear to us how the intervening GAL4 activity would affect OVOB activity in the artificial circuit. Dampening? Feed-forward? Is there an effect on OVOA activity? Regardless, this result does not change our interpretation of the other OVO target genes.

6) The authors conclude with a model of how OVO may participate in the activation of transcription in embryonic pole cells. However, the authors did not carry out any experiments with pole cells that would support/test such a model. It may be more useful to end with a model that describes OVO's role in oogenesis, which is the experimental focus of the manuscript.

We did not complete any experiments in embryonic pole cells in this manuscript and base our discussion on the potential dynamics of OVO transcriptional control and our previous work showing maternal and zygotic OVO protein localization in the developing embryonic germline. Obviously, we are highly interested in this question and continue to work on the role of maternal OVO. We agree that we are extended too far and will remove the embryonic germ cell model in the figure. We will instead focus on the possible mechanisms of OVO gene regulation in light of the evidence we have shown in the adult ovary, as suggested.

eLife assessment

Benner et al. identify OVO as a transcriptional factor instrumental in promoting the expression of hundreds of genes essential for female germline identity and early embryo development. While they provide the dataset that supports their model, the major evidence for the model proposed in this manuscript comes from a separate manuscript by the same group, making the contribution of this manuscript somewhat unclear - that is, the evidence provided in this paper is incomplete to support the proposal of this paper. Overall, the study provides useful information that will help understand the function of ovo during oogenesis and early embryonic development.

Reviewer #1 (Public Review):

Summary:

In this manuscript, Benner et al. identify OVO as a transcriptional factor instrumental in promoting the expression of hundreds of genes essential for female germline identity and early embryo development. Prior data had identified both ovo and otu as genes activated by OVO binding to the promoters. By combining ChIP-seq, RNA-seq, and analysis of prior datasets, the authors extend these data to hundreds of genes and therefore propose that OVO is a master transcriptional regulator of oocyte development. They further speculate that OVO may function to promote chromatin accessibility to facilitate germline gene expression. Overall, the data compellingly demonstrate a much broader role for OVO in the activation of genes in the female germline than previously recognized. By contrast, the relationship between OVO, chromatin accessibility, and the timing of gene expression is only correlative, and more work will be needed to determine the mechanisms by which OVO promotes transcription.

Strengths:

Here Benner et al. convincingly show that OVO is a transcriptional activator that promotes expression of hundreds of genes in the female germline. The ChIP-seq and RNA-seq data included in the manuscript are robust and the analysis is compelling.

Importantly, the set of genes identified is essential for maternal processes, including egg production and patterning of the early embryo. Together, these data identify OVO as a major transcriptional activator of the numerous genes expressed in the female germline, deposited into the oocyte and required for early gene expression. This is an important finding as this is an essential process for development and prior to this study, the major drivers of this gene expression program were unknown.

Weaknesses:

The novelty of the manuscript is somewhat limited as the authors show that, like two prior, well-studied OVO target genes, OVO binds to promoters of germline genes and activates transcription. The fact that OVO performs this function more broadly is not particularly surprising.

A major challenge to understanding the impact of this manuscript is the fact that the experimental system for the RNA-seq, the tagged constructs, and the expression analysis that provides the rationale for the proposed pioneering function of OVO are all included in a separate manuscript.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Benner et al. interrogate the transcriptional regulator OVO to identify its targets in the Drosophila germline. The authors perform ChIP-seq in the adult ovary and identify established as well as novel OVO binding motifs in potential transcriptional targets of OVO. Through additional bioinformatic analysis of existing ATAC-seq, CAGE-seq, and histone methylation data, the authors confirm previous reports that OVO is enriched at transcription start sites and suggest that OVO does not act as part of the core RNA polymerase complex. Benner et al. then perform bulk RNA-seq in OVO mutant and "wildtype" (GAL4 mediated expression of OVO under the control of the ovo promoter in OVO mutants) ovaries to identify genes that are differentially expressed in the presence of OVO. This analysis supports previous reports that OVO likely acts at transcription start sites as a transcriptional activator. While the authors propose that OVO activates the expression of genes that are important for egg integrity, maturation, and for embryonic development (nanos, gcl, pgc, bicoid), this hypothesis is based on correlation and is not supported by in vivo analysis of the respective OVO binding sites in some of the key genes. A temporal resolution for OVO's role during germline development and egg chamber maturation in the ovary is also missing. Together, this manuscript contains relevant ChIP-seq and RNA-seq datasets of OVO targets in the Drosophila ovary alongside thorough bioinformatic analysis but lacks important in vivo experimental evidence that would validate the high-quality datasets.

Strengths:

The manuscript contains relevant ChIP-seq and RNA-seq datasets of OVO targets in the Drosophila ovary alongside thorough bioinformatic analysis

Weaknesses:

1. The authors propose that OVO acts as a positive regulator of essential germline genes, such as those necessary for egg integrity/maturation and embryonic/germline development. Much of this hypothesis is based on GO term analysis (and supported by the authors' ChIP-seq data). However accurate interpretation of GO term enrichment is highly dependent on using the correct background gene set. What control gene set did the authors use to perform GO term analysis (the information was not in the materials and methods)? If a background gene set was not previously specified, it is essential to perform the analysis with the appropriate background gene set. For this analysis, the total set of genes that were identified in the authors' RNA-seq of OVO-positive ovaries would be an ideal control gene set for which to perform GO term analysis. Alternatively, the total set of genes identified in previous scRNA-seq analysis of ovaries (see Rust et al., 2020, Slaidina et al., 2021 among others) would also be an appropriate control gene set for which to perform GO term analysis. If indeed GO term analysis of the genes bound by OVO compared to all genes expressed in the ovary still produces an enrichment of genes essential for embryonic development and egg integrity, then this hypothesis can be considered.

2. The authors provide important bioinformatic analysis of new and existing datasets that suggest OVO binds to specific motifs in the promoter regions of certain germline genes. While the bioinformatic analysis of these data is thorough and appropriate, the authors do not perform any in vivo validation of these datasets to support their hypotheses. The authors should choose a few important potential OVO targets based on their analysis, such as gcl, nanos, or bicoid (as these genes have well-studied phenotypes in embryogenesis), and perform functional analysis of the OVO binding site in their promoter regions. This may include creating CRISPR lines that do not contain the OVO binding site in the target gene promoter, or reporter lines with and without the OVO binding site, to test if OVO binding is essential for the transcription/function of the candidate genes.

3. The authors perform de novo motif analysis to identify novel OVO binding motifs in their ChIP-seq dataset. Motif analysis can be significantly strengthened by comparing DNA sequences within peaks, to sequences that are just outside of peak regions, thereby generating motifs that are specific to peak regions compared to other regions of the promoter/genome. For example, taking the 200 nt sequence on either side of an OVO peak could be used as a negative control sequence set. What control sequence set did the authors use as for their de novo motif analysis? More detail on this is necessary in the materials and methods section. Re-analysis with an appropriate negative control sequence set is suggested if not previously performed.

4. The authors mention that OVO binding (based on their ChIP-seq data) is highly associated with increased gene expression (lines 433-434). How many of the 3,094 peaks (conservative OVO binding sites), and what percentage of those peaks, are associated with a significant increase in gene expression from the RNA-seq data? How many are associated with a decrease in gene expression? This information should be added to the results section.

5. The authors mention that a change in endogenous OVO expression cannot be determined from the RNA-seq data due to the expression of the OVO-B cDNA rescue construct. Can the authors see a change in endogenous OVO expression based on the presence/absence of OVO introns in their RNA-seq dataset? While intronic sequences are relatively rare in RNA-seq, even a 0.1% capture rate of intronic sequence is likely to be enough to determine the change in endogenous OVO expression in the rescue construct compared to the OVO null.

6. The authors conclude with a model of how OVO may participate in the activation of transcription in embryonic pole cells. However, the authors did not carry out any experiments with pole cells that would support/test such a model. It may be more useful to end with a model that describes OVO's role in oogenesis, which is the experimental focus of themanuscript.

Author Response

The following is the authors’ response to the original reviews.

Reviewer #1:

Drawing on insights from preceding studies, the researchers pinpointed mutations within the spag7 gene that correlate with metabolic aberrations in mice. The precise function of spag7 has not been fully described yet, thereby the primary objective of this investigation is to unravel its pivotal role in the development of obesity and metabolic disease in mice. First, they generated a mice model lacking spag7 and observed that KO mice exhibited diminished birth size, which subsequently progressed to manifest obesity and impaired glucose tolerance upon reaching adulthood. This behaviour was primarily attributed to a reduction in energy expenditure. In fact, KO animals demonstrated compromised exercise endurance and muscle functionality, stemming from a deterioration in mitochondrial activity. Intriguingly, none of these effects was observed when using a tamoxifen-induced KO mouse model, implying that Spag7's influence is predominantly confined to the embryonic developmental phase. Explorations within placental tissue unveiled that mice afflicted by Spag7 deficiency experienced placental insufficiency, likely due to aberrant development of the placental junctional zone, a phenomenon that could impede optimal nutrient conveyance to the developing fetus. Overall, the authors assert that Spag7 emerges as a crucial determinant orchestrating accurate embryogenesis and subsequent energy balance in the later stages of life.

The study boasts several noteworthy strengths. Notably, it employs a combination of animal models and a thorough analysis of metabolic and exercise parameters, underscoring a meticulous approach. Furthermore, the investigation encompasses a comprehensive evaluation of fetal loss across distinct pregnancy stages, alongside a transcriptomic analysis of skeletal muscle, thereby imparting substantial value. However, a pivotal weakness of the study centres on its translational applicability. While the authors claim that "SPAG7 is well-conserved with 97% of the amino acid sequence being identical in humans and mice", the precise role of spag7 in the human context remains enigmatic. This limitation hampers a direct extrapolation of findings to human scenarios. Additionally, the study's elucidation of the molecular underpinnings behind the spag7-mediated anomalous development of the placental junction zone remains incomplete. Finally, the hypothesis positing a reduction in nutrient availability to the fetus, though intriguing, requires further substantiation, leaving an aspect of the mechanism unexplored.

Hence, in order to fortify the solidity of their conclusions, these concerns necessitate meticulous attention and resolution in the forthcoming version of the manuscript. Upon the comprehensive addressing of these aspects, the study is poised to exert a substantial influence on the field, its significance reverberating significantly. The methodologies and data presented undoubtedly hold the potential to facilitate the community's deeper understanding of the ramifications stemming from disruptions during pregnancy, shedding light on their enduring impact on the metabolic well-being of subsequent generations.

Thanks to this reviewer for their thoughtful analysis and commentary. Human mutations in SPAG7 are exceedingly rare (SPAG7 | pLoF (genebass.org)), potentially because of the deleterious effects of SPAG7-deficiency on prenatal development. This makes investigation into the causative effects of SPAG7 in humans challenging. There exist mutations in the SPAG7 region of the genome that are associated with BMI, but no direct coding variants within the spag7 gene itself have been studied.

We agree with the reviewer that the precise role of spag7 in the placenta remains unknown. However, given its robust expression and high protein levels in the placenta, including in key cells, such as the syncytiotrophoblast (https://www.proteinatlas.org/ENSG00000091640-SPAG7/tissue/Placenta), it is highly likely that spag7 is critical for normal placenta development and function. Multiple studies (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716072/) have recently shown that sperm associated RNAs play a critical role in embryonic and early placenta development. Our findings will provide the basis for future studies that can elucidate the role of spag7 in human placenta.

Reviewer #2:

Summary:

The authors of this manuscript are interested in discovering and functionally characterizing genes that might cause obesity. To find such genes, they conducted a forward genetic screen in mice, selecting strains which displayed increased body weight and adiposity. They found a strain, with germ-line deficiency in the gene Spag7, which displayed significantly increased body weight, fat mass, and adipose depot sizes manifesting after the onset of adulthood (20 weeks). The mice also display decreased organ sizes, leading to decreased lean body mass. The increased adiposity was traced to decreased energy expenditure at both room temperature and thermoneutrality, correlating with decreased locomotor activity and muscle atrophy. Major metabolic abnormalities such as impaired glucose tolerance and insulin sensitivity also accompanied the phenotype. Unexpectedly, when the authors generated an inducible, whole body knockout mouse using a globally expressed Cre-ERT2 along with a globally floxed Spag7, and induced Spag7 knockout before the onset of obesity, none of the phenotypes seen in the original strain were recapitulated. The authors trace this discrepancy to the major effect of Spag7 being on placental development.

Strengths:

Strengths of the manuscript are its inherently unbiased approach, using a forward genetic screen to discover previously unknown genes linked to obesity phenotypes. Another strong aspect of the work was the generation of an independent, complementary, strain consisting of an inducible knockout model, in which the deficiency of the gene could be assessed in a more granular form. This approach enabled the discovery of Spag7 as a gene involved in the establishment of the mature placenta, which determines the metabolic fate of the offspring. Additional strengths include the extensive array of physiological parameters measured, which provided a deep understanding of the whole-body metabolic phenotype and pinpointed its likely origin to muscle energetic dysfunction.

Weaknesses:

Weaknesses that can be raised are the lack of molecular mechanistic understanding of the numerous phenotypic observations. For example, the specific role of Spag7 to promote placental development remains unclear. Also, the reason why placental developmental abnormalities lead to muscle dysfunction, and whether indeed the entire metabolic phenotype of the offspring can be attributed solely to decreased muscle energetics is not fully explored.

Overall, the authors achieved a remarkable success in identifying genes associated with development of obesity and metabolic disease, discovering the role of Spag7 in placental development, and highlighting the fundamental role of in-utero development in setting future metabolic state of the offspring.

We thank this reviewer for their thoughtful analysis and commentary. Significant effort has been made to understand the causes of the metabolic phenotypes observed in SPAG7-deficient mouse models. It is clear that hyperphagia is not the cause and the muscle energetics deficit is likely not the sole cause. We expect that decreased access to nutrition in utero will lead to widespread and varied metabolic adaptation.

We agree with the reviewer that further work can be done to understand the molecular mechanism driving the metabolic phenotypes of SPAG7-deficient animals. We believe that full investigation of the processes behind the developmental abnormalities is beyond the scope of this paper and best to be done under a separate paper.

Reviewer #3:

Summary:

The manuscript by Flaherty III S.E. et al identified SPAG7 gene in their forward mutagenetic screening and created the germline knockout and inducible knockout mice. The authors reported that the SPAG7 germline knockout mice had lower birth weight likely due to intrauterine growth restriction and placental insufficiency. The SPAG7 KO mice later developed obesity phenotype as a result of reduced energy expenditure. However, the inducible SPAG7 knockout mice had normal body weight and composition.

Strengths:

In this reviewer's opinion, this study has high significance in the field of metabolic research for the following reasons.

1) The authors' findings are significant in the field of obesity research, especially from the perspective of maternal-fetal medicine. The authors created and analyzed the SPAG7 KO mice and found that the KO mice had a "thrifty phenotype" and developed obesity.

2) SPAG7 gene function hasn't been thoroughly studied. The reported phenotype will fill the gap of knowledge.

Overall, the authors have presented their results in a clear and logically organized structure, clearly stated the key question to be addressed, used the appropriate methodology, produced significant and innovative main findings.

Weaknesses:

The manuscript can be further strengthened with more clarification on the following points.

1) The germline whole-body KO mice were female mice (Line293), however the inducible knockout mice were male mice (Line549). Sexual dimorphism is often observed in metabolic studies, therefore the metabolic phenotype of both female and male mice needs to be reported for the germline and inducible knockouts in order to make the justified conclusion.

2) SPAG7 has an NLS. Does this protein function in gene expression? Whether the overall metabolic phenotype is the direct cause of SPAG7 ablation is unclear. For example, the Hsd17b10 gene was downregulated in all tissues in the KO mice. Could this have been coincidentally selected for and thus be the cause of the developmental issues and adulthood obesity? Do the iSpag7 mice demonstrate reduced expression of Hsd17b10?

3) Figure 2c should display the energy expenditure normalized to body weight (or lean body mass).

4) Please provide more information for the figure legend, including the statistical test that was conducted for each data set, animal numbers for each genotype and sexes.

5) The authors should report how long after treatment the data was collected for figures 4F-M.

6) The authors should justify ending the data collection after 8 weeks for the iSPAG7 mice in Figures 4C-E. In the WT vs germline KO mice, there was no clear difference in body weight or lean mass at 15 weeks of age.

Response to point #1 (Weakness): We thank the reviewer for their thoughtful analysis and commentary. All inducible KO animals described in the paper are female (the typo in Line 549 has been corrected). We did perform studies in both male and female animals for both of these lines. Males display similar metabolic phenotypes, though not as robustly as the females. A table summarizing key data from male and female germline KO animals and inducible KO animals has been included below.

Author response table 1.

Author response table 2.

Response to point #2 (Weakness): SPAG7 contains an R3H domain, which is predicted to bind polynucleotides, and other proteins that contain R3H domains are known to bind RNA or ssDNA. The iSPAG7 mice do display decreased hsd17b10 expression (to a lesser degree than the germline KOs) in the tissues examined. When we knock-down SPAG7 in specific tissues, we also see hsd17b10 expression decrease specifically in those tissues. These data all suggest that hsd17b10 expression is, at least, linked to spag7 expression. They also raise the question of why these animals have no metabolic phenotype. Some possible explanations are that hsd17b10 expression is essential only during early development, or that the lower magnitude of downregulation of hsd17b10 in the iSPAG7 is insufficient to produce the metabolic phenotypes seen in the germline Kos with higher magnitude of downregulation.

Response to point #3 (Weakness): How best to normalize total energy expenditure data is a subject of debate within the energy expenditure field. As the animals have increased body weight and decreased lean mass, normalizing to either will skew the results in different directions. We have included the data normalized to body weight and to lean mass below. The decrease in total energy expenditure remains significant in either scenario.

Author response image 1.

Response to point #4 (Weakness): The information has been added to all figures.

Response to point #5 (Weakness): Weeks after treatment have been added to the figure legends for Figures 4F-M.

Response to point #6 (Weakness): Highly significant changes in fat mass, glucose tolerance and insulin sensitivity are already present in the germline SPAG7 KO mice at age of 15 week or earlier. Tamoxifen injection effectively induced SPA7 gene KO in less than a week in the iSPAG7 KO mice. Given the absence of significant changes or any trends towards significance in glucose and insulin tolerance test as well as other metabolic testes in the iSPAG7 KO mice at age of 15 week (same age as the germline KO when these changes observed) and 8 week after SPAG7 gene KO, we did not anticipate to see the changes beyond this point and decided to stop the study at 9 weeks after treatment.

eLife assessment

This study combines molecular genetics and target validation to discover genes involved in obesity and determine their role. It was unanimously agreed that the work is important in terms of significance as it has conceptual and practical implications beyond metabolism, including embryonic and placental development. The strength of evidence is convincing from the use of their forward genetic screen in mice.

Reviewer #2 (Public Review):

Summary:

The authors of this manuscript are interested in discovering and functionally characterizing genes that might cause obesity. To find such genes, they conducted a forward genetic screen in mice, selecting strains which displayed increased body weight and adiposity. They found a strain, with germ-line deficiency in the gene Spag7, which displayed significantly increased body weight, fat mass, and adipose depot sizes manifesting after the onset of adulthood (20 weeks). The mice also display decreased organ sizes, leading to decreased lean body mass. The increased adiposity was traced to decreased energy expenditure at both room temperature and thermoneutrality, correlating with decreased locomotor activity and muscle atrophy. Major metabolic abnormalities such as impaired glucose tolerance and insulin sensitivity also accompanied the phenotype. Unexpectedly, when the authors generated an inducible, whole body knockout mouse using a globally expressed Cre-ERT2 along with a globally floxed Spag7, and induced Spag7 knockout before the onset of obesity, none of the phenotypes seen in the original strain were recapitulated. The authors trace this discrepancy to the major effect of Spag7 being on placental development.

Strengths:

Strengths of the manuscript are its inherently unbiased approach, using a forward genetic screen to discover previously unknown genes linked to obesity phenotypes. Another strong aspect of the work was the generation of an independent, complementary, strain consisting of an inducible knockout model, in which the deficiency of the gene could be assessed in a more granular form. This approach enabled the discovery of Spag7 as a gene involved in the establishment of the mature placenta, which determines the metabolic fate of the offspring. Additional strengths include the extensive array of physiological parameters measured, which provided a deep understanding of the whole-body metabolic phenotype and pinpointed its likely origin to muscle energetic dysfunction.

Weaknesses:

Weaknesses that can be raised are the lack of molecular mechanistic understanding of the numerous phenotypic observations. For example, the specific role of Spag7 to promote placental development remains unclear. Also, the reason why placental developmental abnormalities lead to muscle dysfunction, and whether indeed the entire metabolic phenotype of the offspring can be attributed solely to decreased muscle energetics is not fully explored.

Overall, the authors achieved a remarkable success in identifying genes associated with development of obesity and metabolic disease, discovering the role of Spag7 in placental development, and highlighting the fundamental role of in-utero development in setting future metabolic state of the offspring.

Comments on revised version:

I have no further comments on my assessment of this interesting paper.

