God's creation through speaking implies the power of the word, but also for me that word creates (fiction!)

Switch to lord god starts the story of the secondary creation

The idea was to push readers to "think like God"

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

SECTION A - Evidence, Reproducibility, and Clarity Summary The study investigates the neurodevelopmental impact of trisomy 21 on human cortical excitatory neurons derived from induced pluripotent stem cells (hiPSCs). Key findings include a modest reduction in spontaneous firing, a marked deficit in synchronized bursting, decreased neuronal connectivity, and altered ion channel expression-particularly a downregulation of voltage‐gated potassium channels and HCN1. These conclusions are supported by a combination of in vitro calcium imaging, electrophysiological recordings, viral monosynaptic tracing, RNA sequencing, and in vivo transplantation with two‐photon imaging.

Major Comments • Convincing Nature of Key Conclusions: The study's conclusions are generally well supported by a diverse set of experimental approaches. However, certain claims regarding the intrinsic properties of the excitatory network would benefit from further qualification. In particular, the assertion that reduced synchronization is solely attributable to altered ion channel expression might be considered somewhat preliminary without additional corroborative experiments.

1.1) We agree with the reviewer and now write in the abstract: 'Together, these findings demonstrate long-lasting impairments in human cortical excitatory neuron network function associated with Trisomy 21 .' And in the Introduction: 'Collectively, the observed changes in ion channel expression, neuronal connectivity, and network activity synchronization may contribute to functional differences relevant to the cognitive and intellectual features associated with Down syndrome.'

• One major limitation of the current experimental design is the reliance on predominantly excitatory neuronal cultures derived from hiPSCs. Although the authors convincingly demonstrate differences in network synchronization and connectivity between trisomic (TS21) and control neurons, the almost exclusive focus on excitatory cells limits the physiological relevance of the in vitro network. In the developing cortex, interneurons and astrocytes play crucial roles in modulating network excitability, synaptogenesis, and plasticity. Therefore, incorporating these cell types-either through co-culture systems or through directed differentiation protocols that yield a more heterogeneous neuronal population-could help to determine whether the observed deficits are intrinsic to excitatory neurons or are compounded by a lack of proper inhibitory regulation and glial support. 1.2) Thank you for this thoughtful comment. We agree that interneurons and astrocytes are crucial for network function. To clarify, astrocytes are generated in this culture system, as we previously reported in our characterisation of the timecourse of network development using this approach (Kirwan et al., Development 2025). However, our primary goal was to first isolate and define the cell-autonomous defects intrinsic to TS21 excitatory neurons, minimizing the complexity introduced by additional neuronal types. This focused approach was chosen also because engineering a stable co-culture system with reproducible excitatory/inhibitory (E/I) proportions is a significant undertaking that extends beyond the scope of this initial investigation, and has proven challenging to date for the field. By establishing this foundational phenotype, our work complements prior studies on interneuron and glial contributions. Future studies building on this work will be essential to dissect the more complex, non-cell-autonomous effects within a heterogeneous network. Importantly, since our initial submission, two highly relevant preprints have emerged-including a notable study from the Geschwind laboratory at UCLA (Vuong et al., bioRxiv, 2025; Risgaard et al., bioRxiv, 2025), as well as our own complementary study Lattke et al, under revision, that highlight widespread transcriptional changes in excitatory cells of the human fetal DS cortex, providing strong validation for our central findings. This convergence of results from multiple groups underscores the timeliness and importance of our work.

• Furthermore, the assessment of neuronal connectivity via pseudotyped rabies virus tracing, while innovative, has inherent limitations. The quantification of connectivity as a ratio of red-to-green fluorescence pixels may be influenced by differential viral infection efficiencies, variations in the expression levels of the TVA receptor, or even by the lower basal activity levels observed in TS21 cultures. Complementary approaches-such as electron microscopy for synaptic density analysis or functional connectivity measurements using multi-electrode arrays (MEAs)-could provide additional structural and functional insights that would validate the rabies tracing data. 1.3) Thank you for this constructive feedback. While we cannot formally exclude that TS21 cells might express the TVA receptor at lower levels due to generalized gene dysregulation, we infected all WT and TS21 cultures in parallel using identical virus preparations and titers to minimize technical variability. Crucially, we also addressed the potential confound of differential basal activity by performing the rabies tracing under TTX incubation (see Suppl. Fig. 7), which blocks network activity and ensures that viral spread reflects structural connectivity alone.

While complementary methods like EM or MEA could provide additional insight, they fall outside the scope of the current study. We are confident that our rigorous controls validate our use of the rabies tracing method to assess structural connectivity.

• Qualification of Claims: Some conclusions, particularly those linking specific ion channel dysregulation (e.g., HCN1 loss) directly to network deficits, might be better presented as preliminary. The authors could temper their language to indicate that while the evidence is suggestive, the mechanistic link remains to be fully established. 1.4) We have revised the text to more clearly indicate that the link between HCN1 dysregulation and network deficits is correlative and remains to be fully established. While our ex vivo recordings suggest altered Ih-like currents consistent with reduced HCN1 expression, we now present these findings as preliminary and hypothesis-generating, pending further functional validation. We write in the discussion: However, further targeted functional validation will be needed to confirm a causal link.

• Need for Additional Experiments: Additional experiments that could further consolidate the current findings include: o Inclusion of Inhibitory Neurons or Co-culture Systems: Incorporating interneurons or astrocytes would help determine whether the observed deficits are solely intrinsic to excitatory neurons. See 1.2 o Alternative Connectivity Assessments: Complementing the rabies virus tracing with electron microscopy or multi-electrode array (MEA) recordings would add structural and functional validation of the connectivity differences. See 1.3 o Extended Temporal Profiling: Monitoring network activity over a longer developmental window would clarify whether the observed deficits represent a delay or a permanent alteration in network maturation. 1.5) In vivo we were able to track the cells for up to five months post-transplantation supporting the interpretation of a permanent alteration.

• Reproducibility and Statistical Rigor: The methods and data presentation are largely clear, with adequate replication and appropriate statistical analyses. Nonetheless, a more detailed description of the experimental replicates, particularly regarding the viral tracing and in vivo transplantation studies, would enhance reproducibility. The availability of raw data and scripts for calcium imaging analysis would also further support independent verification. We thank the reviewer for these suggestions and we now provide a more detailed description of replicates. We also add the raw data.