Reviewer #3 (Public Review):

Summary:

The manuscript by Flaherty III S.E. et al identified SPAG7 gene in their forward mutagenetic screening and created the germline knockout and inducible knockout mice. The authors reported that the SPAG7 germline knockout mice had lower birth weight likely due to intrauterine growth restriction and placental insufficiency. The SPAG7 KO mice later developed obesity phenotype as result of reduced energy expenditure. However, the inducible SPAG7 knockout mice had normal body weight and composition.

Strengths:

In this reviewer's opinion, this study has high significance in the field of metabolic research for the following reasons.

1) The authors' findings are significant in the field of obesity research, especially from the perspective of maternal-fetal medicine. The authors created and analyzed the SPAG7 KO mice and found that the KO mice had a "thrifty phenotype" and developed obesity.

2) SPAG7 gene function hasn't been thoroughly studied. The reported phenotype will fill the gap of knowledge.

Overall, the authors have presented their results in a clear and logically organized structure, clearly stated the key question to be addressed, used the appropriate methodology, produced significant and innovative main findings.

Comments on revised version:

The authors have satisfactorily addressed my previous concerns.

Author Response

The following is the authors’ response to the original reviews.

Reviewer #2 (Public Review)

Weaknesses

1) The usage of young growing mice (8-10 weeks) versus adult mice (>4 months) in the murine mechanical overload experiments. The usage of adult mice would be preferable for these experiments given that maturational growth may somehow affect the outcomes.

The basis for this critique is not clear as it has been shown that the longitudinal growth of bones is complete by ⁓8 weeks of age (e.g., PMID: 28326349, and 31997656). These studies, along with others, also indicate that 8 weeks is a post-pubescent age in mice. For these reasons, 8 weeks of age was viewed as being representative of the human equivalent of when people start to perform resistance exercise with the goal of increasing muscle mass. Also, it’s important to consider that the mice were 10-12 weeks of age when the muscles were collected which would be equivalent to a human in their lower 20’s. In our human study, the mean age of the subjects was 23. Given the above points, it’s hard for us to appreciate why the use of mice that started at 8-10 weeks of age is viewed as a weakness. With that being said, we recognize that there may be age-related changes in mechanisms of mechanical load-induced growth, but it was not our intent to address this topic.

1b) No consideration for biological sex.

We appreciate this point and we agree that sex is an important variable to consider. In this study, we explored an unchartered topic and therefore we wanted to minimize as many known variables as possible. We did that, in part, by focusing specifically on male subjects. In the future, it will certainly be important to explore whether sex (and age) impact the structural adaptations that drive the mechanical load-induced growth of muscle fibers.

2) Information on whether myofibrillogenesis is dependent on hypertrophy induced by loading, or just hypertrophy in general. To provide information on this, the authors could use, for instance, inducible Myostatin KO mice (a model where hypertrophy and force production are not always in lockstep) to see whether hypertrophy independent from load induces the same result as muscle loading regarding myofibrillogenesis.

This is a great suggestion, but it goes beyond the intended scope of our study. Nevertheless, with the publication of our FIM-ID methodology, the answer to this and related questions can now be obtained in a time- and cost-effective manner.

3) Limited information on Type 1 fiber hypertrophy. A "dual overload" model is used for the mouse where the soleus is also overloaded, but presumably, the soleus was too damaged to analyze. Exploring hypertrophy of murine Type 1 fibers using a different model (weight pulling, weighted wheel running, or forced treadmill running) would be a welcome addition.

The point is well taken and further studies that are aimed at determining whether there are differences in how Type I vs. Type II fibers grow would be an excellent subject for future studies.

Reviewer #3 (Public Review)

1) Supplemental Figure 1 is not very clear.

Supplemental Figure 1 is now presented as Supplemental Figure 2. We carefully reexamined this figure and, in our opinion, the key points have been appropriately conveyed. We would be more than happy to revise the figure, but we would need guidance with respect to which aspect(s) of the figure were not clear to the reviewer.

Reviewer #1 (Recommendations For The Authors)

Introduction.

1) I do not think the first paragraph is really necessary. Cell growth is a fundamental property of cell biology that requires no further justification.

We believe that it is essential to remind all readers about the importance of skeletal muscle research. For some, the detrimental impact of skeletal muscle loss on one’s quality of life and the greater burden on the healthcare system may not be known.

2) I prefer "fundamental" over "foundationally".

All mentions of the word “foundational” and “foundationally” have been changed to “fundamental” and “fundamentally.”

3) As usual for the Hornberger lab, the authors do an excellent job of providing the (historical) context of the research question.

Thank you for this positive comment.

4) I prefer “Goldspink” as “Dr. Goldspink” feels too personal especially when you are critical of his studies.

All instances of “Dr.” have been removed when referring to the works of others. This includes Dr. Goldspink and Dr. Tokuyasu.

5) Fourth paragraph, after reference #17. I felt like this discussion was not necessary and did not really add any value to the introduction.

We believe that this discussion should remain since it highlights the widely accepted notion that mechanical loading leads to an increase in the number of myofibrils per fiber, yet there is no compelling data to support this notion. This discussion highlights the need for documented evidence for the increase in myofibril number in response to mechanical loading and, as such, it serves as a major part of the premise for the experiments that were conducted in our manuscript.

6) The authors do a nice job of laying out the challenge of rigorously testing the Goldspink model of myofiber hypertrophy.

Thank you!

Results

1). For the EM images, can the authors provide a representative image of myofibril tracing? From the EM image provided, it is difficult to evaluate how accurate the tracing is.

-Representative images and an explanation of myofibril calculation have been provided in Supplemental Figure 5.

2) In the mouse, how does the mean myofibril CSA compare between EM and FIM-ID?

Author response image 1.

The above figures compare the myofibril CSA and fiber CSA measurements that were obtained with EM and FIM-ID for all analyzed fibers, as well as the same fibers separated according to the fiber type (i.e., Ox vs. Gly). The above figure shows that the FIM-ID measurements of myofibril CSA were slightly, yet significantly, lower than the measurements obtained with EM. However, we believe that it would be misleading to present the data in this manner. Specifically, as shown in Fig. 4C, a positive linear relationship exists between myofibril CSA and fiber CSA. Thus, a direct comparison of myofibril CSA measurements obtained from EM and FIM-ID would only be meaningful if the mean CSA of the fibers that were analyzed were the same. As shown on the panel on the right, the mean CSA of the fibers analyzed with FIM-ID was slightly, yet significantly, lower than the mean CSA of the fibers analyzed with EM. As such, we believe that the most appropriate way to compare the measurements of the two methods is to express the values for the myofibril CSA relative to the fiber CSA and this is how we presented the data in the main figure (i.e., Fig. 4E).

3) Looking at Fig. 3D, how is intermyofibrillar space calculated when a significant proportion of the ROI is odd-shaped myofibrils that are not outlined? It is not clear how the intermyofibrillar space between the odd-shaped myofibrils is included in the total intermyofibrillar space calculation for the fiber.

The area occupied by the intermyofibrillar components is calculated by using our custom “Intermyofibrillar Area” pipeline within CellProfiler. Briefly, the program creates a binary image of the SERCA signal. The area occupied by the white pixels in the binary image is then used to calculate the area that is occupied by the intermyofibrillar components. To help readers, an example of this process is now provided in supplemental figure 4.

4) What is the average percentage of each ROI that was not counted by CP (because a myofibril did not fit the shape criteria)? The concern is that the method of collection is biasing the data. In looking at EM images of myofibrils (from other studies), it is apparent that myofibrils are not always oval; in fact, it appears that often myofibrils have a more rectangular shape. These odd-shaped myofibrils are excluded from the analysis yet they might provide important information; maybe these odd-shaped myofibrils always hypertrophy such that their inclusion might change the overall conclusion of the study. I completely understand the challenges of trying to quantify odd-shaped myofibrils. I think it is important the authors discuss this important limitation of the study.

First, we would like to clarify that myofibrils of a generally rectangular shape were not excluded. The intent of the filtering steps was to exclude objects that exhibited odd shapes because of an incomplete closure of the signal from SERCA. To illustrate this point we have annotated the images from Figure 3B-D with a red arrow which points to a rectangular object and blue arrows which point to objects that most likely consisted of two or more individual myofibrils that were falsely identified as a single object.

Author response image 2.

We appreciate the reviewer's concern that differences in the exclusion rates between groups could have biased the outcomes. Indeed, this was something that we were keeping a careful eye on during our analyses, and we hope that the reviewer will take comfort in knowing that objects were excluded at a very similar rate in both the mouse and human samples (44% vs. 46% for SHAM vs. MOV in mice, and 47% vs. 47% for PRE vs. POST in humans). We realize that this important data should have been included in our original submission and it is now contained with the results section of the revised version of our manuscript. Hopefully the explanation above, along with the inclusion of this data, will alleviate the reviewers concerns that differences between the groups may have been biased by the filtering steps.

Discussion.

1) I think the authors provided a balanced interpretation of the data by acknowledging the limitation of having only one time-point. i.e., not being able to assess the myofibril splitting mechanism.

Thank you!

2) I think a discussion on the important limitation of only quantifying oval-shaped myofibrils should be included in the discussion.

Please refer to our response to comment #4 of the results section.

Reviewer #2 (Recommendations For The Authors)

Overall, this is a thoughtful, clear, and impactful manuscript that provides valuable tools and information for the skeletal muscle field. My specific comments are as follows:

1) In the introduction, I really appreciate the historical aspect provided on myofbrillogenesis. As written, however, I was expecting the authors to tackle the myofibril "splitting" question in greater detail with their experiments given the amount of real estate given to that topic, but this was not the case. Consider toning this down a bit as I think it sets a false expectation.

We acknowledge that the study does not directly address the question about myofibril splitting. However, we believe that it is important to highlight the background of this untested theory since it serves as a major part of the premise for the experiments that were performed.

2) In the introduction, is it worth worth citing this study? https://rupress.org/jcb/articlepdf/111/5/1885/1464125/1885.pdf.

This is a very interesting study but, despite the title, we do not believe that it is accurate to say that this study investigated myofibrillogenesis. Instead (as illustrated by the author in Fig. 9) the study focused on the in-series addition of new sarcomeres at the ends of the pre-existing myofibrils (i.e., it studied in-series sarcomerogenesis). In our opinion, the study does not provide any direct evidence of myofibrillogenesis, and we are not aware of any studies that have shown that the chronic stretch model employed by the authors induces myofibrillogenesis. However, numerous studies have shown that chronic stretch leads to the in-series addition of new sarcomeres.

3) Is there evidence for myofbrillogenesis during cardiac hypertrophy that could be referenced here?

This is a great question, and one would think that it would have been widely investigated. However, direct evidence for myofibrillogenesis during load-induced cardiac hypertrophy is just as sparse as the evidence for myofibrillogenesis during load-induced skeletal muscle hypertrophy.

4) In the introduction, perhaps mention that prolonged fixation is another disadvantage of EM tissue preparation. This typically prevents the usage of antibodies afterwards, whereas the authors have been able to overcome this using their method, which is a great strength.

Thank you for the suggestion. This point has been added the 5th paragraph of the introduction.

5) In the introduction, are there not EM-compatible computer programs that could sidestep the manual tracing and increase throughput? Why could software such as this not be used? https://www.nature.com/articles/s41592-019-0396-9

While we agree that automated pipelines have been developed for EM, such methods require a high degree of contrast between the measured objects. With EM, the high degree of contrast required for automated quantification is rarely observed between the myofibrils and the intermyofibrillar components (especially in glycolytic fibers). Moreover, one of the primary goals of our study was to develop a time and cost-effective method for identifying and quantifying myofibrils. As such, we developed a method that would not require the use of EM. We only incorporated EM imaging and analysis to validate the FIM-ID method. Therefore, utilizing an EM-compatible program to sidestep the manual tracing would have sped up the validation step, but it would not have accomplished one of the primary goals of our study.

6) In the results, specifically for the human specimens, were "hybrid" fibers detected and, if so, how did the pattern of SERCA look? Also, did the authors happen to notice centrallynucleated muscle fibers in the murine plantaris after overload? If so, how did the myofibrils look? Could be interesting.

For the analysis of the human fibers, two distinct immunolabeling methods were performed. One set of sections was stained for SERCA1 and dystrophin, while the other set was stained for SERCA2 and dystrophin. In other words, we did not perform dual immunolabeling for SERCA1 and SERCA2 on the same sections. Therefore, during the analysis of the human fibers, we did not detect the presence of hybrid fibers. Furthermore, while we did not perform nuclear staining on these sections, it should be noted that nuclei do not contain SERCA, and to the best of our recollection, we did not detect any SERCAnull objects within the center of the fibers. Moreover, our previous work has shown that the model of MOV used in this study does not lead to signs of degeneration/regeneration (You, Jae-Sung et al. (2019). doi:10.1096/fj.201801653RR). Therefore, it can be safely assumed that very few (if any) of the fibers analyzed in this study were centrally nucleated.

7) In the Results, fixed for how long? This is important since, at least in my experience, with 24+ hours of fixation, antibody reactivity is significantly reduced unless an antigen retrieval step is performed (even then, not always successful). Also, presumably these tissues were drop-fixed? These details are in the Methods but some additional detail here could be warranted for the benefit of the discerning and interested reader.

For both the mouse and human, the samples were immersion-fixed (presumably the equivalent of “drop-fixed”) in 4% paraformaldehyde in 0.1M phosphate buffer solution for a total of 24 hours (as described in the Methods section). We agree that prolonged aldehyde fixation can affect antibody reactivity; however, the antibodies used for FIM-ID did not require an antigen retrieval step.

8) In the results regarding NADH/FAD autofluorescence imaging, a complimentary approach in muscle was recently described and could be cited here: https://journals.physiology.org/doi/full/10.1152/japplphysiol.00662.2022

We appreciate the reviewer’s recommendation to add this citation for the support of our method for fiber type classification and have added it to the manuscript in the second paragraph under the “Further refinement and validation of the automated measurements with FIM-ID” subsection of the Results as citation number 57.

9) In the results, "Moreover, no significant differences in the mean number of myofibrils per fiber CSA were found when the results from the FIM-ID and EM-based measurements were directly compared, and this point was true when the data from all analyzed fibers was considered..." Nit-picky, but should it be "were considered" since data is plural?

Thanks, this error was corrected.

10) In the discussion, are the authors developing a "methodology" or a "method"? I think it may be the latter.

We agree that “method” is the correct term to use. Instances of the word “methodology” have been replaced with “method.”

11) In the discussion, since the same fibers were not being tracked over time, I'm not sure that saying "radial growth" is strictly correct. It is intuitive that the fibers were growing during loading, of course, but it may be safer to say "larger fibers versus control or the Pre sample" or something of the like. For example, "all the fiber types that were larger after loading versus controls" as opposed to "showed significant radial growth"

While we agree that the fiber size was not tracked over time, the experiments were designed to test for a main effect of mechanical loading. Therefore, we are attributing the morphological adaptations to the mechanical loading variable (i.e., mechanical loadinduced growth). The use of terms like “the induction of radial growth” or “the induction of hypertrophy” are commonly used in studies with the methods employed in this study. Respectfully, we believe that it would be more confusing for the readers if we used the suggested terms like "all the fiber types that were larger after loading versus controls". For instance, if I were the reader I would think to myself… but there fiber types that were larger than others before loading (e.g., Ox vs. Gly), so what are the authors really trying to talk about?

12) I would suggest making a cartoon summary figure to complement and summarize the Methods/Results/Discussion

Thank you for this suggestion. We created a cartoon that summarizes the overall workflow for FIM-ID and this cartoon is now presented in Supplemental Figure 1.

Reviewer #1 (Public Review):

Summary:<br /> Using a state-of-the-art image analysis pipeline the authors report that muscle cell hypertrophy in mice and humans occurs primarily through an increase in the number of myofibrils (myofibrillogenesis) and not myofibril hypertrophy.

Strengths:<br /> A strength of the study is the development and validation of an automated image analysis pipeline to quantify myofibril size and abundance in mouse and human muscle cells. In addition to the pipeline, which requires relatively readily available microscopy equipment (an additional strength) is the development of a methodology to optimally prepare muscle samples for high-resolution imaging.

Weaknesses:<br /> A weakness of the study was that only one time-point was assessed during hypertrophy. As mentioned by the authors, this precluded an assessment of the myofibril splitting mechanism.

Reviewer #2 (Public Review):

Summary:<br /> In this work, the authors sought to 1) establish a method for measuring muscle fiber subcellular structure (myofibrils) using common, non-specialized laboratory techniques and equipment, and 2) use this method to provide evidence on whether loading-induced muscle fiber growth was the result of myofibril growth (of existing myofibrils) or myofbrillogenesis (creation of new myofibrils) in mice and humans. The latter is a fundamental question in the muscle field. The authors succeeded in their aims and provided useful methods for the muscle field and detailed insight into muscle fiber hypertrophy; specifically, that loading-induced muscle fiber hypertrophy may be driven mostly by myofibrillogenesis.

Strengths:<br /> 1) The usage of murine and human samples to provide evidence on myofibril hypertrophy vs myofibrillogenesis.<br /> 2) A nice historical perspective on myofibrillogenesis in skeletal muscle.<br /> 3) The description of a useful and tractable IHC imaging method for the muscle biology field supported by extensive validation against electron microscopy.<br /> 4) Fundamental information on how myofiber hypertrophy ensues.

Weaknesses:

- The usage of young growing mice (8-10 weeks) versus adult mice (>4 months) in the murine mechanical overload experiments, as well as no consideration for biological sex. The former point is partly curtailed by the adult human data that is provided (male only). Still, the usage of adult mice would be preferable for these experiments given that maturational growth may somehow affect the outcomes. For the latter point, it is not clear whether male or female mice were used.

Reviewer #3 (Public Review):

Summary:<br /> Radial muscle growth involves an increase in overall muscle cross-sectional area. For decades this process has been described as the splitting of myofibrils to produce more myofibrils during the growth process. However, a closer look at the original papers shows that the evidence underlying this description was incomplete. In this paper, the authors have developed a novel method using fluorescence microscopy to directly measure myofibril size and number. Using a mouse model of mechanical loading and a human model of resistance exercise they discovered that myofibrillogenesis is playing a key role in the radial growth of muscle fibers.

Strengths:<br /> 1. Well-written and clear description of hypothesis, background, and experiments.<br /> 2. Compelling series of experiments.<br /> 3. Different approaches to test the hypothesis.<br /> 4. Rigorous study design.<br /> 5. Clear interpretation of results.<br /> 6. Novel findings that will be beneficial to the muscle biology field.<br /> 7. Innovative microscopy methods that should be widely available for use in other muscle biology labs.

eLife assessment

This landmark study presents MetaPathPredict, a method that uses a stacked ensemble of neural networks to predict the presence or absence of KEGG modules based on annotated features in the genome. The evidence supporting the conclusions is compelling, with a tool that allows for prediction of KEGG modules in sparse gene sequence datasets.

Reviewer #1 (Public Review):

The authors are presenting a new algorithm applying machine learning to determine the presence or absence of KEGG metabolic modules in microbial genomes. Specifically, they aim to make these predictions in incomplete genomes, like those you will see from assembly and binning of metagenomic reads. This is a significant problem and challenge in the bioinformatics and computational biology community, and as such, this work is a substantial step forward. A key aspect of this, which the authors themselves aptly demonstrate in their results is the ability of machine learning to judge the likelihood of a KEGG module being present based on all gene annotations and not just those genes in the module. The yields significantly greater results compared with approaches that rely solely on genes within the pathway.

Reviewer #2 (Public Review):

The authors introduce MetaPathPredict, a method that infers the presence of functional units of gene sets, such as a set of genes coding enzymes for a common metabolic pathway, from a pool of genes or genetic sequences. MetaPathPredict employs a stacked ensemble of neural networks, each trained for a specific pathway, to consider mutual information between pathways.

In predicting the presence of metabolic pathways in incomplete genomes, MetaPathPredict outperforms alternative naive classifiers and single neural network methods. These results demonstrate the effectiveness of a stacked ensemble of neural networks in exploiting mutual information between metabolic pathways.

eLife assessment

In this important study, the authors explore the importance of developmental changes in cortico-DRN innervation in the balance of behavioral control in a foraging task. The authors report somewhat convincing evidence that while juvenile mice and adult mice both perform the task, juveniles exhibit more impulsive behavior due to reduced efficacy of cortico-DRN projections. The authors conclude that the development of cortico-DRN (esp mPFC) projections allows 5HT input to promote perseveration (or exploitation) in the balance of behavioral control. However, reviewers raised issues regarding the strength of the evidence without further experiments.

Reviewer #1 (Public Review):

This study is founded on the idea that 5HT promotes waiting, and tests a clear, and I think novel, hypothesis that input from cortical and particularly prefrontal areas is key to promoting this and that the increase in this relates to declines in impulsive behavior during adolescence. It also nicely tests that hypothesis with integrated behavioral, electrophysiological, and tracing approaches. Overall it makes a compelling argument in favor of the authors ideas. The independent findings also build upon or at least are well supported by prior work, which I think is excellent and increases confidence in the conclusions.

Reviewer #3 (Public Review):

Studying the late development of neural circuits in relation to developmental changes in behaviour is clearly of great interest, particularly during the period of adolescence when a number of developmental abnormalities can be revealed. This is however not an easy task, since there are many concurrent changes that occur simultaneously during this developmental making it difficult to establish causality rather than correlation.

The study focuses on behavioural and circuit changes that occur between juvenile and adulthood focusing in the prefrontal cortex and on its descending projections to the brainstem raphe nuclei. Because the pathway from the frontal cortex to serotonin raphe neurons has been involved in behavioural and stress control, exerting a top-down control on impulsive behavior, there is a good justification to focus on the development of this pathway during a period that is thought to correspond to adolescence.

The authors identified a behavioral change in foraging strategy, which they term persistence. They find that adults tend to be more persistent than juveniles in an exploration for reward. To analyse the maturation of the prefrontal to raphe circuit they use a genetic approach (the Rbp4 promoter which drives expression in layer 5 cortical neurons) recording the synaptic drive elicited by stimulation of the axons arriving into the raphe area. They find that this maturation starts very late in the late adolescent period. They then study the effects of ablation of the layer 5 Rbp4 neurons in adults and find that adult animals have a behavior that is more similar to that of the juveniles. They then conclude that cortical prefrontal projections to the raphe are involved in the control of this behavior.

The study is interesting in showing this new behavioural test quantifying developmental changes in exploratory behavior and indicating that some pathways derived mainly from the frontal cortex continue to mature late. However, there are a number of issues regarding the specificity of the genetic approach used. This makes it difficult to be convinced that the behaviour is related to changes in the cortico-raphe circuit.

eLife assessment

Using single-cell sequencing, high-resolution imaging, and inducible genetic deletion of yolk-sac (YS) derived macrophages, the authors present a useful map of fetal liver macrophage subpopulations and provide important data demonstrating that heterogeneous fetal liver macrophages regulate erythrocyte enucleation, interact physically with fetal HSCs, and may regulate neutrophil accumulation in the fetal liver. These novel findings, although yet incomplete, might provide a solid foundation for further investigating the effects of macrophages on HSC function during fetal hematopoiesis and into adulthood and will be useful for the field of macrophage biology and developmental hematopoiesis.

Reviewer #1 (Public Review):

This manuscript from Kavanjoo et al examines the role of macrophages within the fetal liver beyond erythrocyte maturation. Using single-cell sequencing, high-resolution imaging, and inducible genetic deletion of yolk-sac (YS) derived macrophages, the authors demonstrate that heterogeneous fetal liver macrophages regulate erythrocyte enucleation, interact physically with fetal HSCs, and may regulate neutrophil accumulation in the fetal liver. The data as presented do not strongly support the authors' conclusion that fetal macrophages in the liver regulate the HSC niche or granulopoiesis from HSCs.

Fetal-derived resident tissue macrophages are increasingly implicated in regulation of adult tissue function and homeostasis, but considerably less is known regarding the function of fetal macrophages during development. Macrophages in the fetal liver have been shown to form erythroblastic islands, where they regulate erythrocyte maturation. Here, the authors performed single-cell sequencing on fetal liver macrophages (Cd11b-lo) to gain insight into heterogeneity and utilized previously published pre-Mac signatures from the YS to focus on YS-derived macrophages. These clusters were then further cross-referenced with surface protein expression as determined by multidimensional flow cytometry to hone in on a very specific subset of three groups of F4/80hi macrophages defined by multiple surface markers. Fate-mapping with three models (Tnfrsf11a-Cre - YS pMAC derived; Ms4a3Cre - FL monocyte derived; CXCR4-Cre-ERT2 - definitive HSC derived) revealed that three major subsets are all derived from YS pMACs. However, the relative frequencies of these specific populations are not shown, and because the single sequencing analysis goes through so many iterations of re-clustering that initiates by focusing specifically on pMAC signatures, this result is not surprising.

Probing gene expression within each of the three clusters revealed ligand expression suggesting cell-cell interactions, and cross-referencing with a fetal LT-HSC gene expression dataset revealed potential receptor-ligand interactions. Microscopic investigation of physical interactions between specific macrophage subsets and HSCs was not particularly convincing. In Figure 3C, for example, Cluster C is very difficult to visualize. It would again be helpful to know what the ratios are within the FL for each cluster. Data in Figure 3F are not well represented by Data in Figure 3E.

Furthermore, deletion of YS pMAC-derived macrophages the Tnfrsf11a-Cre X Spi1fl/fl resulted in broad macrophage depletion - although the authors did not demonstrate this using the carefully refined phenotypes they had defined earlier in the manuscript. Nonetheless, the authors demonstrate that macrophage depletion did affect erythroid enucleation, as expected, and the authors also showed some effect of macrophage deletion on LT-HSC gene expression by bulk transcription analysis. These effects were relatively small, however, and this was clear in the absence of effects on hematopoiesis in vivo or HSC proliferation ex vivo. To further investigate the effects of macrophage deletion on downstream hematopoieisis, the authors re-assessed the myeloid compartment following macrophage deletion, and identified and specifically focused on an observed increase in neutrophils in response to macrophage depletion. Based on this increase, they tested HSC differentiation using a colony-forming assay, which shows a slight increase in GM colonies that is also reflective of a slight but insignificant increase in total colony forming capability. The authors concluded that loss of fetal macrophages causes a reprogramming of HSCs to the granulocytic lineage. However, the colony-forming assay and subtle differences in gene expression are not sufficient to conclude that fetal HSCs have been reprogrammed towards granulocytic lineage by macrophage deletion.

Overall, there are some interesting pieces of data in this manuscript, including the classification of new subsets of macrophages in the liver, their fate-mapping to the YS, and gene expression analysis. However, the data as presented do not strongly support a role for these particular macrophage subsets in regulating HSCs or fetal hematopoiesis within the fetal liver niche. Although there may be specific subsets of fetal liver macrophages that more closely physically interact with HSCs, deletion of what appeared to be a vast majority of macrophages in the FL did not appear to affect cellularity of hematopoietic stem and progenitor cells in vivo, and was not shown to convincingly affect HSC function. The mechanism by which macrophage deletion affected granulopoiesis could be independent from HSCs, and would be interesting to further explore.

Reviewer #2 (Public Review):

Using a single-cell omics approach combined with spatial proteomics and genetic fate mapping, Kayvanjoo et al found that fetal liver (FL) macrophages cluster into distinct yolk sac-derived subpopulations and that some of the HSCs in FL preferentially associate with one of the identified macrophage subpopulations. FLs lacking macrophages show a delay in erythropoiesis. The authors also try to identify a role of macrophages for HSCs function in FL, and claim that macrophages affect myeloid differentiation of HSCs. Experimental support for the function of macrophages on HSCs remains weak. Taken together, their data provide a precise map of FL macrophage subpopulations, which is novel and will serve the field well.

eLife assessment

The findings are important and would potentially have theoretical and practical implications outside the field. However the strength of evidence presented was assessed as being incomplete in several respects. Major strengths are (1) genetic factors in facial appearance are of broad interest, and the potential influence of possibly identical factors in a serious congenital disorder (cleft lip/palate) heightens that interest further; (2) proving which single nucleotide variants influence phenotypes, and by what mechanisms, is a major challenge for the field as a whole. The weakness, as assessed, was that in its present form the experimental approach was not sufficiently rigorous to support the conclusions unambiguously.

Reviewer #1 (Public Review):

The authors begin by showing the association between rs6740960 and facial shape, specifically that protrusion of the lower jaw and zygomatic regions, and retrusion of the entire central midface, are associated with the 'T' allele. Next they show that the enhancer harboring the SNP is active in the midface of mouse embryos with lacz transgenic reporter assays. Then they show that, interestingly, while the enhancer harboring the SNP has comparable levels of H3K27Ac in hESC derived CNCC (eCNCC) and cranial chondrocytes (eCC), only in the latter there is significant level of contact between the enhancer and the promoter of PKDCC. Next, they delete the rs6740960 cognate enhancer in two heterozygous clones and demonstrate 60% decrease in PKDCC expression at the allele bearing the enhancer deletion. This is an elegant and satisfying experiment. Next, they use ChIP-qPCR to H3K27Ac in eCNCC and eCC that are heterozygous for the SNP and show an elevated level of H3K27Ac the enhancer haplotype bearing the derived "A" allele in CNCCs and even greater in CC. This is also a clear result, although because of co-operativity among enhancers, there could be another SNP in the haplotype that leads to the difference. Finally they use micro-CT and high end morphometric analysis on mice with two, one, or zero functional Pkdcc alleles, and see correlated quantitative changes in maxilla, mandible, and palatine bone shape. Strengths of the study include analysis of allele specific expression using digital PCR, quantitative H3K27Ac-HiC, showing the SNP allele correlates with the activity of the enhancer harboring it, and a deep morphometric analysis to show the subtle effect of loss of one allele of Pkdcc on craniofacial structures in mouse model. However, no experiments incisively rule out the possibility that another SNP in the haplotype cause the effects attributed to the SNP, slightly diminishing the impact of the study.

Reviewer #2 (Public Review):

The Authors demonstrate compelling genetic evidence that the region that harbors rs6740960 plays a role in both normal craniofacial development risk for craniofacial disease. They show strong evidence that the conserved element harboring this variant is tested for LacZ reporter activity in the developing mouse that is has activity in relevant tissues. They perform several assays to demonstrate a physical link between this enhancer region to a specific target gene, PKDCC, in both cranial neural crest cells and differentiated chondrocytes. Removal of a single copy of the enhancer has little effect on PKDCC expression in CNCCs but strong impacts in chondryocytes. H1 derived cells that are heterozygous at the variant above show strong bias in H3K27ac signals in chondrocytes. The researchers then go on to recharacterize a PKDCC knockout mouse to show that it has craniofacial defects. They use modern micro-CT and analysis techniques to demonstrate subtle changes in jaw and skull structure in PKDCC heterozygous mice and confirm many of the phenotypes that were described by Kinoshita et al 2009. Overall these results point to dosage of PKDCC in craniofacial development with changes in skull shape and susceptibility to orofacial clefting. However the epigenomic differences presented in Figure 2B that serve as the foundation for the rest of the work do not agree with previously published work by this group (Prescot et al 2015). The researchers claim "enrichment of the coactivator p300 and of the active chromatin mark H3K27ac at this region is higher in the chimpanzee CNCCs as compared to human, suggesting that this non-coding element may have higher regulatory activity in the chimp. However this region was not identified in the top 1000 biased enhancer regions provided in the supplement of the Prescott et al 2015 paper. The authors do not indicate any statistical significance and largely rely on signal tracks that have not been corrected for input controls to make this conclusion. The in vivo assay for enhancer activity while excellent at demonstrating where an enhancer can be active is not well suited to quantitative comparisons. Furthermore the researchers claim that the mouse orthologous sequence is not active in the assay despite strong H3K27ac and other enhancer related signals in developing mouse craniofacial tissues as available from the Mouse Encode Project. This calls into questions whether this assay is informative at all if the native sequence which shows functionally conserved activity is not active in the mouse embryo. Lastly the authors only consider this region as a potential enhancer and not any other type of regulatory sequence. GENCODE gene annotations demonstrate a potential lncRNA (LINC02898 /ENST00000378711.2) that is directly adjacent to the region marked by this variant. This could be a promoter for an RNA that regulates PKDCC in cis. Inspection of gene expression data from a recent preprint Yankee et al 2022 as well as Prescot et al data available from the recount3 database indeed indicate RNA signal from both CNCCs and primary human tissue consistent with this annotation. The Mundlos lab has demonstrated similar regulatory mechanisms through lncRNA Maenli at the En1 locus that result in limb abnormalities.

Reviewer #3 (Public Review):

Mohammed et al perform functional follow-up studies on the single nucleotide polymorphism rs6740960 located on chromosome 2p21 that was previously linked to lower jaw and chin shape variation and an increased risk of non-syndromic orofacial clefting. Through a combination of in silico multi-species alignment, in vitro enhancer marks, and finally in vivo data the team could confirm that the SNP is located in an active enhancer element driving transgene expression in the upper and lower jaw. The team tested the human and chimp orthologs in transgenic mice. Interestingly the mouse ought to look did not show any active enhancer activity in the LacZ reporter assay. Next, the authors could show a selective interaction of the enhancer element with the neighboring gene PKDCC in chondrocytes using H3K27ac HiChIP. Deletion of this enhancer in vitro led to an allele specific reduction of PKC expression. Finally, the authors aimed at evaluating the effect of rs6740960 in vivo using a mouse model. Since the enhancer sequence of the mouse did not show any positive reporter activity, the authors decided to use previously described Pkdcc full knockout mouse model (Kinoshita et al. 2009). Using sophisticated imaging technologies the authors were able to show that in mice several facial bones are Pkdcc dose sensitive.

Overall this is an extremely exciting manuscript that addresses one of the key challenges in the post GWAS time: the functional connection of lead SNPs to their target genes and a detailed evaluation of the biological and morphological consequences.<br /> The manuscript is well written, and the conclusions are completely supported by the evidence provided. I really think this is a great paper, however I have several major concerns with the manuscript and its current format.

Major comments:

1: My main concern about the manuscript in its current format is the disconnection between the beautiful work of linking rs6740960 to Pkdcc in the first part of the manuscript and the investigation of dose sensitivity of Pkdcc itself in end of the manuscript. While I realized that this is because the enhancer itself is not conserved between humans and mice, in my opinion it still weakens the novelty of the finding of the second part of the manuscript quite significantly. The Pkdcc knockout has been well described and that the authors now present evidence that also heterozygous knockouts show a minimal phenotype in the facial bones is really not surprising. More importantly it doesn't show how the rs6740960 influences Pkdcc expression in vivo.

A rather straightforward and very interesting experimental approach would be to replace the mouse enhancer sequence with the human or chimp enhancer carrying the risk allele or the wild type. In the last figure the authors have nicely shown that the entire experimental setup for the functional analysis of even minor changes to the facial bones caused by the SNP are available to the team. Even if the result was negative this experiment would significantly enhance the scientific impact of the paper.

2: Another option would be to repeat the LacZ reporter essay with the human wild type and the risk allele in direct comparison. A beautiful example of such an experiment was recently shown by Yanchuset et al (A noncoding single-nucleotide polymorphism at 8q24 drives IDH1-mutant glioma formation, Yanchuset al.,Science378,68-78 2022)

3: It is unclear how the H3K27ac HiChIP signal looks like at the Pkdcc locus in H9 ESC. What is the naïve interaction profile?

Reviewer #2 (Public Review):

Summary:<br /> Verma et al. provide a short technical report showing that endogenously tagged dynein and dynactin molecules localize to growing microtubule plus-ends and also move processively along microtubules in cells. The data are convincing, and the imaging and movies very nicely demonstrate their claims. I don't have any large technical concerns about the work. It is perhaps not surprising that dynein-dynactin complexes behave this way in cells due to other reports on the topic, but the current data are among some of the nicest direct demonstrations of this phenomenon. It may be somewhat controversial since a separate group has reported that dynein does not move processively in mammalian cells (https://www.biorxiv.org/content/10.1101/2021.04.05.438428v3). Because of this, it might be nice for the authors to comment on this discrepancy in the field, although the aforementioned work is still in pre-print form.

Strengths:<br /> Using state-of-the-art methods to endogenously tag dynein/dynactin subunits and performing live-cell imaging is convincing and useful for the field.

Weaknesses:<br /> The claims are perhaps not surprising or novel given the extensive data already published in the field. However, there aren't many similar studies using endogenously tagged subunits to date.

eLife assessment

In their short technical report, Verma et al. describe how endogenously-tagged dynein and dynactin molecules localize to growing microtubule plus-ends and move processively along microtubules in cells. The authors present solid evidence that cytoplasmic dynein is a processive motor that takes long excursions prior to dissociating from microtubules. However, there are concerns about the robustness of the imaging and analysis protocols, which should be more clearly defined. This is a useful study that will be of interest to cell biologists and biochemists in the motor protein field.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript by Verma et al. is a simple and concise assessment of the in-cell motility parameters of cytoplasmic dynein. Although numerous studies have focused on understanding the mechanism by which dynein is activated using a complement of in vitro methodologies, an assessment of dynein motility in cells has been lacking. It has been unclear whether dynein exhibits high processivity within the crowded and complicated environment of the cell. For example, does cargo-bound dynein exhibit short, non-processive motility (as has been recently suggested; Tirumala et al., 2022 bioRxiv)? Does cargo-bound dynein move against opposing forces generated by cargo-bound kinesins? Do cargoes exhibit bidirectional switching due to stochastic activation of kinesins and dyneins? The current work addresses these questions quite simply by observing and quantitating the motility of natively tagged dynein in HeLa cells.

Strengths:<br /> The work uses a simple and straightforward approach to address the question at hand: is dynein a processive motor in cells? Using a combination of TIRF and spinning disc confocal microscopy, the authors provide a clear and unambiguous answer to this question.

Weaknesses:<br /> My only significant concern (which is quite minor) is that the authors focus their analysis on dynein movement in cells treated with docetaxol, which could potentially affect the observed behavior. However, this is likely necessary, as without it, motility would not have been observed due to the 'messiness' of dynein localization in a typical cell (e.g., plus end-tracking in addition to cargo transport).

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, Verma et al. set out to visualize cytoplasmic dynein in living cells and describe their behaviour. They first generated heterozygous CRISPR-Cas9 knock-ins of DHC1 and p50 subunit of dynactin and used spinning disk confocal microscopy and TIRF microscopy to visualize these EGFP-tagged molecules. They describe robust localization and movement of DHC and p50 at the plus tips of MTs, which was abrogated using SiR tubulin to visualize the pool of DHC and p50 on the MTs. These DHC and p50 punctae on the MTs showed similar, highly processive movement on MTs. Based on comparison to inducible EGFP-tagged kinesin-1 intensity in Drosophila S2 cells, the authors concluded that the DHC and p50 punctae visualized represented 1 DHC-EGFP dimer+1 untagged DHC dimer and 1 p50-EGFP+3 untagged p50 molecules.

Strengths:<br /> The idea and motivation behind this work are commendable.

Weaknesses:<br /> There are several major issues with the characterization of the knock-in lines generated, the choice of imaging and analysis methods, and inadequate discussion of prior findings.

The specific points are below:

1. CRISPR-edited HeLa clones:<br /> (i) The authors indicate that both the DHC-EGFP and p50-EGFP lines are heterozygous and that the level of DHC-EGFP was not measured due to technical difficulties. However, quantification of the relative amounts of untagged and tagged DHC needs to be performed - either using Western blot, immunofluorescence or qPCR comparing the parent cell line and the cell lines used in this work.<br /> (ii) The localization of DHC predominantly at the plus tips (Fig. 1A) is at odds with other work where endogenous or close-to-endogenous levels of DHC were visualized in HeLa cells and other non-polarized cells like HEK293, A-431 and U-251MG (e.g.: OpenCell (https://opencell.czbiohub.org/target/CID001880), Human Protein Atlas (https://www.proteinatlas.org/ENSG00000197102-DYNC1H1/subcellular#human), https://www.biorxiv.org/content/10.1101/2021.04.05.438428v3). The authors should perform immunofluorescence of DHC in the parental cells and DHC-EGFP cells to confirm there are no expression artifacts in the latter. Additionally, a comparison of the colocalization of DHC with EB1 in the parental and DHC-EGFP and p50-EGFP lines would be good to confirm MT plus-tip localisation of DHC in both lines.<br /> (iii) It would also be useful to see entire fields of view of cells expressing DHC-EGFP and p50-EGFP (e.g. in Spinning Disk microscopy) to understand if there is heterogeneity in expression. Similarly, it would be useful to report the relative levels of expression of EGFP (by measuring the total intensity of EGFP fluorescence per cell) in those cells employed for the analysis in the manuscript.<br /> (iv) Given that the authors suspect there is differential gene regulation in their CRISPR-edited lines, it cannot be concluded that the DHC-EGFP and p50-EGFP punctae tracked are functional and not piggybacking on untagged proteins. The authors could use the FKBP part of the FKBP-EGFP tag to perform knock-sideways of the DHC and p50 to the plasma membrane and confirm abrogation of dynein activity by visualizing known dynein targets such as the Golgi (Golgi should disperse following recruitment of EGFP-tagged DHC-EGFP or p50-EGFP to the PM), or EGF (movement towards the cell center should cease).

2. TIFRM and analysis:<br /> (i) What was the rationale for using TIRFM given its limitation of visualization at/near the plasma membrane? Are the authors confident they are in TIRF mode and not HILO, which would fit with the representative images shown in the manuscript?<br /> (ii) At what depth are the authors imaging DHC-EGFP and p50-EGFP?<br /> (iii) The authors rely on manual inspection of tracks before analyzing them in kymographs - this is not rigorous and is prone to bias. They should instead track the molecules using single particle tracking tools (eg. TrackMate/uTrack), and use these traces to then quantify the displacement, velocity, and run-time.<br /> (iv) It is unclear how the tracks that were eventually used in the quantification were chosen. Are they representative of the kind of movements seen? Kymographs of dynein movement along an entire MT/cell needs to be shown and all punctae that appear on MTs need to be tracked, and their movement quantified.<br /> (v) What is the directionality of the moving punctae?<br /> (vi) Since all the quantification was performed on SiR tubulin-treated cells, it is unclear if the behavior of dynein observed here reflects the behavior of dynein in untreated cells. Analysis of untreated cells is required.