Minor Comments • Experimental Details: Minor revisions could include clarifying the infection efficiency and expression levels of the viral constructs used in connectivity assays to rule out technical variability.

See 1.3

• Literature Context: The authors reference prior studies appropriately; however, integrating a brief discussion comparing their findings with alternative DS models (e.g., organoids or other hiPSC-derived systems) would improve contextual clarity. We thank the reviewer for this helpful suggestion. We have now added a brief discussion comparing our findings with those reported in alternative Down syndrome models, including brain organoids and other hiPSC-derived systems. This addition helps to contextualize our results within the broader field and highlights the unique strengths and limitations of our in vitro and in vivo xenograft approach. We write: 'Our findings align with and extend previous studies using alternative Down syndrome models, such as brain organoids and other hiPSC-derived systems. Organoid models have provided valuable insights into early neurodevelopmental phenotypes in DS, including altered interneuron proportions (Xu et al Cell Stem Cell 2019) but also suggest that variability across isogenic lines can overshadow subtle trisomy 21 neurodevelopmental phenotypes (Czerminski et al Front in Neurosci 2023). However, these systems often lack the structural complexity, vascularization, and long-term maturation achievable in vivo. By using a xenotransplantation model, we were able to assess the maturation and functional properties of human neurons within a physiologically relevant environment over extended time frames, offering complementary insights into DS-associated circuit dysfunction (Huo et al Stem Cell Reports 2018; Real et al., 2018).

• Presentation and Clarity: Figures are generally clear,.But the manuscript contains a minor labeling error. On page 13, the figure is erroneously labeled as "Fig6A", whereas, based on the context and corresponding data, it should be "Fig5A". I recommend that the authors correct this mistake to ensure consistency and avoid potential confusion for readers. Thank you for pointing this out. This has been corrected in the revised manuscript.

Reviewer #1 (Significance (Required)):

SECTION B - Significance • Nature and Significance of the Advance: The work offers a substantial conceptual advance by providing a mechanistic link between trisomy 21 and impaired neuronal network synchronization. Technically, the study integrates state-of-the-art imaging, electrophysiology, and transcriptomic profiling, thereby offering a multifaceted view of DS-related neural dysfunction. Clinically, the findings have the potential to inform future therapeutic strategies targeting network connectivity and ion channel function in Down syndrome.

We thank the reviewer for this very supportive comment.

• Context in the Existing Literature: The study builds on previous observations of altered network activity in DS patients and DS mouse models (e.g., altered EEG synchronization and reduced synaptic connectivity). It extends these findings to human-derived neuronal models, thus bridging a gap between clinical observations and molecular/cellular mechanisms. Relevant literature includes studies on DS neurodevelopment and the role of ion channels in synaptic maturation. • Target Audience: The reported findings will be of interest to researchers in neurodevelopmental disorders, Down syndrome, and ion channel physiology. Additionally, the study may attract the attention of those working on hiPSC-derived models of neurological diseases, as well as clinicians interested in the pathophysiology of DS. • Keywords and Field Contextualization: Keywords: Down syndrome, trisomy 21, neuronal connectivity, synchronized network activity, hiPSC-derived cortical neurons, ion channel dysregulation.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary The manuscript by Peter et al., reports on the neuronal activity and connectivity of iPSC-derived human cortical neurons from Down syndrome (DS) that is caused by caused by trisomy of the human chromosome 21 (TS21). Major points: Although the manuscript is potentially interesting, the results appear somehow preliminary and need to be corroborated by control experiments and quantifications of effects to fully sustain the conclusions. (1) The authors have not assessed the percentage of WT and TS21 cells that acquire a neuronal or glia identity in their cultures. Indeed, the origin of alterations in network activity and connectivity observed in TS21 neurons could simply derive from reduced number of neurons arising from TS21 iPSC. Alternatively, the same alteration in network activity and connectivity could derive from a multitude of other factors including deficits in neuronal development, neurite extension, or intrinsic electrophysiological properties. In the current version of the manuscript, none of these has been investigated. 2.1) We thank the reviewer for this thoughtful comment. In response, we included an in vivo characterization of cell-type proportions at the same time points where we observed network activity defects using in vivo calcium imaging (see Supplementary Fig. 6).

Previous work has identified several cellular and molecular phenotypes in human cells, postmortem tissue, and mouse models-including those mentioned by the reviewer. In this study, our focus was on investigating neural network activity, intrinsic electrophysiological properties both in vitro and in vivo, and preliminary bulk RNA sequencing. We have also independently measured cell proportions in the human fetal cortex and conducted a more extensive transcriptomic analysis of Ts21 versus control cells in a separate study (Lattke et al., under revision). We observed a reduction of RORB/FOXP1-expressing Layer 4 neurons in the human fetal cortex at midgestation, as well as increased GFAP+ cells, reduced progenitors and a non significant reduction of Cux2+ cells in late stage DS human cell transplants, along with a gene network dysregulation specifically affecting excitatory neurons (Lattke et al., under revision). Here, we provide complementary findings, demonstrating reduced excitatory neuron network connectivity in vitro and decreased neural network synchronised activity in both in vitro and in vivo models (see also 2.8). We agree with the reviewer that this could be for a number of reasons, both cell autonomous (channel expression and/or function) or non-autonomous (connectivity and/or network composition - as reflected in differences in proportions of SATB2+ neurons generated in TS21 cortical differentiations).

(2) Electrophysiological properties of TS21 and WT neurons at day 53/54 in vitro indicate an extremely immature stage of development (i.e. RMP between -36 and -27 mV with most of the cells firing a single action potential after current injection) in the utilized culture conditions: This is far from ideal for in vitro neuronal-network studies. Finally, reduced activity of HCN1 channels should be confirmed by specific recordings isolating or blocking the related current.

2.2) Thank you for this thoughtful comment. We have also conducted ex vivo electrophysiological recordings and found that the neurons exhibit relatively immature properties, consistent with the known slow developmental trajectory of human neuron cultures. In light of this and the absence of direct confirmatory evidence, we now refer to the observed reduction in HCN1 as preliminary.

Main points highlighting the preliminary character of the study. 1) In Figure 1 immunofluorescence images of the neuronal differentiation markers (Tbr1, Ctip2 and Tuj1) are showed. However, no quantification of the percentage of cells expressing these markers for WT and TS21 neurons is reported. On the other hand, simple inspection of the representative images clearly seams to indicate a difference between the two genotypes, with TS21 cultures showing lower number of cells expressing neuronal markers. This quantification should be corroborated by a similar staining for an astrocyte marker (GFAP, but not S100b since is triplicated in DS). This is an extremely important point since it is obvious that any change in the percentage of neurons (or the neuron/astrocyte ratio) in the cultures will strongly affect the resulting network activity (shown in Figure 2) and the connectivity (showed in Figure 4). Possibly, the quantification should be done at the same time points of the calcium imaging experiments.

2.3) See 2.1. We included an in vivo characterization of cell-type proportions at the same time points where we observed network activity defects using in vivo calcium imaging. (see Supplementary Fig. 6).

2) In Figure 2 the authors show some calcium imaging traces of WT and TS21 cultures at different time points. However, they again do not show any quantification of neuronal activity. A power spectra analysis is shown in Supplementary Figure 2, but only for WT cultures, while in Supplementary Figure 3 a comparison between WT and Ts21 power spectra is done, but only at the 50 day time point, while difference in synchrony are assessed at 60 days. At minimum, the author should include in main Figure 2 the quantification of the mean calcium event rate and mean event amplitude at the different time points and the power spectra analysis for both WT and TS21 cultures at the same timepoints.

2.4) We thank the reviewer for this comment. We now add the power spectra analysis in the main Figure 2 and quantification of the mean calcium burst rate and mean event amplitude in SuppFig. 4.

Of note, the synchronized neuronal activity is present in WT cultures at day 60, but totally lost at subsequent time-points (70 and 80 days). The results of this later time points are different from previous data from the same lab (Kirwan et al., 2015). How might these data be explained? It would be important to rule out any potential issues with the health of the culture that could explain the loss of neuronal activity.It would be beneficial to check cell viability at the different time points to exclude possible confounding factors ? A propidium staining or a MTT assay would strongly improve the soundness of the calcium data.

2.5) We thank the reviewer for this important observation. The difference from the findings reported in Kirwan et al., 2015 is due to the use of a different neuronal differentiation medium in the current study (BrainPhys versus N2B27). BrainPhys medium supports robust early network activity compared to N2B27 (onset before day 60 in BrainPhys, post-day 60 in N2B27), resulting in an earlier decline in synchrony at later stages (day 70-80 in BrainPhys, compared with day 90-100 in N2B27). Importantly, in our in vivo xenograft model, burst activity is sustained up to at least 5 months post-transplantation (mpt), indicating that the neurons retain the capacity for network activity over extended periods in a more physiological environment. We adapted the text accordingly.

3) In Figure 3 there is no quantification of the number and/or density of transplanted neurons for WT and TS21, but only representative images. As above, inspection of the representative images seems to show a decrease in cells labeled by the Tbr1 neuronal marker for TS21 cells. Moreover, the in vivo calcium imaging of transplanted WT and TS21 cells lacks most of the quantification normally done in calcium imaging experiments. Are the event rate and event amplitude different between WT and TS21 neurons ? The measure of neuronal synchrony by mean pixel correlation is not well explained, but it looks somehow simplistic. Neuronal synchrony can be more precisely measured by cross-correlation analysis or spike time tiling coefficients on the traces from single-neuron ROI rather than on all pixels in the field of view, as apparently was done here.

2.6) We thank the reviewer for these valuable points. We now include quantification of the number and density of transplanted neurons for both WT and Ts21 grafts in Extended Data Figure 5 (see 2.1).

Regarding the in vivo calcium imaging, we appreciate the reviewer's suggestion to include additional standard metrics. We have quantified the event rate in Real et al 2018. These analyses reveal that Ts21 neurons show a reduction in event rate.

We agree that our initial description of the synchrony analysis using mean pixel correlation was not sufficiently detailed. We have now clarified this in the Methods and Results, and we acknowledge its limitations. Importantly, we note that the reduced synchronisation is a highly consistent phenotype, observed across at least six independent donor pairs, different differentiation protocols, and both in vitro (and in two independent labs) and in vivo settings. As suggested, future studies using ROI-based approaches-such as cross-correlation or spike-time tiling coefficients-would provide a more refined characterization of synchrony at the single-neuron level (Sintes et al, in preparation). We now include this point in the discussion.

4) The results on reduced neuronal connectivity in Figure 3 look very striking. However, these results should be accompanied by control experiments to verify the number of neuronal cells and neurite extension in WT and Ts21 cultures. These two parameters could indeed strongly influence the results. As the cultures appear to grow in clusters, bright-field images and TuJ1 staining of the cultures will also greatly help to understand the degree of morphological interconnection between the clusters.

We now add Tuj1 staining in Supplementary figure 10.

5) The authors performed RNA-seq experiments on day 50 cultures. Why the authors do not show the complete differential gene expression analysis, but only a small subset of genes? A comprehensive volcano plot and the complete list of identified genes with logFC and FDR values would be helpful. If possible, comparison of the present data (particularly on KCN and HCN expression changes) with published and publicly available expression datasets of other human or human Down syndrome iPSC-derived neurons or human Down syndrome brains will greatly increase the soundness of the present findings. In addition, the gene ontology (GO) results are mentioned in the text, but are not presented. Showing the complete GO analysis for both up and downregulated genes will help the reader to better understand the RNA-seq results. Notably, the results shown in Supplementary Figure on GRIN2A and GRIN2B expression (with values of 300-700 counts versus 2000-4000 counts, respectively) clearly indicate that in both WT and TS21 cultures the NMDA developmental switch has not occurred yet at the 50 days timepoint.

We now show volcano plots in Supplementary Fig. 11.

6) The measure of hyperpolarization-activated currents shown in Figure 5 lack proper control experiments. First, the hyperpolarizing current in TS21 cells do not reach a steady-state as the controls. The two curves are therefore hard to compare. To exclude possible difference in kinetic activation, the authors should have prolonged the current injection period (1-2 seconds). Second, to ultimately prove that such currents are mediated by HCN channels in WT cells the authors should perform some control experiments with a specific HCN blocker. A good example of a suitable protocol, with also current blockers to exclude all other possible current contributions, is the one reported in Matt et al Cell. Mol. Life Sci. 68, 125-137 (2011).