3. Estimation of stoichiometry of DHC and p50<br /> Given that the punctae of DHC-EGFP and p50 seemingly bleach on MT before the end of the movie, the authors should use photobleaching to estimate the number of molecules in their punctae, either by simple counting the number of bleaching steps or by measuring single-step sizes and estimating the number of molecules from the intensity of punctae in the first frame.

4. Discussion of prior literature<br /> Recent work visualizing the behavior of dyneins in HeLa cells (DOI: 10.1101/2021.04.05.438428), which shows results that do not align with observations in this manuscript, has not been discussed. These contradictory findings need to be discussed, and a more objective assessment of the literature in general needs to be undertaken.

eLife assessment

The important study uses a new experimental method to provide compelling evidence on how sense- and anti-sense transcription is differentially regulated. The method described here can generally be used to study the alterations in transcription. This paper will be of interest to scientists working in the gene regulation community.

Reviewer #1 (Public Review):

Summary:<br /> In this manuscript, Eaton et al. examine the regulation of transcription directionality using a powerful genomic approach (more about the methodology below). Their data challenge the notion that the polyadenylation signal-reading Cleavage and Polyadenylation (CPA) complex is responsible for controlling promoter directionality by terminating antisense transcription. Namely, depletion of the required CPA factor RBBP6 has little effect on antisense transcription measured by POINT. They find instead that initiation is intrinsically preferential in the sense direction and additionally maintained by the activities of an alternative processing complex called Integrator, together with the kinase CDK9. In the presence of CDK9 activity, depletion of Integrator endoribonuclease INTS11 leads to globally increased transcription in the antisense direction, and minor effects in the sense direction. However, CDK9 inhibition reveals that sense transcription is also sensitive to INS11 depletion. The authors suggest that CDK9 activity is stronger in the sense direction, preventing INTS11-mediated premature termination of sense transcrpts.

Strengths:<br /> The combination of acute depletion of the studied factors using degron approaches (important to limit possible secondary effects), together with novel and very sensitive nascent transcriptomics methods POINT and sPOINT is very powerful. The applied spike-in normalization means the analysis is more rigorous than most. Using this methodology allowed the authors to revisit the interesting question of how promoter/transcription directionality is determined.

The data quality appears very good and the fact that both global analysis as well as numerous gene-specific examples are shown makes it convincing.

The manuscript is well written and hence a pleasure to read.

Weaknesses:<br /> I am slightly worried about the reproducibility of the data - it is unclear to me from the manuscript if and which experiments were performed in replicate (lack of table with genomic experiments and GEO access, mentioned in more detail in below recommendations to authors), and the methods could be more detailed.

A separate discussion section would be useful, particularly since the data provided challenge some concepts in the field. How do the authors interpret U1 data from the Dreyfuss lab in light of their results? How about the known PAS-density directionality bias (more PAS present in antisense direction than in sense) - could the differential PAS density be still relevant to transcription directionality?

I find that the provided evidence for promoter directionality to be for the most part due to preferential initiation in the sense direction should be stressed more. This is in my eyes the strongest effect and is somehow brushed under the rug.

References 12-17 report an effect of Integrator on 5' of protein-coding genes, while data in Figure 2 appears contradictory. Then, experiments in Figure 4 show a global effect of INST11 depletion on promoter-proximal sense transcription. In my opinion, data from the 2.5h time-point of depletion should be shown alongside 1.5h in Figure 2 so that it is clear that the authors found an effect similar to the above references. I find the current presentation somehow misleading.

Conclusion/assessment:<br /> This important work substantially advances our understanding of the mechanisms governing the directionality of human promoters. The evidence supporting the claims of the authors is compelling, with among others the use of advanced nascent transcriptomics including spike-in normalization controls and acute protein depletion using degron approaches.

In my opinion, the authors' conclusions are in general well supported.

Not only the manuscript but also the data generated will be useful to the wide community of researchers studying transcriptional regulation. Also, the POINT-derived novel sPOINT method described here is very valuable and can positively impact work in the field.

Reviewer #2 (Public Review):

Summary:<br /> Eaton and colleagues use targeted protein degradation coupled with nascent transcription mapping to highlight a role for the integrator component INST11 in terminating antisense transcription. They find that upon inhibition of CDK9, INST11 can terminate both antisense and sense transcription - leading to a model whereby INST11 can terminate antisense transcription and the activity of CDK9 protects sense transcription from INST11-mediated termination. They further develop a new method called sPOINT which selectively amplifies nascent 5' capped RNAs and find that transcription initiation is more efficient in the sense direction than in the antisense direction. This is an excellent paper that uses elegant experimental design and innovative technologies to uncover a novel regulatory step in the control of transcriptional directionality.

Strengths:<br /> One of the major strengths of this work is that the authors endogenously tag two of their proteins of interest - RBBP6 and INST11. This tag allows them to rapidly degrade these proteins - increasing the likelihood that any effects they see are primary effects of protein depletion rather than secondary effects. Another strength of this work is that the authors immunoprecipitate RNAPII and sequence extracted full-length RNA (POINT-seq) allowing them to map nascent transcription. A technical advance from this work is the development of sPOINT which allows the selective amplification of 5' capped RNAs < 150 nucleotides, allowing the direction of transcription initiation to be resolved.

Weaknesses:<br /> While the authors provide strong evidence that INST11 and CDK9 play important roles in determining promoter directionality, their data suggests that when INST11 is degraded and CDK9 is inhibited there remains a bias in favour of sense transcription (Figures 4B and C). This suggests that there are other unknown factors that promote sense transcription over antisense transcription and future work could look to identify these.

Reviewer #3 (Public Review):

Summary:<br /> Using a protein degradation approach, Eaton et al show that INST11 can terminate the sense and anti-sense transcription but higher activity of CDK9 in the sense direction protects it from INS11-dependent termination. They developed sPOINT-seq that detects nascent 5'-capped RNA. The technique allowed them to reveal robust transcription initiation of sense-RNA as compared to anti-sense.

Strengths:<br /> The strength of the paper is the acute degradation of proteins, eliminating the off-target effects. Further, the paper uses elegant approaches such as POINT and sPOINT-seq to measure nascent RNA and 5'-capped short RNA. Together, the combination of these three allowed the authors to make clean interpretations of data.

Weaknesses:<br /> While the manuscript is well written, the details on the panel are not sufficient. The methods could be elaborated to aid understanding. Additional discussion on howthe authors' findings contradict the existing model of anti-sense transcription termination should be added.

eLife assessment

The authors report a previously published method ReplicaDock to improve predictions from AlphaFold-multimer (AFm) for protein docking studies. The level of improvement is modest for cases where AFm is successful; for cases where AFm is not as successful, the improvement is more significant, although the accuracy of prediction is also notably lower. Therefore, the evidence for the ReplicaDock approach being more predictive than AFm is solid for some cases (e.g., the antibody-antigen test case) but incomplete for the more extensive test sets (e.g., those presented in Figure 6). Overall, the study makes a valuable contribution by combining data- and physics-driven approaches.

Reviewer #1 (Public Review):

Summary:<br /> The authors wanted to use AlphaFold-multimer (AFm) predictions to reduce the challenge of physics-based protein-protein docking.

Strengths:<br /> They found that two features of AFm predictions are very useful. 1) pLLDT is predictive of flexible residues, which they could target for conformational sampling during docking; 2) the interface-pLLDT score is predictive of the quality of AFm predictions, which allows the authors to decide whether to do local or global docking.

Weaknesses:<br /> 1) As admitted by the authors, the AFm predictions for the main dataset are undoubtedly biased because these structures were used for AFm training. Could the authors find a way to assess the extent of this bias?<br /> 2) For the CASP15 targets where this bias is absent, the presentation was very brief. In particular, it would be interesting to see how AFm helped with the docking. The authors may even want to do a direct comparison with docking results without the help of AFm.

Reviewer #2 (Public Review):

Summary:<br /> In short, this paper uses a previously published method, ReplicaDock, to improve predictions from AlphaFold-multimer. The method generated about 25% more acceptable predictions than AFm, but more important is improving an Antibody-antigen set, where more than 50% of the models become improved.

When looking at the results in more detail, it is clear that for the models where the AFm models are good, the improvement is modest (or not at all). See, for instance, the blue dots in Figure 6. However, in the cases where AFm fails, the improvement is substantial (red dots in Figure 6), but no models reach a very high accuracy (Fnat ~0.5 compared to 0.8 for the good AFm models). So the paper could be summarized by claiming, "We apply ReplicaDock when AFm fails", instead of trying to sell the paper as an utterly novel pipeline. I must also say that I am surprised by the excellent performance of ReplicaDock - it seems to be a significant step ahead of other (not AlphaFold) docking methods, and from reading the original paper, that was unclear. Having a better benchmark of it alone (without AFm) would be very interesting.

These results also highlight several questions I try to describe in the weakness section below. In short, they boil down to the fact that the authors must show how good/bad ReplicaDock is at all targets (not only the ones where AFm fails. In addition, I have several more technical comments.

Strengths:<br /> Impressive increase in performance on AB-AG set (although a small set and no proteins).

Weaknesses:<br /> The presentation is a bit hard to follow. The authors mix several measures (Fnat, iRMS, RMSDbound, etc). In addition, it is not always clear what is shown. For instance, in Figure 1, is the RMSD calculated for a single chain or the entire protein? I would suggest that the author replace all these measures with two: TM-score when evaluating the quality of a single chain and DockQ when evaluating the results for docking. This would provide a clearer picture of the performance. This applies to most figures and tables. For instance, Figure 9 could be shown as a distribution of DockQ scores.

The improvements on the models where AFm is good are minimal (if at all), and it is unclear how global docking would perform on these targets, nor exactly why the plDDT<0.85 cutoff was chosen. To better understand the performance of ReplicaDock, the authors should therefore (i) run global and local docking on all targets and report the results, (ii) report the results if AlphaFold (not multimer) models of the chains were used as input to ReplicaDock (I would assume it is similar). These models can be downloaded from AlphaFoldDB.

Further, it would be interesting to see if ReplicaDock could be combined with AFsample (or any other model to generate structural diversity) to improve performance further.

The estimates of computing costs for the AFsample are incorrect (check what is presented in their paper). What are the computational costs for RepliaDock global docking?

It is unclear strictly what sequences were used as input to the modelling. The authors should use full-length UniProt sequences if they were not done.

The antibody-antigen dataset is small. It could easily be expanded to thousands of proteins. It would be interesting to know the performance of ReplicaDock on a more extensive set of Antibodies and nanobodies.

Using pLDDT on the interface region to identify good/bas models is likely suboptimal. It was acceptable (as a part of the score) for AlphaFold-2.0 (monomer), but AFm behaves differently. Here, AFm provides a direct score to evaluate the quality of the interaction (ipTM or Ranking Confidence). The authors should use these to separate good/bad models (for global/local docking), or at least show that these scores are less good than the one they used.

Author Response

The following is the authors’ response to the original reviews.

Reviewer #2 (Public Review):

Making state-of-the-art (super-resolution) microscopy widely available has been the subject of many publications in recent years as correctly referenced in the manuscript. By advocating the ideas of open-microscopy and trying to replace expensive, scientific-grade components such as lasers, cameras, objectives, and stages with cost-effective alternatives, interested researchers nowadays have a number of different frameworks to choose from. In the iteration of the theme presented here, the authors used the existing modular UC2 framework, which consists of 3D printable building blocks, and combined a cheapish laser, detector and x,y,(z) stage with expensive filters/dichroics and a very expensive high-end objective (>15k Euros). This particular choice raises a first technical question, to which extent a standard NA 1.3 oil immersion objective available for <1k would compare to the chosen NA 1.49 one.

Measurement of the illumination quality (e.g. the spectral purity) of low budget lasers convinced us of the necessity to use spectral filtering. These cannot be replaced with lower budget alternatives, to sill retain the necessary sensitivity to image single molecules. As expected, the high-quality objectives are able to produce high-quality data. Lower budget alternatives (<500 €) to replace the objective have been tried out. Image quality is reduced but key features in fluorescent images can be identified (see figure S1). The usage of a low budget objective for SMLM imaging is possible, but quality benchmarks such as identifying railroad tracks along microtubule profiles is not possible. Their usage is not optimal for applications aiming to visualize single molecules and might find better application in teaching projects.

The choice of using the UC2 framework has the advantage, that the individual building blocks can be 3D printed, although it should be mentioned that the authors used injection-molded blocks that will have a limited availability if not offered commercially by a third party. The strength of the manuscript is the tight integration of the hardware and the software (namely the implementations of imSwitch as a GUI to control data acquisition, OS SMLM algorithms for fast sub-pixel localisation and access to Napari).

The injection-molded cubes can be acquired through the OpenUC2 platform. Alternatively, the 3D printable version of the cubes is freely available and just requires the user to have a 3D printer. https://github.com/openUC2/UC2-GIT/tree/master/CAD/CUBE_EmptyTemplate

The presented experimental data is convincing, demonstrating (1) extended live cell imaging both using bright-field and fluorescence in the incubator, (2) single-particle tracking of quantum dots, and (3) and STORM measurements in cells stained against tubulin. In the following I will raise two aspects that currently limit the clarity and the potential impact of the manuscript.

First, the manuscript would benefit from further refinement. Elements in Figure 1d/e are not described properly. Figure 2c is not described in the caption. GPI-GFP is not introduced. MMS (moment scaling spectrum) could benefit from a one sentence description of what it actually is. In Figure 6, the size of the STORM and wide-field field of views are vastly different, the distances between the peaks on the tubuli are given in micrometers rather than nanometers. (more in the section on recommendations for the author)

Second, and this is the main criticism at this point, is that although all the information and data is openly available, it seems very difficult to actually build the setup due to a lack of proper documentation (as of early July 2023).

1) The bill of materials (https://github.com/openUC2/UC2-STORM-and-Fluorescence#bill-of-material) should provide a link to the commercially available items. Some items are named in German. Maybe split the BoM in commercially available and 3D printable parts (I first missed the option to scroll horizontally).

2) The links to the XY and Z stage refer to the general overview site of the UC2 project (https://github.com/openUC2/) requiring a deep dive to find the actual information.

3) Detailed building instructions are unfortunately missing. How to assemble the cubes (pCad files showing exploded views, for example)? Trouble shooting?

4) Some of the hardware details (e.g. which laser was being used, lenses, etc) should be mentioned in the manuscript (or SI)

I fully understand that providing such level of detail is very time consuming, but I hope that the authors will be able to address these shortcomings.

1) The bill of materials has been and will also in future still be improved. The items have been sorted into UC2 printed parts and externally acquired parts. The combination of part name as well as provider enables users to find and acquire the same parts. Additionally, depending on the country where the user is located, different providers of a given part might be advantageous as delivery means and costs might vary.

2) The Z-stage now has a specific repository with different solutions, offering different solutions with different levels of movement precision. According to the user and their budget, different solutions can be optimal for the endeavor.

https://github.com/openUC2/UC2-Zstage

The XY stage now also has a detailed repository, as the motorizing of the stage requires a fair amount of tinkering. The video tutorials and the detailed instructions on stage motorizing should help any user to reproduce the stage shown within this manuscript. https://github.com/openUC2/UC2-Motorized-XY-Table

3) The updated repository has a short video showing the general assembly of the cubes and the layers. Additionally, figure S2 shows all the pieces that are included in every layer (as a photograph as well as CAD). An exploded view of the complete setup would certainly be a helpful visualization of the complete setup. We however hope that the presented assembly tutorials and documents are sufficient to successfully reproduce the U.C.STORM setup.

First, we want to thank the reviewers for their effort to help us improving our work. We apologize for any trivial mistakes we had overlooked. Please find below our answers to the very constructive and helpful comments of the editors.  

Recommendations for the authors:

Reviewer #1 (Recommendations for The Authors):

To complement the current data set:

Figure 2(a & b): Panels i & ii, were chosen on the area where the distribution of the laser appears to be flatter. Can the authors select microtubules from a different section? Otherwise, it is reasonable to also crop the field-of-view along the flatter area (as done in Fig 6).

Figure 2 was changed to according to the reviewer’s suggestions. The profiles of microtubules from a different section have similar profiles, but the region with best illumination thus best SNR of the profile have been used for the figure.

Figure 2(c): The current plot shows the gaussian distribution which does not appear to be centered. Instead of a horizontal line, can the authors provide a diagonal profile across the field of view and update the panel below?

A diagonal cross-section of the illuminated FOV is provided in figure 2 to replace the previous horizontal profile. The pattern seems not to be perfectly radially symmetric, and more light seems to be blocked at the bottom of the illumination pattern compared to the top. A possible improvement can be provided by a fiber-coupled laser, that could provide a more homogeneous illumination while being easier to handle in the assembly process.

Author response image 1.

Diagonal cross-section of the illuminated FOV. Pixel-size (104nm) is the same as in figure 2. Intensity has been normalized according to the maximal value.

Figure 2(d): The system presents a XY drift of ~500nm over the course of a couple of hours. However, is not clear how the focus is being maintained. Can the authors clarify this point and add the axial drift to the plot?

The axial position of the sample could be maintained over a prolonged period of time without correcting for drift. Measurements where an axial shift was induced by tension pulses in the electronics have been discarded, but the stability of the stage seems to be sufficient to allow for imaging without lateral and axial drift correction. The XY drift measurement displayed in Figure 2(d) can be extended by measuring the σ of the PSF over time. The increase of σ would suggest an axial displacement in relation to the focus plane. In these measurements, a slight axial drift can be seen, the fluorescent beads however can still be localized over the whole course of the measurement.

A separate experiment was performed, using the same objective on the UC2 setup and on a high-quality setup equipped with a piezo actuator able to move in 10 nm steps. The precise Z steps of the piezo allows to reproducibly swipe through the PSF shape and to give an estimate of the axial displacement of the sample, according to the changes in PSF FWHM (Full Width at Half Maximum). When superimposing the graph with the UC2 measurement of fluorescent beads with the smallest possible Z step, an estimate about the relative axial position of the sample can be provided. The accuracy of the stage however remains limited.

Author response image 2.

Drift Figure: a. Drift of fluorescent TS beads on the UC2 setup positioned upon an optical table over a duration of two hours. Beads are localized and resulting displacement in i. and ii. are plotted in the graphs below. The procedure is repeated in b. with the microscope placed on a laboratory bench instead. c. (for the optical table i.) and d. (for the laboratory bench i.) show the variation in the sigma value of the localized beads over the measurement duration. As the sigma values changes when the beads are out of focus, the stability of the setup can be confirmed, as it remains practically unchanged over the measurement duration.

Author response image 3.

Z-focus Figure: Estimation of the axial position of TS beads on the UC2 setup. a. The change in PSF FWHM was quantified by acquiring a Z stack of a beads sample. The homebuilt high-quality setup (HQ) was used as a reference, by using the same objective and TS sample. The PSF FWHM on the UC2 setup was measured using the lowest possible axial stage displacement. A Z-position can thus be estimated for single molecules, as displayed in b.

Addressing the seemingly correlated behavior of the X and Y drift:

Further measurement show less correlation between drift in X and in Y. Simultaneous motion in X and Y seems to indicate that the stage or the sample is tilted. The collective movement in X and Y seems accentuated by bigger jumps, probably originating from vibrations (as more predominantly shown in the measurements on the laboratory bench compared to the optical table). Tension fluctuations inducing motion of the stage are possible but are highly unlikely to have induced the drift in the displayed measurements.

Figure 3: Can the authors comment on the effect or otherwise potential effect of the incubator (humidity, condensation etc) may have on the system (e.g., camera, electronics etc)?

When moving the microscope into the incubator, the first precaution is to check if the used electronics are able to perform at 37° C. Then, placing the microscope inside the incubator can induce condensation of water droplets at the cold interfaces, potentially damaging the electronics or reducing imaging quality. This can be prevented by preheating the microscope in e.g. an incubator without humidity, for a few hours before placing it within the functional incubator. The used incubator should also be checked for air streams (to distribute the CO2), and a direct exposure of the setup to the air stream should be prevented. The usage of a layer of foam material (e.g. Polyurethane) under the microscope helps to reduce possible effects of incubator vibrations on the microscope. The hydrophilic character of PLA makes its usage within the incubator challenging due to its reduced thermal stability. The temperature also inherently reduces the mechanical stability of 3D printed parts. Using a less hydrophilic and more thermally stable plastic, such as ABS, combined with a higher percentage of infill are the empirical solution to this challenge. Further options and designs to improve the usage of the microscope within the incubator are still in developement.

Figure 5: Can the authors perform single molecule experiments with an alternative tag such as Alexa647?

The SPT experiments were performed with QDs to make use of their photostability and brightness. The dSTORM experiment suggests that imaging single AF647 molecules with sufficient SNR is possible. The usage of AF647 for SPT is possible but would reduce the accuracy of the localization and shorten the acquired track-lengths, due to the blinking properties of AF647 when illuminated. The tracking experiment with the QDs thus was a proof of concept that the SPT experiments are possible and allow to reproduce the diffusion coefficients published in common literature. The usage of alternative tags can be an interesting extension of the capabilities that users can perform for their applications.