2.7) We thank the reviewer for this detailed and helpful comment. We agree that to definitively identify the recorded currents as Ih, it would be necessary to isolate them pharmacologically using specific HCN channel blockers and appropriate controls, such as those described in Matt et al., Cell. Mol. Life Sci. Unfortunately, due to current constraints, we no longer have access to the animals used in this study and cannot allocate the necessary time or resources, we are unable to perform the additional experiments at this stage.

However, our goal here was to use electrophysiological recordings as an indication of altered HCN channel activity, which we then support with molecular evidence. We now emphasize this point more clearly in the revised manuscript.

7) The manuscript lacks information on the statistical analysis used. Also, the numerosity of samples is not clear. Were the dots shown in some graph technical replicates from a single neuronal induction or were all independent neuronal inductions or a mix of the two ? Please clarify.

We now clarify the numbers in the Figure legend.

8) The method section lacks important information to guarantee reproducibility. Just a few examples: • Only electrophysiology methods for slice are reported, but not for in vitro culture.

We now clarify these details in the methods.

• Details on Laminin coating is lacking. What concentration was used ? Was poly-ornithine or poly-lysine used before Laminin coating ? We now clarify these details in the methods.

• How long cells were switched to BrainPhys medium before calcium imaging ? We now clarify these details in the methods.

Minor point/typos etc.

Introduction • Page 4 line 6: in the line "Trisomy 21 in humans commonly results in a range in developmental and morphological changes in the forebrain ..." "in" could be replaced by "of". We have fixed this. • Page 5 line 2: please remove "an" before the word "another". We have fixed this. • Page 5 line 2: please replace "ecitatory" with "excitatory". We have fixed this typo.

Results • Page 10 line 25: The concept of "pixel-wise" appears for the first time in this section and could be better introduced to facilitate the understanding of the experiment. • In the "results" section, page 11 line 1 and 4, references are made to "Figure 4D" and "4F," but these figures do not appear to be present in the figure section. Upon reviewing the rest of the section, the data seem to refer to "Figure 3D" and "3E." We have fixed this. Discussion • Page 15 line 20: please replace "synchronised" with "synchronized". We have fixed this typo. • Page 16 line 11: please replace "T21" with "TS21". We have fixed this typo. Methods • Page 19 line 12: "Pens/Strep" has to be replaced by Pen/Strep. We have fixed this typo. • Page 20 line 20: "Tocris Biocience" has to be replaced by "Tocris Bioscience". We have fixed this typo. • Page 21 line 2: "Addegene" has to be replaced by "Addgene". We have fixed this typo. Figures • Figure 3: the schematic experimental design (Fig. 3A) could be enlarged to match the width of the images/graphs below. We have fixed this. • Figure 5: the reviewer suggests resizing/repositioning the graphs in Fig. 1A so that they match the width of those below. We have fixed this. • Figure S1D: In all the figures of the paper, the respective controls for the TS21 1 and TS21 2 lines are labelled as "WT1/WT2," while in these graphs, they are called "Ctrl1" and "Ctrl2." To ensure consistency throughout the paper, it is suggested to change the names in these graphs. We have fixed this. • Figure S4L: The graph is not very clear, especially regarding the significance reported at -50 pA, please modify the graphical visualization and/or add a legend in the caption. We have fixed this.

Reviewer #2 (Significance (Required)):

Nature and significance of the advance for the field. The results presented in the manuscript are potentially interesting and useful, but not completely novel (currents deregulation has already been highlighted in mouse models of Down Syndrome).

2.8) We thank the reviewer for this comment. While we agree that current deregulation has been observed in mouse models of Down syndrome, the novelty and significance of our study lie in demonstrating these alterations directly in human neurons using both in vitro and in vivo xenograft models.

This is a critical advance because the human cortex has distinct developmental and functional properties not fully recapitulated in mice. In fact, three recent studies have already highlighted significant defects mainly in excitatory neurons within the fetal human DS cortex (Vuong et al., bioRxiv, 2025; Risgaard et al., bioRxiv, 2025; Lattke et al, under revision). Our work builds directly on these observations by providing, for the first time, an electrophysiological and network-level characterization of these human-specific deficits.

Our findings thus provide translationally relevant insight that is not merely confirmatory but extends previous work by grounding it in a human cellular context.

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Referee #2

Evidence, reproducibility and clarity

Summary

The manuscript by Peter et al., reports on the neuronal activity and connectivity of iPSC-derived human cortical neurons from Down syndrome (DS) that is caused by caused by trisomy of the human chromosome 21 (TS21).

Major points:

Although the manuscript is potentially interesting, the results appear somehow preliminary and need to be corroborated by control experiments and quantifications of effects to fully sustain the conclusions.

(1) The authors have not assessed the percentage of WT and TS21 cells that acquire a neuronal or glia identity in their cultures. Indeed, the origin of alterations in network activity and connectivity observed in TS21 neurons could simply derive from reduced number of neurons arising from TS21 iPSC. Alternatively, the same alteration in network activity and connectivity could derive from a multitude of other factors including deficits in neuronal development, neurite extension, or intrinsic electrophysiological properties. In the current version of the manuscript, none of these has been investigated.

(2) Electrophysiological properties of TS21 and WT neurons at day 53/54 in vitro indicate an extremely immature stage of development (i.e. RMP between -36 and -27 mV with most of the cells firing a single action potential after current injection) in the utilized culture conditions: This is far from ideal for in vitro neuronal-network studies. Finally, reduced activity of HCN1 channels should be confirmed by specific recordings isolating or blocking the related current.

Main points highlighting the preliminary character of the study.

1) In Figure 1 immunofluorescence images of the neuronal differentiation markers (Tbr1, Ctip2 and Tuj1) are showed. However, no quantification of the percentage of cells expressing these markers for WT and TS21 neurons is reported. On the other hand, simple inspection of the representative images clearly seams to indicate a difference between the two genotypes, with TS21 cultures showing lower number of cells expressing neuronal markers. This quantification should be corroborated by a similar staining for an astrocyte marker (GFAP, but not S100b since is triplicated in DS). This is an extremely important point since it is obvious that any change in the percentage of neurons (or the neuron/astrocyte ratio) in the cultures will strongly affect the resulting network activity (shown in Figure 2) and the connectivity (showed in Figure 4). Possibly, the quantification should be done at the same time points of the calcium imaging experiments.

2) In Figure 2 the authors show some calcium imaging traces of WT and TS21 cultures at different time points. However, they again do not show any quantification of neuronal activity. A power spectra analysis is shown in Supplementary Figure 2, but only for WT cultures, while in Supplementary Figure 3 a comparison between WT and Ts21 power spectra is done, but only at the 50 day time point, while difference in synchrony are assessed at 60 days. At minimum, the author should include in main Figure 2 the quantification of the mean calcium event rate and mean event amplitude at the different time points and the power spectra analysis for both WT and TS21 cultures at the same timepoints.

Of note, the synchronized neuronal activity is present in WT cultures at day 60, but totally lost at subsequent time-points (70 and 80 days). The results of this later time points are different from previous data from the same lab (Kirwan et al., 2015). How might these data be explained? It would be important to rule out any potential issues with the health of the culture that could explain the loss of neuronal activity.It would be beneficial to check cell viability at the different time points to exclude possible confounding factors ? A propidium staining or a MTT assay would strongly improve the soundness of the calcium data.

3) In Figure 3 there is no quantification of the number and/or density of transplanted neurons for WT and TS21, but only representative images. As above, inspection of the representative images seems to show a decrease in cells labeled by the Tbr1 neuronal marker for TS21 cells. Moreover, the in vivo calcium imaging of transplanted WT and TS21 cells lacks most of the quantification normally done in calcium imaging experiments. Are the event rate and event amplitude different between WT and TS21 neurons ? The measure of neuronal synchrony by mean pixel correlation is not well explained, but it looks somehow simplistic. Neuronal synchrony can be more precisely measured by cross-correlation analysis or spike time tiling coefficients on the traces from single-neuron ROI rather than on all pixels in the field of view, as apparently was done here.

4) The results on reduced neuronal connectivity in Figure 3 look very striking. However, these results should be accompanied by control experiments to verify the number of neuronal cells and neurite extension in WT and Ts21 cultures. These two parameters could indeed strongly influence the results. As the cultures appear to grow in clusters, bright-field images and TuJ1 staining of the cultures will also greatly help to understand the degree of morphological interconnection between the clusters.

5) The authors performed RNA-seq experiments on day 50 cultures. Why the authors do not show the complete differential gene expression analysis, but only a small subset of genes? A comprehensive volcano plot and the complete list of identified genes with logFC and FDR values would be helpful. If possible, comparison of the present data (particularly on KCN and HCN expression changes) with published and publicly available expression datasets of other human or human Down syndrome iPSC-derived neurons or human Down syndrome brains will greatly increase the soundness of the present findings. In addition, the gene ontology (GO) results are mentioned in the text, but are not presented. Showing the complete GO analysis for both up and downregulated genes will help the reader to better understand the RNA-seq results. Notably, the results shown in Supplementary Figure on GRIN2A and GRIN2B expression (with values of 300-700 counts versus 2000-4000 counts, respectively) clearly indicate that in both WT and TS21 cultures the NMDA developmental switch has not occurred yet at the 50 days timepoint.

6) The measure of hyperpolarization-activated currents shown in Figure 5 lack proper control experiments. First, the hyperpolarizing current in TS21 cells do not reach a steady-state as the controls. The two curves are therefore hard to compare. To exclude possible difference in kinetic activation, the authors should have prolonged the current injection period (1-2 seconds). Second, to ultimately prove that such currents are mediated by HCN channels in WT cells the authors should perform some control experiments with a specific HCN blocker. A good example of a suitable protocol, with also current blockers to exclude all other possible current contributions, is the one reported in Matt et al Cell. Mol. Life Sci. 68, 125-137 (2011).

7) The manuscript lacks information on the statistical analysis used. Also, the numerosity of samples is not clear. Were the dots shown in some graph technical replicates from a single neuronal induction or were all independent neuronal inductions or a mix of the two ? Please clarify.

8) The method section lacks important information to guarantee reproducibility. Just a few examples: - Only electrophysiology methods for slice are reported, but not for in vitro culture. - Details on Laminin coating is lacking. What concentration was used ? Was poly-ornithine or poly-lysine used before Laminin coating ? - How long cells were switched to BrainPhys medium before calcium imaging ?

Minor point/typos etc.

Introduction

• Page 4 line 6: in the line "Trisomy 21 in humans commonly results in a range in developmental and morphological changes in the forebrain ..." "in" could be replaced by "of".
• Page 5 line 2: please remove "an" before the word "another".
• Page 5 line 2: please replace "ecitatory" with "excitatory"

Results

• Page 10 line 25: The concept of "pixel-wise" appears for the first time in this section and could be better introduced to facilitate the understanding of the experiment.
• In the "results" section, page 11 line 1 and 4, references are made to "Figure 4D" and "4F," but these figures do not appear to be present in the figure section. Upon reviewing the rest of the section, the data seem to refer to "Figure 3D" and "3E."

Discussion

• Page 15 line 20: please replace "synchronised" with "synchronized".
• Page 16 line 11: please replace "T21" with "TS21".

Methods

• Page 19 line 12: "Pens/Strep" has to be replaced by Pen/Strep.
• Page 20 line 20: "Tocris Biocience" has to be replaced by "Tocris Bioscience".
• Page 21 line 2: "Addegene" has to be replaced by "Addgene".

Figures

• Figure 3: the schematic experimental design (Fig. 3A) could be enlarged to match the width of the images/graphs below.
• Figure 5: the reviewer suggests resizing/repositioning the graphs in Fig. 1A so that they match the width of those below.
• Figure S1D: In all the figures of the paper, the respective controls for the TS21 1 and TS21 2 lines are labelled as "WT1/WT2," while in these graphs, they are called "Ctrl1" and "Ctrl2." To ensure consistency throughout the paper, it is suggested to change the names in these graphs.
• Figure S4L: The graph is not very clear, especially regarding the significance reported at -50 pA, please modify the graphical visualization and/or add a legend in the caption.

Significance

Nature and significance of the advance for the field. The results presented in the manuscript are potentially interesting and useful, but not completely novel (currents deregulation has already been highlighted in mouse models of Down Syndrome).

Work in the context of the existing literature. This work follows the line of evidence that characterizes Down Syndrome in human neurons (Huo, H.-Q. et al. Stem Cell Rep. 10, 1251-1266 (2018); Briggs, J. A. et al. Etiology. Stem Cells 31, 467-478 (2013)), both in vitro and in xenotransplanted mice, by corrborating some important findings already found in animal models (Stern, S., Segal, M. & Moses, E. EBioMedicine 2, 1048-1062 (2015); Cramer, N. P., Xu, X., F. Haydar, T. & Galdzicki, Z. Physiol. Rep. 3, e12655 (2015); Stern, S., Keren, R., Kim, Y. & Moses, E. http://biorxiv.org/lookup/doi/10.1101/467522 (2018) doi:10.1101/467522.