Figure 6: The authors demonstrate dSTORM of microtubules. It would enhance the paper to also demonstrate 3D imaging (e.g., via cylindrical lens).

The usage of a cylindrical lens for 3D imaging was not performed yet. The implementation would not be difficult, given the high modularity of the setup in general. The calibration of the PSF shape with astigmatism might however be challenging as the vertical scanning of the Z-stage lacks reliability in its current build. Methods such as biplane imaging might also be difficult to implement, as the halved number of photons in each channel leads to losses in the accuracy of localization. As a future improvement of the setup, the option of providing 3D information with single molecule accuracy is definitely desirable and will be tried out. In the following figure, two concepts for introducing 3D imaging capabilities in the detection layer of the microscope are presented.

Author response image 4.

3D concept Figure: Two possible setup modifications to provide axial information when imaging single molecules. a. A cylindrical lens can be placed to induce an asymmetry between the PSF FWHM in x and in y. Every Z position can be identified by two distinct PSF FWHM values in X and Y. b. By splitting the beam in two and defocusing one path, every PSF will have a specific set of values for its FWHM on the two detectors.

Imaging modalities section: Regarding the use of cling film to diffuse; can the authors comment on the continual use of this approach, including its degradation over time?

The cling foil was only used as a diffuser for broadening the laser profile. A detailed analysis of the constitution of the foil was not done, as no visible changes could be seen on the illumination pattern and the foil itself. The piece of cling foil is attached to a rotor. Detaching of the cling foil or vibrations originating from the rotor need to be minimized. By keeping the rotation speed to a necessary minimum and attaching the cling foil correctly to the rotor, a usable solution can be created. The low price of the cling foil provides the possibility to exchange the foil on a regular basis, allowing to keep the foil under optimal conditions.

Author response image 5.

Profile Figure: By moving a combination of pinhole and photometer to scan through the laser profile with a translational mount, the shape of the laser beam can be estimated. The cling foil plays the same role as a diffuser in other setups.

Reviewer #2 (Recommendations for The Authors):

lines

20, add "," after parts

110, rotating cling foil?

112/116, "custom 3D printed" I thought they were injection molded, please finalize

113, "puzzle pieces" rephrase and they are also barely visible

119, not clear that the stage is a manual stage that was turned into a motorised one by adding belts

123-126, detail for SI,

132, replace Arduino-coded with Arduino-based

143, add reference to Napari

146, (black) cardboard seems to be a cheaper and quicker alternative

153, dichroic

151-155, reads more like a blog post than a paper (maybe add a section on trouble shooting)

156, antibody?

167/189, moderate, please be specific

194, layer of foam material, specify

221, add description/reference to GPI. What is that? why is it relevant?

226: add one sentence description of MMS

318, add "," after students

332-334, as mentioned earlier, not clear, you bought a manual stage and connected belts, correct?

376-377, might be difficult to understand for the layman

391, what laser was used?

Figure 1, poor contrast between components, components visible should be named as much as possible, maybe provide the base layer in a different shade. To me, the red and blue labels look like fluorophores.

Figure 1. looks like d is the excitation layer and not e, please fix.

Figure 2, caption a-c, figure 1-d!, btw, why is the drift so anti-correlated?

Figure 6 (line 259) nanometer I guess, not micrometer

We now incorporated all the above-mentioned changes in the manuscript. Furthermore we added the supplementary Figures as below.

Author response image 6.

Basic concept of the UC2 setup: Left: Cubes (green) are connected to one another via puzzle pieces (white). Middle: 3D printed mounts have been designed to adapt various optics (right) to the cube framework. Combined usage of cubes and design of various mounts allows to interface various optics for the assembly.

Author response image 7.

Building the UC2 widefield microscope: a. Photograph of the complete setup. b. All pieces necessary to build the setup. A list of the components can be found in the bill of materials. c. Bottom emission layer of the microscope before assembly. d. Emission layer after assembly. Connection between cubes is doubled by using a layer of puzzles on the top and the bottom of the emission layer. e. CAD schematic of the emission layer and the positioning of the optics. f. Middle excitation layer of the microscope before assembly. Beam magnifier and homogenizer have been left out for clarity. g. Excitation layer after assembly is also covered by a puzzle layer. h. CAD schematic of the excitation layer and the positioning of the optics. i. Z-stage photograph and corresponding CAD file. Motor of the stage is embedded within the bottom cube. j. A layer of empty cubes supports the microscope stage. k. At this stage of the assembly, the objective is screwed into the objective holder. l. Finally, the stage is wired to the electronics and can then be mounted on top of the microscope (see a.).

Author response image 8.

Measurements performed on the UC2 setup with lower budget objectives. The imaged sample is HeLa cells, stably transfected to express CLC-GFP, then labelled with AF647 through immunostaining. The setup has been kept identical except for the objectives. Scale bar respectively represents 30 µm.

eLife assessment

This important study provides compelling evidence that the low-cost and open-hardware UC2 microscopy framework can be expanded to enable single-molecule localization microscopy. The authors managed to fit the instrumentation and control thereof in a unit that can be placed in a small stage-top-incubator. Together with providing adapted software for data acquisition and data analysis, the UC.STORM setup can rival the capabilities of comparable commercial instruments at a fraction of the costs.

Reviewer #1 (Public Review):

The authors have developed an open-source high-resolution microscope that is easily accessible to scientists, students, and the general public. The microscope is specifically designed to work with incubators and can image cells in culture over long periods. The authors provide detailed instructions for building the microscope and the necessary software to run it using off-the-shelf components. The system has great potential for studying cell biology and various biological processes.

The authors' work will make scientific instruments more accessible and remove obstacles to the free diffusion of capabilities and know-how in science. This important contribution will enable more people to conduct scientific research.

Reviewer #2 (Public Review):

Making state-of-the-art (super-resolution) microscopy widely available has been the subject of many publications in recent years as correctly referenced in the manuscript. By advocating the ideas of open-microscopy and trying to replace expensive, scientific-grade components such as lasers, cameras, objectives, and stages with cost-effective alternatives, interested researchers nowadays have a number of different frameworks to choose from. In the iteration of the theme presented here, the authors used the existing modular UC2 framework, which consists of 3D printable building blocks, and combined a cheapish laser, detector and x,y,(z) stage with expensive filters/dichroics and an expensive high-end objective (>15k Euros).

The choice of using the UC2 framework has the advantage, that the individual building blocks can be 3D printed, although it should be mentioned that the authors used injection-moulded blocks that will have a limited availability if not offered commercially by a third party. The strength of the manuscript is the tight integration of the hardware and the software (namely the implementations of imSwitch as a GUI to control data acquisition, OS SMLM algorithms for fast sub-pixel localisation and access to Napari).

The presented experimental data is convincing, demonstrating (1) extended live cell imaging both using bright-field and fluorescence in the incubator, (2) single-particle tracking of quantum dots, and (3) and STORM measurements in cells stained against tubulin.

For the revised (current) version of the manuscript, the authors further polished the manuscript and, more importantly, added plenty of information on the GitHub page that should make it significantly easier for interested researchers to replicate the instrument.

Overall, this is compelling work that is helping to make super-resolved microscopy more accessible.

eLife assessment

This important collection of over 800 new cell type-specific driver lines will be an invaluable resource for researchers studying associative learning in Drosophila. Thoroughly characterized and well documented, this collection will permit researchers to selectively target neurons that deliver information to, or receive it from, the memory center of the fly brain called the Mushroom Body. Given the wealth of new drivers and the genetic access they provide to over 300 cell types, this compelling work will be of interest not only to researchers studying the mechanisms of associative learning but more generally to those dissecting sensorimotor circuits in the fly nervous system.

Reviewer #1 (Public Review):

Summary:<br /> The emergence of Drosophila EM connectomes has revealed numerous neurons within the associative learning circuit. However, these neurons are inaccessible for functional assessment or genetic manipulation in the absence of cell-type-specific drivers. Addressing this knowledge gap, Shuai et al. have screened over 4000 split-GAL4 drivers and correlated them with identified neuron types from the "Hemibrain" EM connectome by matching light microscopy images to neuronal shapes defined by EM. They successfully generated over 800 split-GAL4 drivers and 22 split-LexA drivers covering a substantial number of neuron types across layers of the mushroom body associative learning circuit. They provide new labeling tools for olfactory and non-olfactory sensory inputs to the mushroom body; interneurons connected with dopaminergic neurons and/or mushroom body output neurons; potential reinforcement sensory neurons; and expanded coverage of intrinsic mushroom body neurons. Furthermore, the authors have optimized the GR64f-GAL4 driver into a sugar sensory neuron-specific split-GAL4 driver and functionally validated it as providing a robust optogenetic substitute for sugar reward. Additionally, a driver for putative nociceptive ascending neurons, potentially serving as optogenetic negative reinforcement, is characterized by optogenetic avoidance behavior. The authors also use their very large dataset of neuronal anatomies, covering many example neurons from many brains, to identify neuron instances with atypical morphology. They find many examples of mushroom body neurons with altered neuronal numbers or mistargeting of dendrites or axons and estimate that 1-3% of neurons in each brain may have anatomic peculiarities or malformations. Significantly, the study systematically assesses the individualized existence of MBON08 for the first time. This neuron is a variant shape that sometimes occurs instead of one of two copies of MBON09, and this variation is more common than that in other neuronal classes: 75% of hemispheres have two MBON09's, and 25% have one MBON09 and one MBON08. These newly developed drivers not only expand the repertoire for genetic manipulation of mushroom body-related neurons but also empower researchers to investigate the functions of circuit motifs identified from the connectomes. The authors generously make these flies available to the public. In the foreseeable future, the tools generated in this study will allow important advances in the understanding of learning and memory in Drosophila.

Strengths:<br /> 1) After decades of dedicated research on the mushroom body, a consensus has been established that the release of dopamine from DANs modulates the weights of connections between KCs and MBONs. This process updates the association between sensory information and behavioral responses. However, understanding how the unconditioned stimulus is conveyed from sensory neurons to DANs, and the interactions of MBON outputs with innate responses to sensory context remains less clear due to the developmental and anatomic diversity of MBONs and DANs. Additionally, the recurrent connections between MBONs and DANs are reported to be critical for learning. The characterization of split-GAL4 drivers for 30 major interneurons connected with DANs and/or MBONs in this study will significantly contribute to our understanding of recurrent connections in mushroom body function.

2) Optogenetic substitutes for real unconditioned stimuli (such as sugar taste or electric shock) are sometimes easier to implement in behavioral assays due to the spatial and temporal specificity with which optogenetic activation can be induced. GR64f-GAL4 has been widely used in the field to activate sugar sensory neurons and mimic sugar reward. However, the authors demonstrate that GR64f-GAL4 drives expression in other neurons not necessary for sugar reward, and the potential activation of these neurons could introduce confounds into training, impairing training efficiency. To address this issue, the authors have elaborated on a series of intersectional drivers with GR64f-GAL4 to dissect subsets of labeled neurons. This approach successfully identified a more specific sugar sensory neuron driver, SS87269, which consistently exhibited optimal training performance and triggered ethologically relevant local searching behaviors. This newly characterized line could serve as an optimized optogenetic tool for sugar reward in future studies.

3) MBON08 was first reported by Aso et al. 2014, exhibiting dendritic arborization into both ipsilateral and contralateral γ3 compartments. However, this neuron could not be identified in the previously published Drosophila brain connectomes. In the present study, the existence of MBON08 is confirmed, occurring in one hemisphere of 35% of imaged flies. In brains where MBON08 is present, its dendrite arborization disjointly shares contralateral γ3 compartments with MBON09. This remarkable phenotype potentially serves as a valuable resource for understanding the stochasticity of neurodevelopment and the molecular mechanisms underlying mushroom body lobe compartment formation.

Weaknesses:<br /> There are some minor weaknesses in the paper that can be clarified:

1) In Figure 8, the authors trained flies with a 20s, weak optogenetic conditioning first, followed by a 60s, strong optogenetic conditioning. The rationale for using this training paradigm is not explicitly provided. In Figure 8E, if data for training with GR64f-GAL4 using the same paradigm is available, it would be beneficial for readers to compare the learning performance using newly generated split-GAL4 lines with the original GR64f-GAL4, which has been used in many previous research studies. It is noteworthy that in previously published work, repeating training test sessions typically leads to an increase in learning performance in discrimination assays. However, this augmentation is not observed in any of the split-GAL4 lines presented in Figure 8E. The authors may need to discuss possible reasons for this.

2) In line 327, the authors state that in all samples, the β'1 compartment is arborized by MBON09. However, in Figure 11J, the probability of having at least one β'1 compartment not arborized is inferred to be 2%. The authors should address and clarify this conflict in the text to avoid misunderstanding.

3) In general, are the samples presented male or female? This sample metadata will be shown when the images are deposited in FlyLight, but it would be useful in the context of this manuscript to describe in the methods whether animals are all one sex or mixed sex, and in some example images (e.g. mAL3A) to note whether the sample is male or female.

Reviewer #2 (Public Review):

Summary:<br /> The article by Shuai et al. describes a comprehensive collection of over 800 split-GAL4 and split-LexA drivers, covering approximately 300 cell types in Drosophila, aimed at advancing the understanding of associative learning. The mushroom body (MB) in the insect brain is central to associative learning, with Kenyon cells (KCs) as primary intrinsic neurons and dopaminergic neurons (DANs) and MB output neurons (MBONs) forming compartmental zones for memory storage and behavior modulation. This study focuses on characterizing sensory input as well as direct upstream connections to the MB both anatomically and, to some extent, behaviorally. Genetic access to specific, sparsely expressed cell types is crucial for investigating the impact of single cells on computational and functional aspects within the circuitry. As such, this new and extensive collection significantly extends the range of targeted cell types related to the MB and will be an outstanding resource to elucidate MB-related processes in the future.

Strengths:<br /> The work by Shuai et al. provides novel and essential resources to study MB-related processes and beyond. The resulting tools are publicly available and, together with the linked information, will be foundational for many future studies. The importance and impact of this tool development approach, along with previous ones, for the field cannot be overstated. One of many interesting aspects arises from the anatomical analysis of cell types that are less stereotypical across flies. These discoveries might open new avenues for future investigations into how such asymmetry and individuality arise from development and other factors, and how it impacts the computations performed by the circuitry that contains these elements.

Weaknesses:<br /> Providing such an array of tools leaves little to complain about. However, despite the comprehensive genetic access to diverse sensory pathways and MB-connected cell types, the manuscript could be improved by discussing its limitations. For example, the projection neurons from the visual system seem to be underrepresented in the tools produced (or almost absent). A discussion of these omissions could help prevent misunderstandings. Additionally, more details on the screening process, particularly the selection of candidate split halves and stable split-GAL4 lines, would provide valuable insights into the methodology and the collection's completeness.

Reviewer #3 (Public Review):

Summary:<br /> Previous research on the Drosophila mushroom body (MB) has made this structure the best-understood example of an associative memory center in the animal kingdom. This is in no small part due to the generation of cell-type specific driver lines that have allowed consistent and reproducible genetic access to many of the MB's component neurons. The manuscript by Shuai et al. now vastly extends the number of driver lines available to researchers interested in studying learning and memory circuits in the fly. It is an 800-plus collection of new cell-type specific drivers target neurons that either provide input (direct or indirect) to MB neurons or that receive output from them. Many of the new drivers target neurons in sensory pathways that convey conditioned and unconditioned stimuli to the MB. Most drivers are exquisitely selective, and researchers will benefit from the fact that whenever possible, the authors have identified the targeted cell types within the Drosophila connectome. Driver expression patterns are beautifully documented and are publicly available through the Janelia Research Campus's Flylight database where full imaging results can be accessed. Overall, the manuscript significantly augments the number of cell type-specific driver lines available to the Drosophila research community for investigating the cellular mechanisms underlying learning and memory in the fly. Many of the lines will also be useful in dissecting the function of the neural circuits that mediate sensorimotor circuits.

Strengths:<br /> The manuscript represents a huge amount of careful work and leverages numerous important developments from the last several years. These include the thousands of recently generated split-Gal4 lines at Janelia and the computational tools for pairing them to make exquisitely specific targeting reagents. In addition, the manuscript takes full advantage of the recently released Drosophila connectomes. Driver expression patterns are beautifully illustrated side-by-side with corresponding skeletonized neurons reconstructed by EM. A comprehensive table of the new lines, their split-Gal4 components, their neuronal targets, and other valuable information will make this collection eminently useful to end-users. In addition to the anatomical characterization, the manuscript also illustrates the functional utility of the new lines in optogenetic experiments. In one example, the authors identify a specific subset of sugar reward neurons that robustly promotes associative learning.

Weaknesses:<br /> While the manuscript succeeds in making a mass of descriptive detail quite accessible to the reader, the way the collection is initially described - and the new lines categorized - in the text is sometimes confusing. Most of the details can be found elsewhere, but it would be useful to know how many of the lines are being presented for the first time and have not been previously introduced in other publications/contexts. And where can the lines be found at Flylight? Are they listed as one collection or as many? Also, the authors say that some of the lines were included in the collection despite not necessarily targeting the intended type of neuron (presumably one that is involved in learning and memory). What percentage of the collection falls into this category? And what about the lines that the authors say they included in the collection despite a lack of specificity? How many lines does this represent?

Reviewer #1 (Public Review):

Summary:

In this study, the authors examined the extent to which the processing of speech and music depends on neural networks that are either specific to a domain or general in nature. They conducted comprehensive intracranial EEG recordings on 18 epilepsy patients as they listened to natural, continuous forms of speech and music. This enabled an exploration of brain activity at both the frequency-specific and network levels across a broad spectrum. Utilizing statistical methods, the researchers classified neural responses to auditory stimuli into categories of shared, preferred, and domain-selective types. It was observed that a significant portion of both focal and network-level brain activity is commonly shared between the processing of speech and music. However, neural responses that are selectively responsive to speech or music are confined to distributed, frequency-specific areas. The authors highlight the crucial role of using natural auditory stimuli in research and the need to explore the extensive spectral characteristics inherent in the processing of speech and music.

Strengths:

The study's strengths include its high-quality sEEG data from a substantial number of patients, covering a majority of brain regions. This extensive cortical coverage grants the authors the ability to address their research questions with high spatial resolution, marking an advantage over previous studies. They performed thorough analyses across the entire cortical coverage and a wide frequency range of neural signals. The primary analyses, including spectral analysis, temporal response function calculation, and connectivity analysis, are presented straightforwardly. These analyses, as well as figures, innovatively display how neural responses, in each frequency band and region/electrode, are 'selective' (according to the authors' definition) to speech or music stimuli. The findings are summarized in a manner that efficiently communicates information to readers. This research offers valuable insights into the cortical selectivity of speech and music processing, making it a noteworthy reference for those interested in this field. Overall, this research offers a valuable dataset and carries out extensive yet clear analyses, amounting to an impressive empirical investigation into the cortical selectivity of speech and music. It is recommended for readers who are keen on understanding the nuances of selectivity and generality in the processing of speech and music to refer to this study's data and its summarized findings.

Weaknesses:

The weakness of this study, in my view, lies in its experimental design and reasoning:<br /> 1. Despite using longer stimuli, the study does not significantly enhance ecological validity compared to previous research. The analyses treat these long speech and music stimuli as stationary signals, overlooking their intricate musical or linguistic structural details and temporal variation across local structures like sentences and phrases. In previous studies, short, less ecological segments of music were used, maintaining consistency in content and structure. However, this study, despite employing longer stimuli, does not distinguish between neural responses to the varied contents or structures within speech and music. Understanding the implications of long-term analyses, such as spectral and connectivity analyses over extended periods of around 10 minutes, becomes challenging when they do not account for the variable, sometimes quasi-periodical or even non-periodical, elements present in natural speech and music. When contrasting this study with prior research and highlighting its advantages, a more balanced perspective would have been beneficial in the manuscript.

2. In contrast to previous studies that employed short stimulus segments along with various control stimuli to ensure that observed selectivity for speech or music was not merely due to low-level acoustic properties, this study used longer, ecological stimuli. However, the control stimuli used in this study, such as tone or syllable sequences, do not align with the low-level acoustic properties of the speech and music stimuli. This mismatch raises concerns that the differences or selectivity between speech and music observed in this study might be attributable to these basic acoustic characteristics rather than to more complex processing factors specific to speech or music.

3. The concept of selectivity - shared, preferred, and domain-selective - increases the risks of potentially overgeneralized interpretations and theoretical inaccuracies. The authors' categorization of neural sites/regions as shared, preferred, or domain-selective regarding speech and music processing essentially resembles a traditional ANOVA test with post hoc analysis. While this categorization gives meaningful context to the results, the mere presence of significant differences among control stimuli, a segment of speech, and a piece of music does not necessarily imply that a region is specifically selective to a type of stimulus like speech. The manuscript's narrative might lead to an overgeneralized interpretation that their findings apply broadly to speech or music. However, identifying differences in neural responses to a few sets of specific stimuli in one brain region does not robustly support such a generalization. This is because speech and music are inherently diverse, and specificity often relates more to the underlying functions than to observed neural responses to a limited number of examples of a stimulus type. See the next point.