Audience. Scientists in the field of pre-clinical biomedical research, especially those working on neurodevelopmental disorders and iPSC-based non-animal models.

Field of expertise. In vitro electrophysiology, Neurodevelopmental disorders, Down Syndrome, ips cells.

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Referee #1

Evidence, reproducibility and clarity

Summary

The study investigates the neurodevelopmental impact of trisomy 21 on human cortical excitatory neurons derived from induced pluripotent stem cells (hiPSCs). Key findings include a modest reduction in spontaneous firing, a marked deficit in synchronized bursting, decreased neuronal connectivity, and altered ion channel expression-particularly a downregulation of voltage‐gated potassium channels and HCN1. These conclusions are supported by a combination of in vitro calcium imaging, electrophysiological recordings, viral monosynaptic tracing, RNA sequencing, and in vivo transplantation with two‐photon imaging.

Major Comments

• Convincing Nature of Key Conclusions: The study's conclusions are generally well supported by a diverse set of experimental approaches. However, certain claims regarding the intrinsic properties of the excitatory network would benefit from further qualification. In particular, the assertion that reduced synchronization is solely attributable to altered ion channel expression might be considered somewhat preliminary without additional corroborative experiments.
• One major limitation of the current experimental design is the reliance on predominantly excitatory neuronal cultures derived from hiPSCs. Although the authors convincingly demonstrate differences in network synchronization and connectivity between trisomic (TS21) and control neurons, the almost exclusive focus on excitatory cells limits the physiological relevance of the in vitro network. In the developing cortex, interneurons and astrocytes play crucial roles in modulating network excitability, synaptogenesis, and plasticity. Therefore, incorporating these cell types-either through co-culture systems or through directed differentiation protocols that yield a more heterogeneous neuronal population-could help to determine whether the observed deficits are intrinsic to excitatory neurons or are compounded by a lack of proper inhibitory regulation and glial support.
• Furthermore, the assessment of neuronal connectivity via pseudotyped rabies virus tracing, while innovative, has inherent limitations. The quantification of connectivity as a ratio of red-to-green fluorescence pixels may be influenced by differential viral infection efficiencies, variations in the expression levels of the TVA receptor, or even by the lower basal activity levels observed in TS21 cultures. Complementary approaches-such as electron microscopy for synaptic density analysis or functional connectivity measurements using multi-electrode arrays (MEAs)-could provide additional structural and functional insights that would validate the rabies tracing data.
• Qualification of Claims: Some conclusions, particularly those linking specific ion channel dysregulation (e.g., HCN1 loss) directly to network deficits, might be better presented as preliminary. The authors could temper their language to indicate that while the evidence is suggestive, the mechanistic link remains to be fully established.
• Need for Additional Experiments: Additional experiments that could further consolidate the current findings include:
  • Inclusion of Inhibitory Neurons or Co-culture Systems: Incorporating interneurons or astrocytes would help determine whether the observed deficits are solely intrinsic to excitatory neurons.
  • Alternative Connectivity Assessments: Complementing the rabies virus tracing with electron microscopy or multi-electrode array (MEA) recordings would add structural and functional validation of the connectivity differences.
  • Extended Temporal Profiling: Monitoring network activity over a longer developmental window would clarify whether the observed deficits represent a delay or a permanent alteration in network maturation.
• Reproducibility and Statistical Rigor: The methods and data presentation are largely clear, with adequate replication and appropriate statistical analyses. Nonetheless, a more detailed description of the experimental replicates, particularly regarding the viral tracing and in vivo transplantation studies, would enhance reproducibility. The availability of raw data and scripts for calcium imaging analysis would also further support independent verification.

Minor Comments

• Experimental Details:

Minor revisions could include clarifying the infection efficiency and expression levels of the viral constructs used in connectivity assays to rule out technical variability. - Literature Context:

The authors reference prior studies appropriately; however, integrating a brief discussion comparing their findings with alternative DS models (e.g., organoids or other hiPSC-derived systems) would improve contextual clarity. - Presentation and Clarity:

Figures are generally clear,.But the manuscript contains a minor labeling error. On page 13, the figure is erroneously labeled as "Fig6A", whereas, based on the context and corresponding data, it should be "Fig5A". I recommend that the authors correct this mistake to ensure consistency and avoid potential confusion for readers.

Significance

• Nature and Significance of the Advance:

The work offers a substantial conceptual advance by providing a mechanistic link between trisomy 21 and impaired neuronal network synchronization. Technically, the study integrates state-of-the-art imaging, electrophysiology, and transcriptomic profiling, thereby offering a multifaceted view of DS-related neural dysfunction. Clinically, the findings have the potential to inform future therapeutic strategies targeting network connectivity and ion channel function in Down syndrome. - Context in the Existing Literature:

The study builds on previous observations of altered network activity in DS patients and DS mouse models (e.g., altered EEG synchronization and reduced synaptic connectivity). It extends these findings to human-derived neuronal models, thus bridging a gap between clinical observations and molecular/cellular mechanisms. Relevant literature includes studies on DS neurodevelopment and the role of ion channels in synaptic maturation. - Target Audience:

The reported findings will be of interest to researchers in neurodevelopmental disorders, Down syndrome, and ion channel physiology. Additionally, the study may attract the attention of those working on hiPSC-derived models of neurological diseases, as well as clinicians interested in the pathophysiology of DS. - Keywords and Field Contextualization:

Keywords: Down syndrome, trisomy 21, neuronal connectivity, synchronized network activity, hiPSC-derived cortical neurons, ion channel dysregulation.

The type of relationship I want to have with my reciever is a friendly, honest professional work relationship. I believe if there is trust within the relationship, circumstances like the one present right now will minimize the issue of me not being able to attend the internship on Monday.

I want to achieve the outcome of quickly informing my boss that I will be unable to make it in order to ensure the meeting is still prepared well either by my boss or another coworker.

The outcome I want to achieve is to send the message that I apoligize for not being able to attend in the morning. I want it to be known I was preparing and already had some of the legwork done, however, a uncertain circumstance occured and there is nothing I can do. I want to make sure the boss can see I am sorry and will be back as soon as possible.

This is something that resonated with me. I was initially very shocked to hear about the stepmother first cutting off the toe of her eldest daughter then the heel of her other. These actions are extreme compared to the versions I grew up with. This to me serves to provide a reflection of how different the times were, where the brothers Grimm had a much harder and more violent life, we live lives of relative comfort. I find it interesting how this is reflected in the changes of the stories over time and wonder how the story will adapt in the future. -Tristan Hill

The message may change the results of the meeting with the client because my boss needs to be prepared.

My boss needs to know that I am sick, I cannot make it, when I might be next available, and any information they may not have about the client or how to prepare for them.

Receivers want to understand and act on the message being sent. This means they need to know information to act on your message. she needs to know you will be sick and unable to make it into work. 2. This is important to your receiver because she needs to be informed that you will not be present and how that will affect her, as well as the team or group. your absence means someone else taking up your work and handling the meeting. Power: less power than boss Familiarity: unfamiliar formality: very formal quality: trustworthy, stable, new, cordial

It is interesting how we as a species have given objects meaning based on the average experience with those products.

eLife Assessment

This work reports the characterization of newly identified genetic variants of SLC4A1 in patients with distal renal tubular acidosis. Cell culture studies supplemented with histological analysis of a previously established disease mouse model provide convincing evidence that some of the variants increase intracellular pH, reduce ATP synthesis, and attenuate autophagic degradative flux. The study is valuable in establishing a mechanistic framework for future exploration of the link between intracellular pH and mutations in SLC4A1 in vivo.

Reviewer #1 (Public review):

Summary:

This study is an evaluation of patient variants in the kidney isoform of AE1 linked to distal renal tubular acidosis. Drawing on observations in the mouse kidney, this study extends findings to autophagy pathways in a kidney epithelial cell line.

Strengths:

Experimental data are convincing and nicely done.

The revised manuscript incorporates most of the reviewer recommendations and presents a more cohesive story that is easier to read and assess. The data are convincing, of suitable quality and nicely presented. Statistical evaluation is rigorous. The link between kAE1 mutants and cell metabolism and autophagy is novel and provides insights on pathological observations in dRTA.

Reviewer #2 (Public review):

Context and significance:

Distal renal tubular acidosis (dRTA) can be caused by mutations in a Cl-/HCO3- exchanger (kAE1) encoded by the SLC4A1 gene. The precise mechanisms underlying the pathogenesis of the disease due to these mutations is unclear, but it is thought that loss of the renal intercalated cells (ICs) that express kAE1 and/or aberrant autophagy pathway function in the remaining ICs may contribute to the disease. Understanding how mutations in SLC4A1 affect cell physiology and cells within the kidney, a major goal of this study, is an important first step to unraveling the pathophysiology of this complex heritable kidney disease.

Summary:

The authors identify a number of new mutations in the SLC4A1 gene in patients with diagnosed dRTA that they use for heterologous experiments in vitro. They also use a dRTA mouse model with a different SLC4A1 mutation for experiments in mouse kidneys. Contrary to previous work that speculated dRTA was caused mainly by trafficking defects of kAE1, the authors observe that their new mutants (with the exception of Y413H) traffic and localize at least partly to the basolateral membrane of polarized heterologous mIMCD3 cells, an immortalized murine collecting duct cell line. They go on to show that the remaining mutants induce abnormalities in the expression of autophagy markers and increased numbers of autophagosomes, along with an alkalinized intracellular pH. They also reported that cells expressing the mutated kAE1 had increased mitochondrial content coupled with lower rates of ATP synthesis. The authors also observed a partial rescue of the effects of kAE1 variants through artificially acidifying the intracellular pH. Taken together, this suggests a mechanism for dRTA independent of impaired kAE1 trafficking and dependent on intracellular pH changes that future studies should explore.

Strengths:

The authors corroborate their findings in cell culture with a well characterized dRTA KI mouse and provide convincing quantification of their images from the in vitro and mouse experiments. The data largely support the claims as stated. Some of the mutants induce different strengths of effects on autophagy and the various assays than others, and it is not clear why this is from the data in the manuscript. The authors provide discussion of potential reasons for these differences that future studies could explore.

Weaknesses:

The pH effects of their mutants are only explored in vitro, and the in vitro system has a number of differences from a living mouse kidney or ex vivo kidney slice.

Reviewer #3 (Public review):

Summary:

The authors have identified novel dRTA causing SLC4A1 mutations and studied the resulting kAE1 proteins to determine how they cause dRTA. Based on a previous study on mice expressing the dRTA kAE1 R607H variant, the authors hypothesize that kAE1 variants cause an increase in intracellular pH which disrupts autophagic and degradative flux pathways. The authors clone these new kAE1 variants and study their transport function and subcellular localization in mIMCD cells. The authors show increased abundance of LC3B II in mIMCD cells expressing some of the kAE1 variants, as well as reduced autophagic flux using eGFP-RFP-LC3. These data, as well as the abundance of autophagosomes, serve as the key evidence that these kAE1 mutants disrupt autophagy. Furthermore, the authors demonstrate that decreasing the intracellular pH abrogates the expression of LC3B II in mIMCD cells expressing mutant SLC4A1. Lastly, the authors argue that mitochondrial function, and specifically ATP synthesis, is suppressed in mIMCD cells expressing dRTA variants and that mitochondria are less abundant in AICs from the kidney of R607H kAE1 mice. Overall, the authors provide evidence about how new kAE1 mutants may cause dRTA.

Strengths:

The authors cloned novel dRTA causing kAE1 mutants into expression vectors to study the subcellular localization and transport properties of the variants. The immunofluorescence images are generally of high quality and the authors do well to include multiple samples for all of their western blots.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary: 

This study is an evaluation of patient variants in the kidney isoform of AE1 linked to distal renal tubular acidosis. Drawing on observations in the mouse kidney, this study extends findings to autophagy pathways in a kidney epithelial cell line. 

Strengths: 

Experimental data are convincing and nicely done.

Thank you

Weaknesses: 

Some data are lacking or not explained clearly. Mutations are not consistently evaluated throughout the study, which makes it difficult to draw meaningful conclusions.

We have revised our manuscript to clarify some earlier explanations and provided rationale for focusing on specific variants throughout the study.