4. The authors' approach, akin to mapping a 'receptive field' by correlating stimulus properties with neural responses to ascertain functional selectivity for speech and music, presents issues. For instance, in the cochlea, different stimuli activate different parts of the basilar membrane due to the distinct spectral contents of speech and music, with each part being selective to certain frequencies. However, this phenomenon reflects the frequency selectivity of the basilar membrane - an important function, not an inherent selectivity for speech or music. Similarly, if cortical regions exhibit heightened responses to one type of stimulus over another, it doesn't automatically imply selectivity or preference for that stimulus. The explanation could lie in functional aspects, such as a region's sensitivity to temporal units of a specific duration, be it music, speech, or even movie segments, and its role in chunking such units (e.g., around 500 ms), which might be more prevalent in music than in speech, or vice versa in the current study. This study does not delve into the functional mechanisms of how speech and music are processed across different musical or linguistic hierarchical levels but merely demonstrates differences in neural responses to various stimuli over a 10-minute span.

Reviewer #2 (Public Review):

Summary:

The study investigates whether speech and music processing involve specific or shared brain networks. Using intracranial EEG recordings from 18 epilepsy patients, it examines neural responses to speech and music. The authors found that most neural activity is shared between speech and music processing, without specific regional brain selectivity. Furthermore, domain-selective responses to speech or music are limited to frequency-specific coherent oscillations. The findings challenge the notion of anatomically distinct regions for different cognitive functions in the auditory process.

Strengths:

1. This study uses a relatively large corpus of intracranial EEG data, which provides high spatiotemporal resolution neural recordings, allowing for more precise and dynamic analysis of brain responses. The use of continuous speech and music enhances ecological validity compared to artificial or segmented stimuli.

2. This study uses multiple frequency bands in addition to just high-frequency activity (HFA), which has been the focus of many existing studies in the literature. This allows for a more comprehensive analysis of neural processing across the entire spectrum. The heterogeneity across different frequency bands also indicates that different frequency components of the neural activity may reflect different underlying neural computations.

3. This study also adds empirical evidence towards distributed representation versus domain-specificity. It challenges the traditional view of highly specialized, anatomically distinct regions for different cognitive functions. Instead, the study suggests a more integrated and overlapping neural network for processing complex stimuli like speech and music.

Weaknesses:

While this study is overall convincing, there are still some weaknesses in the methods and analyses that limit the implication of the work.

The study's main approach, focusing primarily on the grand comparison of response amplitudes between speech and music, may overlook intricate details in neural coding. Speech and music are not entirely orthogonal with each other at different levels of analysis: at the high-level abstraction, these are two different categories of cognitive processes; at the low-level acoustics, they overlap a lot; at intermediate levels, they may also share similar features. The selected musical stimuli, incorporating both vocals and multiple instrumental sounds, raise questions about the specificity of neural activation. For instance, it's unclear if the vocal elements in music and speech engage identical neural circuits. Additionally, the study doesn't adequately address whether purely melodic elements in music correlate with intonations in speech at a neural level. A more granular analysis, dissecting stimuli into distinct features like pitch, phonetics, timbre, and linguistic elements, could unveil more nuanced shared, and unique neural processes between speech and music. Prior research indicates potential overlap in neural coding for certain intermediate features in speech and music (Sankaran et al. 2023), suggesting that a simple averaged response comparison might not fully capture the complexity of neural encoding. Further delineation of phonetic, melodic, linguistic, and other coding, along with an analysis of how different informational aspects (phonetic, linguistic, melodic, etc) are represented in shared neural activities, could enhance our understanding of these processes and strengthen the study's conclusions.

The paper's emphasis on shared and overlapping neural activity, as observed through sEEG electrodes, provides valuable insights. It is probably true that domain-specificity for speech and music does not exist at such a macro scale. However, it's important to consider that each electrode records from a large neuronal population, encompassing thousands of neurons. This broad recording scope might mask more granular, non-overlapping feature representations at the single neuron level. Thus, while the study suggests shared neural underpinnings for speech and music perception at a macroscopic level, it cannot definitively rule out the possibility of distinct, non-overlapping neural representations at the microscale of local neuronal circuits for features that are distinctly associated with speech and music. This distinction is crucial for fully understanding the neural mechanisms underlying speech and music perception that merit future endeavors with more advanced large-scale neuronal recordings.

While classifying electrodes into 3 categories provides valuable insights, it may not fully capture the complexity of the neural response distribution to speech and music. A more nuanced and continuous approach could reveal subtler gradations in neural response, rather than imposing categorical boundaries. This could be done by computing continuous metrics, like unique variances explained by each category, or ratio-based statistics, etc. Incorporating such a continuum could enhance our understanding of the neural representation of speech and music, providing a more detailed and comprehensive picture of cortical processing.

Reviewer #3 (Public Review):

Summary:

Te Rietmolen et al., investigated the selectivity of cortical responses to speech and music stimuli using neurosurgical stereo EEG in humans. The authors address two basic questions: 1. Are speech and music responses localized in the brain or distributed; 2. Are these responses selective and domain-specific or rather domain-general and shared? To investigate this, the study proposes a nomenclature of shared responses (speech and music responses are not significantly different), domain selective (one domain is significant from baseline and the other is not), domain preferred (both are significant from baseline but one is larger than the other and significantly different from each other). The authors employ this framework using neural responses across the spectrum (rather than focusing on high gamma), providing evidence for a low level of selectivity across spectral signatures. To investigate the nature of the underlying representations they use encoding models to predict neural responses (low and high frequency) given a feature space of the stimulus envelope or peak rate (by time delay) and find stronger encoding for both in the low-frequency neural responses. The top encoding electrodes are used as seeds for a pair-wise connectivity (coherence) in order to repeat the shared/selective/preferred analysis across the spectra, suggesting low selectivity. Spectral power and connectivity are also analyzed on the level of the regional patient population to rule out (and depict) any effects driven by a select few patients. Across analyses the authors consistently show a paucity of domain selective responses and when evident these selective responses were not represented across the entire cortical region. The authors argue that speech and music mostly rely on shared neural resources.

Strengths:

I found this manuscript to be rigorous providing compelling and clear evidence of shared neural signatures for speech and music. The use of intracranial recordings provides an important spatial and temporal resolution that lends itself to the power, connectivity, and encoding analyses. The statistics and methods employed are rigorous and reliable, estimated based on permutation approaches, and cross-validation/regularization was employed and reported properly. The analysis of measures across the entire spectra in both power, coherence, and encoding models provides a comprehensive view of responses that no doubt will benefit the community as an invaluable resource. Analysis of the level of patient population (feasible with their high N) per region also supports the generalizability of the conclusions across a relatively large cohort of patients. Last but not least, I believe the framework of selective, preferred, and shared is a welcome lens through which to investigate cortical function.

Weaknesses:

I did not find methodological weaknesses in the current version of the manuscript. I do believe that it is important to highlight that the data is limited to passively listening to naturalistic speech and music. The speech and music stimuli are not completely controlled with varying key acoustic features (inherent to the different domains). Overall, I found the differences in stimulus and lack of attentional controls (passive listening) to be minor weaknesses that would not dramatically change the results or conclusions.

eLife assessment

This study presents valuable intracranial findings on how two types of natural auditory stimuli – speech and music – are processed in the human brain, and demonstrates that speech and music largely share network-level brain activities, thus challenging the domain-specific processing view. The evidence supporting the claims of the authors is solid but somewhat incomplete: although the data analysis is thorough, the results are robust and the stimuli have ecological validity, considerations such as low-level acoustics control, limitations of experimental design, and in-depth analysis, are lacking. The work will be of broad interest to speech and music researchers as well as cognitive scientists in general.

eLife assessment

In this study, the authors provide compelling evidence for dysgranular insular involvement in top-down and bottom-up interoceptive processing. Its translational application in ADE patients corroborates the assumption that the mid-insula may indeed be a locus of 'interoceptive disruption' in psychiatric disorders, which underscores the study's high relevance for both body-brain as well as clinical research. The authors' findings are fundamental and substantially advance our understanding of the neural basis of interoception and its putative disruption in psychiatric disorders.

Author Response

We appreciate the thoughtful comments from the reviewers. All reviewers express common support for the study’s meaningful contribution to understanding interoceptive neurocircuitry in health and in psychiatric disorders. Specifically, the reviewers highlight the strong theoretical backing and the novel combination of tasks and analytical methods. In turn, the reviewers identify several areas for improvement that we plan to address in our resubmission. These include a more detailed demographic characterization of the study participants, increased clarity when describing the statistics that support each conclusion, and additional discussion when interpreting the resting state findings, as we did not include a separate control condition for the effect of time. One reviewer commented that we largely cite our previous work with the isoproterenol paradigm; while we will provide an updated and broader view of the literature in our resubmission, there remains a limited number of comparable interoceptive perturbation studies. Finally, one comment referred to our reliance on ratings of interoceptive intensity without included additional behavioral measures. While our measures of interest were chosen for their relevance to our hypotheses, we will consider adding additional measures such as interoceptive accuracy (correspondence between heart rate and dial ratings) that were collected during the perturbation task, should they provide additional insight into the insular responses of the participants.

Author Response

The following is the authors’ response to the previous reviews.

This paper now provides a convincing presentation of valuable results of the drivers of nest construction for one termite species, and they briefly discuss possible relevance to other termite species. However, the authors have not yet addressed how their results may be important outside the field of termite nest construction. I could imagine the significance of the paper being elevated to important if there is a broader discussion about the impact of this work, e.g., the relevance of the results, the approach, and/or next steps to related fields outside of termite nest construction.

Reading our manuscript again, we have to agree with the reviewer that we mostly focused the discussion of our results in the context of termite construction, without attempting to generalise to other systems. To some extent we still defend this choice, as we prefer not to make too many claims on the relevance of our results beyond what we can reasonably support with our own experimental results. However, we thought that it would be appropriate – as suggested by the reviewer – to add at least one paragraph to indicate how our results could be extrapolated to other systems. This new paragraph is now at the end of the discussion section.

Here we elaborate a bit further on this point: first of all, while termites certainly build the most complex structures found in the natural world, there aren’t many other animals that are capable of collectively building complex structures. Typically, collective building activity is limited to highly social (typically eusocial) animals, but other social insects, such as ants and wasps, are phylogenetically distant from termites, their nests are often different (the large majority of ant nests only comprise excavated galleries with little construction, while wasp nests tend to comprise multiple repeated patterns that could be produced from stereotyped individual behaviour). Because of these differences, drawing a comparison between the mechanisms that regulate termite architecture and those that regulate other forms of animal architecture would be too speculative. One domain, however, where similar mechanisms to those that we describe here could operate is that of pattern formation at the cellular and tissue level, where surface curvature was shown to drive different phenomena from cell migration to tissue growth. A comment on this is now added in the manuscript at the very end of the discussion.

Similarly, on a related note, as someone not directly in the field of termite nest construction but wanting to understand the system (and the results) presented here in a broader context, I found the additional information about species and natural habitat very helpful and interesting, though I was rather disappointed to find it relegated to supplementary material where most readers will not see it.

We considered this suggestion to present more information about the natural nesting habits of the termites that we study into the main text, but eventually we decided to leave it as supplementary only. We feel that the nesting habits of the termites that we studied here are not too central to the problem that we want to focus on, of how they coordinate their building activity. In fact, there is a large variety of nesting habits across termite genera and species, but we believe that, at a basic level, the mechanisms that we describe here would also apply to species with different nesting habits, because our results are consistent with what is described in the scientific literature for other termite species. As our introduction is already a bit long, we left this description of Coptotermes nesting habits in the supplementary material, where, hopefully, it will still be accessible and useful to readers interested in finding this information.

When providing responses to reviewers, please directly address the reviewers’ comments point-by-point rather than summarizing comments and responding to summaries.

We apologize for our previous way to respond to comments and thanks the reviewer for his remark as we learn to navigate through the eLife reviewing system (where some comments are repeated in the overall assessment and in the feed-back of individual reviewers).

Figure 2 colors: Panels A and E and maybe B do not seem colorblind-friendly. I suggest modifying the colormaps to address this.

We have changed the colormaps of figures A,B and E which are now colorblind-friendly.

Line 180: This system is not in equilibrium. Perhaps the authors mean "steady-state?" I suggest reviewing language to ensure that the correct technical terms are used.

We have now corrected this.

eLife assessment

This valuable study investigates the environmental drivers behind termite construction, focusing, in particular, on pellet deposition behavior, with the conclusion that termites likely sense curvature indirectly through substrate evaporation. The findings reconcile discrepancies between previous studies through experimental and computational approaches. While the strength of the evidence supporting these claims is compelling, the authors do not discuss how their results affect our understanding of insect nest construction or animal-built structures more broadly.

Joint Public Review:

In this manuscript the authors performed experiments and simulations which showed that substrate evaporation is the main driver of early construction in termites. Additionally, these experiments and simulations were designed taking into account several different works, so that the current results shine a light on how substrate evaporation is a sufficient descriptor of most of the results seen previously.

Through simulations and ingenious experiments the authors have shown how curvature is extremely correlated with evaporation, and therefore, how results coming from these 2 environmental factors can be explained through evaporation alone. The authors have continued to use their expertise of numerical simulations and a previously developed model for termite construction, to highlight and verify their findings. On my first pass of the manuscript I felt the authors were missing an experiment: an array of humidity probes to measure evaporation in the three spatial dimensions and over time. Technologically such an experiment is not out of reach, but the author's alternative (a substrate made with a saline solution and later measuring the salt deposits on the surface) was a very ingenious low tech solution to the problem.

The authors agree that future experiments should tackle finely controlled humidity levels and curvature in order to have a more quantitative measure termite behaviour, but the work done so far is more than sufficient to justify their current claims.

In the revised text, the authors have added more clarity into different biological systems in which these results could be applied. Perhaps what it would have been beneficial to also add more information on how the resulting algorithms of constructions can be used in swarm robotics with collective construction, both macro and micro, but I acknowledge that the style of the paper does focus more on the biological aspects

The results presented here are so far the best attempt on characterizing multiple cues that induce termite construction activity, and that possibly unifies the different hypothesis presented in the last 8 years into a single factor, resulting into a valuable addition to the field. More importantly, even if these results come from different species of termites than some of the previous works, they are relatable and seem to be mostly consistent, improving the strength of the author's claims.

Author Response

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

HP1 plays a pivotal role in orchestrating chromatin packaging through the creation of biomolecular condensates. The existence of distinct homologs offers an intriguing avenue for investigating the interplay between genetic sequence and condensate formation. In this study, the authors conducted extensive coarse-grained simulations to delve into the phase separation behavior of HP1 paralogs. Additionally, the researchers delved into the captivating possibility of various HP1 paralogs co-localizing within assemblies composed of multiple components. Importantly, the study also delved into the critical role of DNA in finely tuning this complex process.

Strengths:

I applaud the authors for their methodical approach in conducting simulations aimed at dissecting the contributions of hinges, CTE, NTE, and folded regions. The comprehensive insights unveiled in Figure 3 compellingly substantiate the significance of these protein components in facilitating the process of phase separation.

This systematic exploration has yielded several innovative revelations. Notably, the authors uncovered a nuanced interplay between the folded and disordered domains. Although disordered regions have traditionally been linked to driving phase separation through their capacity for forming multivalent interactions, the authors have demonstrated that the contribution of the CD cannot be overlooked, as it significantly impacts the saturation concentration.

The outcomes of this study serve to elucidate the intricate mechanisms and regulatory aspects governing HP1 LLPS.

Weaknesses:

The authors do not provide an assessment of the quantitative precision of their model. To illustrate, HP1a is anticipated to undergo phase separation primarily under low salt concentrations. Does the model effectively capture this sensitivity to salt conditions? Regrettably, the specific salt conditions employed in the simulations are not explicitly stated. While I anticipate that numerous findings in the manuscript remain valid, it could be beneficial to acknowledge potential limitations tied to the simulations. For instance, might the absence of quantitative precision impact certain predictions, such as the CD's influence on phase separation?

We thank the reviewer for their kind feedback and for highlighting the essential mechanistic insights obtained from our study. We have addressed the concerns raised by the reviewer below, and the specific amendments made in the manuscript are also delineated.

We appreciate the reviewer's comment on our model. Our coarse-grained (CG) physics-based model integrates electrostatic and short-range interactions, parametrized based on the Urry hydrophobicity scale. This approach effectively bridges the timescale gap between simulation and experiment, offering a transferable framework to compute protein phase diagrams in temperature-concentration space that can be compared to experimental phase behavior (1). Additionally, the vdW contact probability per residue correlation between AA and CG simulations (Fig. S1 f-h) underscores our model’s capability to uncover the mechanistic insights into the phase separation of HP1 paralogs. Despite its simplicity and widespread adoption for studying sequence-dependent phase separation in biomolecular condensates, we recognize that our CG model does not yet fully replicate experimental observations or the nuanced effects of local secondary structures on phase-separation propensities. We are actively refining our methods and exploring new strategies to enhance the accuracy and efficiency of CG models for the study of biological phase separation.

In assessing the influence of salt on the LLPS of HP1α, we note that Wang et al. (2) demonstrated that HP1α can undergo LLPS at a low salt concentration (50 mM KCl). Furthermore, Wohl et al. (3) showed that the CG HPS (Kapcha-Rossky) model can capture the salt-dependent LLPS behavior through the electrostatic screening in HP1a, a Drosophila homolog of human HP1α. In our CG model, the salt concentration is captured by the DebyeHuckle term with tunable screening lengths, which allows for the simulations of salt-dependent effects in the low salt regime. We have added Figure S5 to illustrate the influence of salt on the LLPS propensity of HP1α. In the low-salt regime (50 mM), the Csat of HP1α was reduced by twofold compared to that at 100 mM. Increasing the salt concentration to 150 mM raised the Csat and started destabilizing the condensate. In the high salt regime (200500 mM), HP1α did not undergo phase separation, consistent with the experimental observations (2, 4–6).

Author response image 1.

Salt-dependent effects on the LLPS of HP1α homodimer. (a, b) Density profiles and snapshots of HP1α homodimer simulation with the box dimensions of 170x170x1190 Å3 at differing salt concentrations, 50, 100, 150, 200, 250, and 500 mM, respectively. The simulations were conducted at 320 K using the HPS-Urry model.

However, the primary objectives of our study are to elucidate the molecular interactions and to delineate the domain contributions that dictate the distinct phase-separation behaviors of the HP1 paralogs. To this end, we standardized our simulation conditions to a physiological salt concentration of 100 mM for all paralog constructs, facilitating a direct comparison and enabling physiologically relevant predictions, including those for the CD domain. We have added the salt concentration used in the CG simulations in the Materials and Methods section, relevant figure captions, and the following sentence in the third paragraph of the Discussions section to improve clarity.

“…Our CG simulations corroborate these experimental observations, indicating that a low salt concentration (50 mM) promotes the LLPS of HP1α. Raising the salt concentration weakens the electrostatic interactions and increases the Csat, eventually precluding HP1α’s phase separation at high salt regimes (200-500 mM) (Fig. S5).”

Reviewer #2 (Public Review):

In this paper, Phan et al. investigate the properties of human HP1 paralogs, their interactions and abilities to undergo liquid-liquid phase separation. For this, they use a coarse-grained computational approach (validated with additional all-atom simulations) which allows to explore complex mixtures. Matching (wet-lab) experimental results, HP1 beta (HP1b) exhibits different properties from HP1 alpha and gamma (HP1a,g), in that it does not phase separate. Using domain switch experiments, the authors determine that the more negatively charged hinge in HP1b, compared to HP1a and HP1g, is mainly responsible for this effect. Exploring heterotypic complexes, mixtures between HP1 subtypes and DNA, the authors further show that HP1a can serve as a scaffold for HP1b to enter into condensed phases and that DNA can further stabilize phase separated compartments. Most interestingly, they show that a multicomponent mixture containing DNA, and HP1a and HP1b generates spatial separation between the HP1 paralogs: due to increased negative charge of DNA within the condensates, HP1b is pushed out and accumulates at the phase boundary. This represents an example how complex assemblies could form in the cell.

Overall, this is purely computational work, which however builds on extensive experimental results (including from the authors). The methods showcase how coarse-grained models can be employed to generate and test hypotheses how proteins can condense. Applied to HP1 proteins, the results from this tour-de-force study are consistent and convincing, within the experimental constraints. Moreover, they generate further models to test experimentally, in particular in light of multicomponent mixtures.

There are, of course, some limitations to these models.

First, the CG models employed probably will not be able to pick up more complex structure-driven interactions (i.e. specific binding of a peptide in a protein cleft, including defined H-bonds, or induced structural elements). Some of those interactions (i.e. beyond charge-charge or hydrophobics) may also play a role in HP1, and might be ignored here. There is also the question of specificity, i.e. how can diverse phases coexist in cells, when the only parameters are charge and hydrophobicity? Does the arrangement of charges in the NTD, hinges and CTDs matter or are only the average properties important?

We thank the reviewer for the thoughtful comments. We also appreciate the opportunity to incorporate the feedback on the reviewer’s concerns below.

We agree that the interaction picture becomes more sophisticated, and many interaction modes may be involved in the phase coexistence in the cell environment. However, due to system sizes and required sampling, studying LLPS at an atomistic resolution remains challenging with the current state-of-the-art computer hardware. Our approach employs the CG model to reduce the computational cost but still capture the predominant interactions at the residue level. We have added the plots (Fig. S1 f-h) to show the correlation of the vdW contact probability per residue for each paralog between AA and CG simulation. The Pearson correlation coefficient is approximately 0.86, suggesting a strong positive linear correlation in the contact propensity between AA and CG simulations.

Author response image 2.

Our sequence analysis reveals a high fraction of charged residues in HP1 paralogs, with Arg, Lys, Glu, and Asp constituting 39-45% of the total amino acid count in the sequence. This property may explain why the electrostatic interactions are predominantly involved in the phase-separation behaviors of HP1 paralogs. Our findings on electrostatically driven phase separation and co-localization of HP1 paralogs are consistent with experimental observations by Larson et al. and Keenen et al. (5, 6). Significantly, we observe that the charge patterning in the disordered regions (NTE, hinge, and CTE) plays a critical role in the LLPS of HP1 paralogs, as articulated in the second paragraph of the Discussions section. Modifying this charge patterning, such as by phosphorylating serine residues in HP1α, excising the HP1α CTE, or substituting four acidic residues with basic ones in the HP1β hinge, can profoundly augment the LLPS of these proteins (4, 5, 7). Our in silico molecular details, complemented by in vitro observations, lay a solid foundation for future experiments. These future investigations may delve deeper into the specificity of interactions and the role of structural elements in modulating HP1 phase separation.

Second, the authors fix CSD-CSD dimers, whereas these interactions are expected to be quite dynamic. In the particular example of HP1 proteins, having dimerization equilibria may change the behavior of complex mixtures significantly, e.g. in view of the proposed accumulation of HP1b at a phase boundary. This point would warrant more discussion in the paper. Moreover, the biological plausibility of such a behavior would be interesting. Is there any experimental data supporting such assemblies?

We appreciate the reviewer's insightful comment regarding the dynamic nature of CSD-CSD interactions in HP1 proteins. Our assumption of fixing CSD-CSD dimers is grounded on reported dissociation constant (Kd) values for HP1α and HP1β, which are within the nanomolar range, indicative of strong dimerization affinity (4, 8). While the precise Kd values for HP1γ are not available, a study has demonstrated that HP1γ dimerization is crucial for its interaction with chromatin, suggesting a similar strong dimerization tendency as its paralogs (9, 10). Furthermore, evidence from the literature underscores the dimeric functionality of HP1 paralogs facilitated by their ChromoShadow Domains (CSD), which are instrumental in forming stable genomic domains and engaging in crucial interactions within chromatin architecture (5, 6, 11).

However, we acknowledge that despite the strong dimerization affinity, the CSD-CSD interactions exhibit dynamics, which may influence the behavior of complex mixtures, particularly at phase boundaries. A study by Nielsen et al. (12) shows that mammalian HP1 paralogs can interact directly with one another to form heterodimers. Moreover, the CSD-CSD interface has been shown to act as a hub for transient interactions with diverse binding partner proteins (5, 13). These experimental observations reflect the dynamic nature of CSD-CSD interactions. However, due to the computational constraints and the focus of our study, a simplified static model was employed to gain initial insights into the phase separation behaviors of HP1 paralogs. We believe that the dynamic nature of CSD-CSD interactions and its implications for phase behavior in complex mixtures form an exciting avenue for future computational and experimental studies.

In light of the reviewer’s comment, we have expanded our discussion in the 6th paragraph of the Discussions Section:

“... It is important to emphasize that our model is predicated on the assumption that HP1 proteins establish stable chromoshadow domain (CSD-CSD) dimers, a hypothesis supported by their Kd values being in the nanomolar range (13, 53). While this simplification serves as a useful starting point, it may not fully capture the dynamic nature of HP1 dimerization. Further computational and experimental studies are needed to understand better the behavior of the complex mixtures of HP1 paralogs, particularly at phase boundaries.”

References: 1) R. M. Regy, J. Thompson, Y. C. Kim, J. Mittal, Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins. Protein Sci., doi: 10.1002/pro.4094 (2021).

2) L. Wang, Y. Gao, X. Zheng, C. Liu, S. Dong, R. Li, G. Zhang, Y. Wei, H. Qu, Y. Li, C. D. Allis, G. Li, H. Li, P. Li, Histone Modifications Regulate Chromatin Compartmentalization by Contributing to a Phase Separation Mechanism. Mol. Cell 76, 646-659.e6 (2019).

3) S. Wohl, M. Jakubowski, W. Zheng, Salt-Dependent Conformational Changes of Intrinsically Disordered Proteins. J. Phys. Chem. Lett. 12, 6684–6691 (2021).

4) C. Her, T. M. Phan, N. Jovic, U. Kapoor, B. E. Ackermann, A. Rizuan, Y. C. Kim, J. Mittal, G. T. Debelouchina, Molecular interactions underlying the phase separation of HP1α: role of phosphorylation, ligand and nucleic acid binding. Nucleic Acids Res., gkac1194 (2022).

5) A. G. Larson, D. Elnatan, M. M. Keenen, M. J. Trnka, J. B. Johnston, A. L. Burlingame, D. A. Agard, S. Redding, G. J. Narlikar, Liquid droplet formation by HP1α suggests a role for phase separation in heterochromatin. Nature 547, 236–240 (2017).

6) M. M. Keenen, D. Brown, L. D. Brennan, R. Renger, H. Khoo, C. R. Carlson, B. Huang, S. W. Grill, G. J. Narlikar, S. Redding, HP1 proteins compact dna into mechanically and positionally stable phase separated domains. eLife 10, 1–38 (2021).

7) W. Qin, A. Stengl, E. Ugur, S. Leidescher, J. Ryan, M. C. Cardoso, H. Leonhardt, HP1β carries an acidic linker domain and requires H3K9me3 for phase separation. Nucleus 12, 44–57 (2021).

8) S. V. Brasher, The structure of mouse HP1 suggests a unique mode of single peptide recognition by the shadow chromo domain dimer. EMBO J. 19, 1587–1597 (2000).

9) X. Li, S. Wang, Y. Xie, H. Jiang, J. Guo, Y. Wang, Z. Peng, M. Hu, M. Wang, J. Wang, Q. Li, Y. Wang, Z. Liu, Deacetylation induced nuclear condensation of HP1γ promotes multiple myeloma drug resistance. Nat. Commun. 14, 1290 (2023).

10) Y. Mishima, C. D. Jayasinghe, K. Lu, J. Otani, M. Shirakawa, T. Kawakami, H. Kimura, H. Hojo, P. Carlton, S. Tajima, I. Suetake, Nucleosome compaction facilitates HP1γ binding to methylated H3K9. Nucleic Acids Res. 43, 10200–10212 (2015).

11) D. O. Trembecka-Lucas, J. W. Dobrucki, A heterochromatin protein 1 (HP1) dimer and a proliferating cell nuclear antigen (PCNA) protein interact in vivo and are parts of a multiprotein complex involved in DNA replication and DNA repair. Cell Cycle 11, 2170–2175 (2012).

12) A. L. Nielsen, M. Oulad-Abdelghani, J. A. Ortiz, E. Remboutsika, P. Chambon, R. Losson, Heterochromatin formation in mammalian cells: Interaction between histones and HP1 Proteins. Mol. Cell 7, 729–739 (2001).

13) A. Thiru, D. Nietlispach, H. R. Mott, M. Okuwaki, D. Lyon, P. R. Nielsen, M. Hirshberg, A. Verreault, N. V. Murzina, E. D. Laue, Structural basis of HP1/PXVXL motif peptide interactions and HP1 localisation to heterochromatin. EMBO J. 23, 489–499 (2004).

14) P. Yu Chew, J. A. Joseph, R. Collepardo-Guevara, A. Reinhardt, Thermodynamic origins of two-component multiphase condensates of proteins. Chem. Sci. 14, 1820–1836 (2023).

Recommendations for the authors:

In this important work, the authors apply a residue-resolution protein coarse-grained model to investigate the differences in molecule dimensions and phase behaviour of three HP1 paralogs, HP1 paralog mixtures, and HP1/DNA mixtures. The simulations are well designed to investigate the impact of HP1 sequence on its phase behaviour. The work reveals that electrostatic interactions are a key determinant of HP1 paralog phase behaviour; hence advancing our understanding of the molecular mechanisms driving the phase separation behaviour of HP1 paralogs. Notably, the authors uncovered a nuanced interplay between the folded and disordered domains of HP1. Although disordered regions have traditionally been linked to driving phase separation through their capacity for forming multivalent interactions, the authors demonstrate that the contribution of the CD cannot be overlooked, as it significantly impacts the saturation concentration.

Essential revisions (based on reviewers assessment below):

1) The manuscript describes the results of both single-molecule simulations and direct coexistence simulations. However, it is not very easy for the reader to determine which types simulations were performed in each section. The details on the simulations input parameters are also missing. Such details are needed throughout, i.e. to allow readers to follow the work and its implications. For instance, the specific salt conditions employed in the simulations are not explicitly stated. Since HP1 charge is presented as a key regulator for the modulation of HP1 paralogs radii of gyration and their phase behaviour, it is crucial for the authors to explicitly describe the salt concentration used for the different simulations and highlight how the relative differences observed are expected to change as the salt concentration decreases/increases.

We have turned the first sentences in the paragraphs into subtitles to describe the results of single homodimers in dilute phase and multi-dimers in phase coexistence simulations.

“Sequence variation affects the conformations of HP1 paralogs in the dilute phase.”

“Sequence variation in HP1 paralogs leads to their distinct phase separation behaviors.”

To improve the clarity, we have also added the following sentence to Fig. 2 caption.

“… Figs. 2a-e show the results obtained under dilute conditions, while Figs. 2f-m illustrate the conditions of phase coexistence.”

We have specified the salt concentration used in the CG simulations in the Materials and Methods section and the relevant figure captions to improve clarity. We also addressed the reviewer’s comment on salt concentration in the public review above.

2) Since direct coexistence simulations suffer from important finite-size effects, especially for multi-component mixtures as those investigated here, describing how many proteins/DNA copies were used per system, the size of the simulation, and which checks were done to check for finite-size effects is important. Regarding this point, estimating C_sat from Direct Coexistence simulations is extremely challenging, given the sensitivity of the dilute phase concentration to the box dimensions. Hence, it would be valuable if the authors clarify that the differences on C_sat provided represent a qualitative comparison and are sensitive to the simulation conditions. Importantly, the observation of spatial segregation of components in multi-component condensates could be an artefact of the box dimensions, relative copies of the various components, and overall system density.

We appreciate the reviewer’s concern regarding the finite-size effects in phase coexistence simulations and potential artifacts arising from box dimensions and system composition. In response to this, we have expanded the Materials and Methods section to elaborate on the specific checks to examine the finite-size effects. The new texts and additional SI figures are shown below.

“Previous studies have demonstrated that slab geometry can help mitigate finite-size effects and facilitate efficient sampling of the phase diagram (41). To assess the potential impact of finite-size effects with our chosen box dimensions, we conducted a test using the HP1α homodimer, which serves as a representative system given the comparable sequence lengths of HP1 paralogs and their chimeras. By reducing the system size by 30% and constructing its phase diagram, we observed that both the original system size (50 dimers) and the reduced counterpart (35 dimers) produced similar phase diagrams, with critical temperatures of 353.3 K and 352.1 K, respectively, as shown in Figs. S4a,b.

We further evaluated the influence of the xy cross-sectional area on the measurement of Csat. With the z-direction box length fixed at 1190 ų, we varied the xy cross-sectional areas (120x120, 150x150, and 200x200 Ų) while maintaining the protein density consistent with the control case (170x170 Ų). Given that HP1 dimers are multidomain proteins, a 120x120 Ų cross-section was the minimum size feasible to prevent particle overlap in HOOMD simulations due to the constraints of the small box size. Our findings indicate that the condensates remained stable across all tested cross-sectional areas and that there were no significant differences in Csat measurements within the margin of error, as depicted in Figs. S4c,d. These results confirm that our chosen box size is sufficiently large to minimize finite-size effects, thus ensuring the robustness of our results.”

Author response image 3.

Finite-size analysis. (a) Phase diagrams for the HP1α homodimer (50 dimers) and for a system reduced in size by 30% (35 dimers), with critical temperatures of 353.3 K and 352.1 K, respectively. (b) Density profiles of HP1α and its reduced size counterpart at various temperatures. (c, d) Density profiles and snapshots of HP1α homodimer simulation with box dimensions of 170x170x1190 Å3 and for systems with z-direction length fixed at 1190 Å and varying cross-sectional areas: 120x120, 150x150, and 200x200 Å2. The black dashed line shows the simulated saturation concentration of wildtype HP1α homodimer in the box dimensions of 170x170x1190 Å3. The simulations were conducted at 320 K and 100 mM salt concentrations. The error bars represent the standard deviation from triplicate simulation sets.

In response to the observed spatial segregation in our multi-component condensates, we have carefully considered finite-size effects and are confident that the segregation reflects genuine phase behavior rather than an artifact of simulation parameters. This interpretation is supported by findings from Chew et al. (14), who observed similar multilayered condensates and conducted thorough validations to verify these phases. To clarify our approach, we have included additional details in the Materials and Methods section of our manuscript.

“... By selecting a box size that minimizes finite-size effects, we can ensure that the spatial segregation observed in our multi-component condensates reflects genuine phase behavior. This finding aligns with Chew et al. (66), who also reported well-separated multilayered condensates and conducted thorough validations to confirm these phases.”

3) The authors should provide a clearer assessment of the quantitative precision of their model. For instance, the authors use all-atom simulations to compare with CG interaction maps. The all-atom maps are sparser due to less sampling, but the authors state that the maps are 'in good agreement'. How do the authors judge this? The issue of model validation is very important: to illustrate, HP1a is anticipated to undergo phase separation primarily under low salt concentrations. Does the model effectively capture this sensitivity to salt conditions? While numerous findings in the manuscript likely remain valid, it could be beneficial to acknowledge potential limitations tied to the simulations. For instance, might the absence of quantitative precision impact certain predictions, such as the CD's influence on phase separation?<br /> The CG models employed do not consider the specific binding of a peptide in a protein cleft, including defined H-bonds, or induced structural elements. Thus, the authors should discuss whether specific interactions (i.e. beyond charge-charge or hydrophobics) may also play a role in the phase behaviour of HP1, and why it makes sense to ignore them in this study. If the only important parameters are charge and hydrophobicity, how can diverse phases coexist in cells? Does the arrangement of charges in the NTD, hinges and CTDs matter or are only the average properties important?

This is similar to the point made by Reviewer 2 in the Public Review. We have addressed these questions in the public review and incorporated new plots (Fig. S1 f-h) in the SI.

4) The authors fix CSD-CSD dimers, whereas these interactions are expected to be quite dynamic. In the particular example of HP1 proteins, having dimerization equilibria may change the behaviour of complex mixtures significantly, e.g. in view of the proposed accumulation of HP1b at a phase boundary. This point warrants more discussion in the paper.

We have addressed the comment in the public review and extended the discussion in the Discussion section.

Reviewer #2 (Recommendations For The Authors):

The authors use all-atom simulations to validate their CG model. In Figure S1, they compare interaction maps. Of course, the AA maps are sparser due to less sampling, but the authors state that the maps are 'in good agreement'. How do the authors judge this (they do not look very similar to me, e.g. the NTD-hinge interactions are mostly lacking)?

This is similar to Reviewer 1’s concern. We agree that the AA simulations are moderately limited over 5 μs due to the large size of the HP1 proteins (~400 residues in a dimer). However, the expansion trends of the average dimensions of the HP1 paralogs agree with the CG simulations (Fig. S1 a,b). Regarding the AA contact maps, we agree that they are relatively sparse, which makes it difficult to compare them to the CG maps. We have added new plots (Fig. S1 f-h) to show the correlation of the vdW contact probability per residue for each paralog in the AA and CG simulations. The Pearson correlation coefficients are approximately 0.86, suggesting a strong positive linear correlation in the contact propensity between AA and CG simulations.

eLife assessment

This valuable study substantially advances our understanding of molecular mechanisms driving the phase separation behavior of HP1 paralogs. The evidence supporting the conclusions is convincing, with rigorous and well-designed computational simulations. The work will be of broad interest to biophysicists and biochemists.

Reviewer #1 (Public Review):

Summary:<br /> HP1 plays a pivotal role in orchestrating chromatin packaging through the creation of biomolecular condensates. The existence of distinct homologs offers an intriguing avenue for investigating the interplay between genetic sequence and condensate formation. In this study, the authors conducted extensive coarse-grained simulations to delve into the phase separation behavior of HP1 paralogs. Additionally, the researchers delved into the captivating possibility of various HP1 paralogs co-localizing within assemblies composed of multiple components. Importantly, the study also delved into the critical role of DNA in finely tuning this complex process.

Strengths:

I applaud the authors for their methodical approach in conducting simulations aimed at dissecting the contributions of hinges, CTE, NTE, and folded regions. The comprehensive insights unveiled in Figure 3 compellingly substantiate the significance of these protein components in facilitating the process of phase separation.

This systematic exploration has yielded several innovative revelations. Notably, the authors uncovered a nuanced interplay between the folded and disordered domains. Although disordered regions have traditionally been linked to driving phase separation through their capacity for forming multivalent interactions, the authors have demonstrated that the contribution of the CD cannot be overlooked, as it significantly impacts the saturation concentration.

The outcomes of this study serve to elucidate the intricate mechanisms and regulatory aspects governing HP1 LLPS.

Reviewer #2 (Public Review):

In this paper, Phan et al. investigate the properties of human HP1 paralogs, their interactions and abilities to undergo liquid-liquid phase separation. For this, they use a coarse-grained computational approach (validated with additional all-atom simulations) which allows to explore complex mixtures. Matching (wet-lab) experimental results, HP1 beta (HP1b) exhibits different properties from HP1 alpha and gamma (HP1a,g), in that it does not phase separate. Using domain switch experiments, the authors determine that the more negatively charged hinge in HP1b, compared to HP1a and HP1g, is mainly responsible for this effect. Exploring heterotypic complexes, mixtures between HP1 subtypes and DNA, the authors further show that HP1a can serve as a scaffold for HP1b to enter into condensed phases and that DNA can further stabilize phase separated compartments. Most interestingly, they show that a multicomponent mixture containing DNA, and HP1a and HP1b generates spatial separation between the HP1 paralogs: due to increased negative charge of DNA within the condensates, HP1b is pushed out and accumulates at the phase boundary. This represents an example how complex assemblies could form in the cell.

Overall, this is purely computational work, which however builds on extensive experimental results (including from the authors). The methods showcase how coarse-grained models can be employed to generate and test hypotheses how proteins can condense. Applied to HP1 proteins, the results from this tour-de-force study are consistent and convincing, within the experimental constraints. Moreover, the authors generate further models to test experimentally, in particular in light of multicomponent mixtures. Finally, the authors clearly discuss the computational methods, assumptions and limits of the methodology, which makes this a strong contribution to our understanding of biophysical basis of condensate formation in gene regulation.

eLife assessment

In this valuable study, the authors aimed to identify and characterize intrinsic factors that govern the aging process of bone marrow mesenchymal stromal cells (BMSCs), which are believed to be related to osteoporosis. The authors conclude that PCBP2 is an intrinsic aging factor, the decrease of its expression during aging results in cell proliferation activity decrease and cell senescence. The study provides convincing evidence in support of its conclusions.

Reviewer #1 (Public Review):

Summary:<br /> This study aimed to elucidate the intrinsic factors and potential mechanisms of BMSCs aging from the interactions among PCBP2, ROS, and FGF2. This study represents the first study to reveal PCBP2 as an intrinsic aging factor to regulate the replicative senescence of hBMSCs through ROS-FGF2 signaling. This study provides convincing evidence to support the above conclusion.

Strengths:<br /> This study utilized multiple in vitro approaches, such as proteomics, siRNA, and overexpression, to demonstrate that PCBP2 is an intrinsic factor of BMSC aging.

Weaknesses:<br /> This study did not perform in vivo experiments.

Reviewer #2 (Public Review):

Summary:<br /> The authors were trying to identify and characterize the intrinsic factors that control the process of cell aging of bone marrow mesenchymal stromal cells (BMSCs), which is believed to be related to osteoporosis.

Strengths:<br /> The method is reasonable. The concept and methods used in this work can be easily extended to other systems and cells to study their aging process. It is also interesting to further examine if PCBP2 functions as an intrinsic aging factor in these other cell types.

The results are solid, supporting the claims and conclusions. The authors successfully identified and characterized PCBP2 as one of the intrinsic aging factors for BMSC cells.

Weaknesses:<br /> It is unclear if PCBP2 can also function as an intrinsic factor for BMSC cells in female individuals. More work may be needed to further dissect the mechanism of how PCBP2 impacts FGF2 expression. Could PCBP2 impact the FGF2 expression independent of ROS?

Additional context that would help readers interpret or understand the significance of the work:<br /> In the current work, the authors studied the aging process of BMSC cells, which are related to osteoporosis. Aging processes also impact many other cell types and their function, such as in muscle, skin, and the brain.

eLife assessment

This valuable study describes an investigation of the properties of two heterologously-expressed Nav1.4 channels, with mutations close to the selectivity filter found in tetrodotoxin(TTX)-resistant snakes. The authors studied these mutants by electrophysiological methods, assessed the muscle properties of two types of snakes bearing these mutations, and built homology models of the channels to hypothesize a molecular explanation of the altered channel properties. The methods employed and the results are generally solid, although some aspects would benefit from additional experiments and a more nuanced discussion.

Reviewer #1 (Public Review):

Summary:<br /> This is an analysis of the mutations of Nav1.4 that allow tetrodotoxin resistance in two snake species while reducing the functional capacity of sodium channels in skeletal muscle and thereby reducing muscle function compared to toxin-sensitive snakes.

Strengths:<br /> This is a well-conceived, solid, and well-presented manuscript. Although the subject is not entirely new, the approach is original and the data obtained is solid. The analysis of the structural changes implications in the channel function is certainly an important contribution to the field.

Weaknesses:<br /> A short discussion on nerve sodium channels would be useful.

Reviewer #2 (Public Review):

Summary:<br /> The story of the co-evolution of TTX-bearing newts and their independently evolved TTX-resistant garter snake predators is a classic in evolutionary ecology/physiology. Over the years specific amino acid substitutions in the muscle-expressing (and other) sodium channels have been identified and the behavioral assays of snake crawling performance have indicated that the attainment of TTX-resistance comes at a cost in mobility. One previous study also examined how the amino acid mutations affected the biophysics of Nav channel properties. The present paper starts with this foundation and builds by adding in details and making causal connections across multiple snake populations with different degrees of resistance. The addition of muscle physiology bridges the gap between organismal performance and sodium channel biophysics. Moving in the other direction, examining molecular models of Nav channel structure and energetics allows a deep understanding of how amino acid substitutions affect channel properties. In the end, a clear picture is painted from molecular to organismal levels in two different parallel evolutions of TTX resistance.

Strengths:<br /> This study is a tour de force. It is clearly written, and nicely illustrated, and the methods and procedures are meticulously documented.

Weaknesses:<br /> One caveat is that the Nav channels used to test mutations in expression systems are rat channels engineered with TTX-resisting substitutions observed in snake populations. The ideal experiment would have been to use the snake channels. While the rat channels appear to be a good substitute for the snake channels and the authors have taken pains to show that the important amino acids are conserved between garter snakes and rats, the authors might explain why they did not use snake channels.

The noise analysis seems like a reasonable way to get at the question of single-channel conductance. But why did the authors not just measure single channel conductance in patches as opposed to this much more complex and roundabout method? It is recommended that the authors discuss how noise analysis deals with the problem of having the number of open channels changing rapidly during activation and fast inactivation. Is this a potential problem for deriving the total number of channels?

Reviewer #3 (Public Review):

Summary:<br /> This paper explores the cost of toxin resistance in snakes that prey on newts defended by highly potent TTX. Two species of garter snakes, T. atratus and T. sirtalis, are examined. Both species have resistant and sensitive populations. Resistance is achieved by substitutions in the voltage-gated sodium channels, which block TTX binding. Resistant T. atratus carry the triple substitutions EPN while resistant T. sirtalis carry the quadruple LVNV. These substitutions occur on the third and fourth intracellular domains of the voltage-gated sodium-channel gene Nav1.4, which is the paralog found in skeletal muscle. EPN and LVNV have been previously attributed to conferring resistance to TXX through target-site insensitivity of the channel. Previous work has also shown that snakes from resistant populations have reduced locomotor capabilities compared to their non-resistant counterparts.

The authors systematically test the hypothesis that the resistance-conferring substitutions affect other phenotypes related to the function of the voltage-gated sodium channel, which is, in turn, responsible for the reduced locomotor capabilities. First, they compare the effects of EPN and LVNV on recombinantly expressed rat Nav1.4 with and without EPN and LVNV (in vitro). They find that both EPN and LVNV significantly reduce the channel's conductance. On top of that, LVNV also causes premature deactivation of the channel, thus reducing the current passing through the membrane. Next, they compare muscle tissue function between resistant and non-resistant populations of T. atratus and T. sirtalis (ex vivo). They find that both resistant populations have reduced twitch force (with T. sirtalis, carrying LVNV, having an even stronger reduction), reduced peak rate of force development, and overall reduced force. In addition, T. sirtalis (LVNV) muscle also has reduced peak tetanic force. Finally, they compare the biophysical effects of EPN and LVNV through homology modeling of Nav1.4 to explain the in vitro and in vivo results (in silico). They found that E1248 (of EPN) has a counteracting effect on the destabilizing effect of N1539, shared by both species. T. sirtalis (LVNV) lacks such a counteracting mutation, which could explain the stronger negative effects observed in LVNV channels and muscles.

Strengths:<br /> A particular strength of this paper is the multi-level approach used to tease apart the negative pleiotropic effects of resistance-conferring substitutions. Each level of experiments informed the next, creating a focused comprehensive analysis of the costs associated with this specialized dietary adaptation in snakes. The results make an important contribution to our understanding of the role of negative pleiotropy in adaptive evolution and would be of broad interest to readers. The paper is well-written, and the data and analyses are clearly presented.

Weaknesses:<br /> The sheer size of the Nav1.4 gene makes it difficult to clone into an expression vector and that's probably why an already cloned rat Nav1.4 was selected for the in vitro experiments. It would be great if the authors could comment on how the level of resistance produced by mutations on the rat Nav1.4 compared to the garter snake Nav1.4s. Are there previous data on tissue-isolated T. sirtalis and T. atratus channels? Is it possible that the snake mutations have slightly different effects on the rat genetic background due to epistatic interactions with sites beyond the 3rd and 4th domains?

Following up on the first comment, sometimes negative pleiotropic effects are mitigated by compensatory mutations in other regions of the protein. This reviewer would recommend that the authors comment on this possibility. Are there substitutions beyond the 3rd and 4th domains that could potentially play a role in this adaptation?

Based on the results, it seems that resistant T. sirtalis got the shorter end of the stick concerning negative pleiotropic effects, despite having similar (the same?) levels of resistance to TTX. Does this difference/disadvantage scale up to locomotor performance as well?

It would be great if the authors could comment on how these resistant populations have persisted despite the locomotor/muscular disadvantages. Are there known differences in predation rates between the populations? The benefit must have outweighed the cost in these cases.

Reviewer #4 (Public Review):

Summary:<br /> The authors set out to address whether TTX resistance in a subset of snakes is due to mutations near the selectivity filters of their Nav1.4 channels. They present an investigation of the properties of two heterologously expressed Nav1.4 channels, bearing the Nav1.4EPN and Nav1.4LVNV mutations found in TTX-resistant snakes. After assessing their sensitivity to TTX, they have studied the biophysical properties of these mutants by electrophysiological methods and discovered that the voltage dependence of their activation and inactivation remains unchanged compared to the TTX-sensitive Nav1.4. These experiments revealed some kinetic differences in Nav1.4LVNV and that both Nav1.4EPN and Nav1.4LVNV show a reduced unitary conductance. The authors also assessed muscle properties (resistance, force development, and contraction timing) of two groups of snakes (in vivo and in dissected muscles) with Nav1.4EPN and Nav1.4LVNV mutations. These experiments showed a reduced performance for the skeletal muscles of snakes bearing Nav1.4EPN and Nav1.4LVNV background. Finally, the authors have built homology models of Nav1.4EPN and Nav1.4LVNV channels to hypothesize a molecular explanation of the altered properties.

Strengths:<br /> • Three levels of analysis are performed in this study: 1) functional characterization of mutated Nav1.4 channels through electrophysiology; 2) molecular level comparisons between human and snake Nav1.4 channels structures through homology modelling; 3) organismal performance/muscle strength experiments on snakes that carry Nav1.4 mutants that render them virtually TTX resistant.

Weaknesses:<br /> • While there is reason to believe that there is a causal link between the observed changes in Nav1.4 and the changes on the organismal level, the evidence presented is not definitive. Specifically, the conclusions from the biophysical/electrophysiological experiments are extrapolated to be causal for the altered muscle performance in TTX-resistant snakes, although there might be alternative explanations. First, the reduction in muscle force could also originate from changes in the calcium release apparatus or other alterations in the electrical properties of the muscle (are there changes in length or duration of muscle action potentials? Is there a change in the fraction of muscle cells that fail action potentials, as would be expected for a significant reduction in conductance?). Second, it remains unclear if, among the different snake Nav channels (e.g. Nav1.6 in motor neurons), Nav1.4 is the only one to display side chain alterations in these TTX-resistant snakes.

• Some of the data presented as part of the NSNA is not sufficiently convincing and should be supplemented with additional evidence or carefully discussed with regard to its limitations.

• The mutations studied are located close to the selectivity filter of Nav1.4. This means that the most likely consequence of the mutations is altered sodium selectivity, possibly along with changes to block extracellular calcium. But these possibilities are not currently addressed.

• The description and accuracy of the homology model remains somewhat unclear, as no validation of the modeled channel has been presented. Therefore, the accuracy of the homology model remains vague, which calls into question to what degree the molecular features of this model can be linked to the electrophysiological findings.

eLife assessment

The authors provide solid data on a functional investigation of potential nucleoid-associated proteins and the modulation of chromosomal conformation in a model cyanobacterium. While the experiments presented are convincing, the manuscript could benefit from restructuring towards the precise findings; alternatively, additional data buttressing the claims made would significantly enhance the study. These valuable findings will be of interest to the chromosome and microbiology fields.

Reviewer #1 (Public Review):

Strength:<br /> At first glance, I had a very positive impression of the overall manuscript. The experiments were well done, the data presentation looks very structured, and the text reads well in principle.

Weakness:<br /> Having a closer look, the red line of the manuscript is somewhat blurry. Reading the abstract, the introduction, and parts of the discussion, it is not really clear what the authors exactly aim to target. Is it the regulation of fermentation in cyanobacteria because it is under-investigated? Is it to bring light to the transcriptional regulation of hydrogenase genes? The regulation by SigE? Or is it to get insight into the real function of cyAbrB2 in cyanobacteria? All of this would be good of course. But it appears that the authors try to integrate all these aspects, which in the end is a little bit counterintuitive and in some places even confusing. From my point of view, the major story is a functional investigation of the presumable transcriptional regulator cyAbrB2, which turned out to be a potential NAP. To demonstrate/prove this, the hox genes have been chosen as an example due to the fact that a regulatory role of cyAbrB2 has already been described. In my eyes, it would be good to restructure or streamline the introduction according to this major outcome.

Points to consider:<br /> The authors suggest that the microoxic condition is the reason for the downregulation of e.g. photosynthesis (l.112-114). But of course, they also switched off the light to achieve a microoxic environment, which presumably is the trigger signal for photosynthesis-related genes. I suggest avoiding making causal conclusions exclusively related to oxygen and recommend rephrasing (for example, "were downregulated under the conditions applied").

The authors hypothesized that cyAbrB2 modulates chromosomal conformation and conducted a 3C analysis. But if I read the data in Figure 5B & C correctly, there is a lot of interaction in a range of 1650 and 1700 kb, not only at marked positions c and j. Positions c and j have been picked because it appears that cyAbrB2 deletion impacts this particular interaction. But is it really significant? In the case of position j the variation between the replicates seems quite high, in the case of position c the mean difference is not that high. Moreover, does all this correlate with cyAbrB2 binding, i.e. with positions of gray bars in panel A? If this was the case, the data obtained for the cyabrB2 mutant should look totally different but they are quite similar to WT. That's why the sentence "By contrast, the interaction frequency in Δcyabrb2 mutant were low and unchanged in the aerobic and microoxic conditions" does not fit to the data shown. But I have to mention that I am not an expert in these kinds of assays. Nevertheless, if there is a biological function that shall be revealed by an experiment, the data must be crystal clear on that. At least the descriptions of the 3C data and the corresponding conclusions need to be improved. For me, it is hard to follow the authors' thoughts in this context.

The figures are nicely prepared, albeit quite complex and in some cases not really supportive of the understanding of the results description. Moreover, they show a rather loose organization that sometimes does not fit the red line of the results section. For example, Figure 1D is not mentioned in the paragraph that refers to several other panels of the same figure (see lines110-128). Panel 1D is mentioned later in the discussion. Does 1D really fit into Figure 1 then? Are all the panels indeed required to be shown in the main document? As some elements are only briefly mentioned, the authors might also consider moving some into the supplement (e.g. left part of Figure 1C, Figure 2A, Figure 3B ...) or at least try to distribute some panels into more figures. This would reduce complexity and increase comprehensibility for future readers. Also, Figure 3 is a way too complex. Panel G could be an alone-standing figure. The latter would also allow for an increase in font sizes or to show ChIP data of both conditions (L+O2 and D-O2) separately. Moreover, a figure legend typically introduces the content as a whole by one phrase but here only the different panels are described, which fits to the impression that all the different panels are not well connected. Of course, it is the decision of the authors what to present and how but may they consider restructuring and simplifying.

The authors assume a physiological significance of transient upregulation of e.g. hox genes under microoxic conditions. But does the hydrogenase indeed produce hydrogen under the conditions investigated and is this even required? Moreover, the authors use the term "fermentative gene". But is hydrogen indeed a fermentation product, i.e. are protons the terminal electron acceptor to achieve catabolic electron balance? Then huge amounts of hydrogen should be released. Comment should be made on this.

The authors also mention a reverse TCA cycle. But is its existence an assumption or indeed active in cyanobacteria, i.e. is it experimentally proven? The authors are a little bit vague in this regard (see lines 241-246).

Reviewer #2 (Public Review):

This work probes the control of the hox operon in the cyanobacterium Synechocystis, where this operon directs the synthesis of a bidirectional hydrogenase that functions to produce hydrogen. In assessing the control of the hox system, the authors focused on the relative contributions of cyAbrB2, alongside SigE (and to a lesser extent, SigA and cyAbrB1) under both aerobic and microoxic conditions. In mapping the binding sites of these different proteins, they discovered that cyAbrB2 bound many sites throughout the chromosome repressed many of its target genes, and preferentially bound regions that were (relatively) rich in AT-residues. These characteristics led the authors to consider that cyAbrB2 may function as a nucleoid-associated protein (NAP) in Synechocystis, given its functional similarities with other NAPs like H-NS. They assessed the local chromosome conformation in both wild-type and cyabrB2 mutant strains at multiple sites within a 40 kb window on either side of the hox locus, using a region within the hox operon as bait. They concluded that cyAbrB2 functions as a nucleoid-associated protein that influences the activity of SigE through its modulation of chromosome architecture.

The authors approached their experiments carefully, and the data were generally very clearly presented and described.

Based on the data presented, the authors make a strong case for cyAbrB2 as a nucleoid-associated protein, given the multiple ways in which it seems to function similarly to the well-studied Escherichia coli H-NS protein. It would be helpful to provide some additional commentary within the discussion around the similarities and differences of cyAbrB2 to other nucleoid-associated proteins, and possible mechanisms of cyAbrB2 control (post-translational modification; protein-protein interactions; etc.). The manuscript would also be strengthened with the inclusion of biochemical experiments probing the binding of cyAbrB2, particularly focussing on its oligomerization and DNA polymerization/bridging potential.

Previous work had revealed a role for SigE in the control of hox cluster expression, which nicely justified its inclusion (and focus) in this study. However, the results of the SigA studies here suggested that SigA both strongly associated with the hox promoter, and its binding sites were shared more frequently than SigE with cyAbrB2. The focus on cyAbrB2 is also well-justified, given previous reports of its control of hox expression; however, it shares binding sites with an essential homologue cyAbrB1. Interestingly, while the B1 protein appears to bind similar sites, instead of repressing hox expression, it is known as an activator of this operon. It seems important to consider how cyAbrB1 activity might influence the results described here.

eLife assessment

The manuscript describes a valuable method to boost WNT signaling in a tissue-specific manner. The work extends previous data from the authors based on fusing an RSPO2 mutant protein to an antibody that binds ASGR1/2. In the current manuscript, two new antibodies with similar effects are described, that expand this solid approach and provide alternatives for potential future clinical applications. This manuscript will be of interest to all scientists studying protein engineering and cellular targeting.

Reviewer #1 (Public Review):

Summary:

The authors have previously described a way to boost WNT/CTNNB1 signaling in a tissue-specific manner, by directing an RSPO2 mutant protein (RSPO2RA) to a liver-specific receptor (ASGR1/2). This is done by fusing the RSPO2RA to an antibody that binds ASGR1/2.

Here the authors describe two new antibodies, 8M24 and 8G8, with similar effects. 8M24 shows specificity for ASGR1, while 8G8 has broader affinity for mouse/human ASGR1/2.

The authors resolve and describe the crystal structure of the hASGR1CRD:8M24 complex and the hASGR2CRD:8G8 complex in great detail, which helps explain the specificities of the 8M24 and 8G8 antibodies. Their epitopes are non-overlapping.<br /> Upon fusion of the antibodies to an RSPO2RA (an RSPO mutant), these antibodies are able to enhance WNT signaling by promoting the ASGR1-mediated clearance of ZNRF3/RNF43, thereby increasing cell surface expression of FZD. This has previously also been shown to be the case for RSPO2RA fused to an anti-ASGR1 antibody 4F3 - and the paper also tests how the antibodies compare to the 4F3 fusion.

Strengths:<br /> One challenge in treating diseases is the fact that one would like therapeutics to be highly specific - not just in terms of their target (e.g. aimed at a specific protein of interest) but also in terms of tissue specificity (i.e. affecting only tissue X but leaving all others unaffected). This study broadens the collection of antibodies that can be used for this purpose and thus expands a potential future clinical toolbox.

Weaknesses:<br /> 1. The authors demonstrate that ASGR1 is degraded in response to RSPO2RA-antibody treatment through both the proteasomal and the lysosomal pathway, suggesting that this is due to the RSPO2RA-mediated recruitment of ZNRF3/RNF43, which have E3 ubiquitin ligase activity. The paper doesn't show, however, if ASGR1 is indeed ubiquitinated.

2. The authors conclude that the RSPO2A-Ab fusions can act as a targeted protein degredation platform, because they can degrade ASGR. While I agree with this statement, I would argue that the goal of these Abs would not be to degrade ASGR per se. The argumentation is a bit confusing here. This holds for both the results and the discussion section: The authors focus on the dual role of their agents, i.e. on promoting both WNT signaling AND on degrading ASGR1. They might want to reconsider how they present their data (e.g. it may be interesting to target ASGR1, but one would presumably then like to do this without also increasing WNT responsiveness?).

3. Lines 326-331: The authors use a lot of abbreviations for all of the different protein targeting technologies, but since they are hinting at specific mechanisms, it would be better to actually describe the biological activity of LYTAC versus AbTAC/PROTAB/REULR so non-experts can follow.

4. Can the authors comment on how 8M24 and 8G8 compare to 4F3? The latter seems a bit more specific (ie. lower background activity in the absence of ASGR1 in 5C)? Are there any differences/advances between 8M24 and 8G8 over 4F3? This remains unclear.

5. Can the authors ensure that the axes are labelled/numbered similarly for Fig 5B-D? This will make it easier to compare 5C and 5D.

Reviewer #2 (Public Review):

Summary:<br /> The authors have previously engineered an antibody fusion protein targeting ZNRF3/RNF43 ubiquitin ligases, which enhances Wnt signaling specifically in hepatocytes. This is achieved using RSPO2RA (ZNRF3/RNF43 ligand with F105R/F109A mutations which abolish its binding to LGRs) and ASGR1 (hepatocyte-specific cell surface molecule). In the current study, they have identified two new ASGR1 and ASGR1/2 antibodies (8M24 and 8G8), which also enhance Wnt signaling when fused to RSPO2RA antibody. These also lead to the degradation of ASGR1, demonstrating that protein degradation and signaling enhancement can be dually targeted with a single molecule.

Strengths:<br /> The authors show crystal structures for binding of these antibodies to ASGR1/2, and hypothesize about why specificity is mediated through specific residues. They do not test these hypotheses.

The authors demonstrate a sub-picomolar affinity of these antibodies for ASGR1/2, which should be powerful clinically.

The authors demonstrate in hepatocyte cell lines that these function as mimetics, and that they do not function in HEK cells, which do not express ASGR1. They do not perform an exhaustive screen of all non-hepatocyte cells, nor do they test these molecules in vivo.

Surprisingly, these molecules also induced loss of ASGR1, which the authors hypothesize is due to ubiquitination and degradation, initiated by the E3 ligases recruited to ASGR1. They demonstrate that inhibition of either the proteasome or lysosome abrogates this effect and that it is dependent on E1 ubiquitin ligases. They do not demonstrate direct ubiquitination of ASGR1 by ZNRF3/RNF43.

Weaknesses:<br /> As co-listed with strengths above, the analysis is not always exhaustive but shows good preliminary findings for the field.