Reviewer #2 (Public review):

Context and significance: 

Distal renal tubular acidosis (dRTA) can be caused by mutations in a Cl-/HCO3- exchanger (kAE1) encoded by the SLC4A1 gene. The precise mechanisms underlying the pathogenesis of the disease due to these mutations are unclear, but it is thought that loss of the renal intercalated cells (ICs) that express kAE1 and/or aberrant autophagy pathway function in the remaining ICs may contribute to the disease. Understanding how mutations in SLC4A1 affect cell physiology and cells within the kidney, a major goal of this study, is an important first step to unraveling the pathophysiology of this complex heritable kidney disease. 

Summary: 

The authors identify a number of new mutations in the SLC4A1 gene in patients with diagnosed dRTA that they use for heterologous experiments in vitro. They also use a dRTA mouse model with a different SLC4A1 mutation for experiments in mouse kidneys. Contrary to previous work that speculated dRTA was caused mainly by trafficking defects of kAE1, the authors observe that their new mutants (with the exception of Y413H, which they only use in Figure 1) traffic and localize at least partly to the basolateral membrane of polarized heterologous mIMCD3 cells, an immortalized murine collecting duct cell line. They go on to show that the remaining mutants induce abnormalities in the expression of autophagy markers and increased numbers of autophagosomes, along with an alkalinized intracellular pH. They also reported that cells expressing the mutated kAE1 had increased mitochondrial content coupled with lower rates of ATP synthesis. The authors also observed a partial rescue of the effects of kAE1 variants through artificially acidifying the intracellular pH. Taken together, this suggests a mechanism for dRTA independent of impaired kAE1 trafficking and dependent on intracellular pH changes that future studies should explore. 

Strengths: 

The authors corroborate their findings in cell culture with a well-characterized dRTA KI mouse and provide convincing quantification of their images from the in vitro and mouse experiments

Thank you  

Weaknesses: 

The data largely support the claims as stated, with some minor suggestions for improving the clarity of the work. Some of the mutants induce different strengths of effects on autophagy and the various assays than others, and it is not clear why this is from the present manuscript, given that they propose pHi and the unifying mechanism

We have modified our manuscript to discuss the various strengths of the mutants and emphasize that alteration of cytosolic pH by kAE1 variants may not be the only mechanism leading to dRTA.  

Reviewer #3 (Public review):

Summary: 

The authors have identified novel dRTA causing SLC4A1 mutations and studied the resulting kAE1 proteins to determine how they cause dRTA. Based on a previous study on mice expressing the dRTA kAE1 R607H variant, the authors hypothesize that kAE1 variants cause an increase in intracellular pH, which disrupts autophagic and degradative flux pathways. The authors clone these new kAE1 variants and study their transport function and subcellular localization in mIMCD cells. The authors show increased abundance of LC3B II in mIMCD cells expressing some of the kAE1 variants, as well as reduced autophagic flux using eGFP-RFP-LC3. These data, as well as the abundance of autophagosomes, serve as the key evidence that these kAE1 mutants disrupt autophagy. Furthermore, the authors demonstrate that decreasing the intracellular pH abrogates the expression of LC3B II in mIMCD cells expressing mutant SLC4A1. Lastly, the authors argue that mitochondrial function, and specifically ATP synthesis, is suppressed in mIMCD cells expressing dRTA variants and that mitochondria are less abundant in AICs from the kidney of R607H kAE1 mice. While the manuscript does reveal some interesting new results about novel dRTA causing kAE1 mutations, the quality of the data to support the hypothesis that these mutations cause a reduction in autophagic flux can be improved. In particular, the precise method of how the western blots and the immunofluorescence data were quantified, with included controls, would enhance the quality of the data and offer more supportive evidence of the authors' conclusions. 

Strengths: 

The authors cloned novel dRTA causing kAE1 mutants into expression vectors to study the subcellular localization and transport properties of the variants. The immunofluorescence images are generally of high quality, and the authors do well to include multiple samples for all of their western blots.

Thank you

Weaknesses: 

Inconsistent results are reported for some of the variants. For example, R295H causes intracellular alkalinization but also has no effect on intracellular pH when measured by BCECF. The authors also appear to have performed these in vitro studies on mIMCD cells that were not polarized, and therefore, the localization of kAE1 to the basolateral membrane seems unlikely, based upon images included in the manuscript. Additionally, there is no in vivo work to demonstrate that these kAE1 variants alter intracellular pH, including the R607H mouse, which is available to the authors. The western blots are of varying quality, and it is often unclear which of the bands are being quantified. For example, LAMP1 is reported at 100kDa, the authors show three bands, and it is unclear which one(s) are used to quantify protein abundance. Strikingly, the authors report a nonsensical value for their quantification of LCRB II in Figure 2, where the ratio of LCRB II to total LCRB (I + II) is greater than one. The control experiments with starvation and bafilomyocin are not supportive and significantly reduce enthusiasm for the authors' findings regarding autophagy. There are labeling errors between the manuscript and the figures, which suggest a lack of vigilance in the drafting process.

The R295H variant was identified in a dRTA patient and as such, it was important to report it. However, this is the first mutation located in the amino-terminus of the protein, which may be involved in protein-protein interactions, so other mechanisms may cause dRTA for this variant. We have therefore modified our manuscript to state that alteration of cytosolic pH may not be the only mechanism leading to dRTA. At this time, we are not able to measure cytosolic pH in vivo and hope to be able to do it in the future.

In our revised manuscript, we also show cell surface biotinylation results supporting that plasma membrane abundance of the kAE1 S525F and R589H variants is not significantly different than WT in non-polarized mIMCD3 cells (Figure 3 A&B), in line with the predominant basolateral localization of the variants in polarized cells (Figure 1C). Therefore, these two mutant proteins are not mis-trafficked in non-polarized cells.  Finally, we have clarified which bands have been used for quantification and corrected quantifications (including ratio measurements).

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

(1) R295H is recessively inherited, whereas Y413H is dominantly inherited: this is interesting and may be linked to their cellular expression and function. Is this information known for the other mutations examined in this study? 

The S25F and R589H dRTA variants have both been reported to exhibit autosomal dominant inheritance. This information is now updated in lines 146 and 158-159.

(2) R589H expression levels are evaluated in the Western blot of Figure 1, but localization and activity are not examined in Figure 2. However, R589H is included in autophagy experiments shown in later figures. Similarly, mutant R607H is the subject of several experiments further into the manuscript, but no initial analysis is provided for this variant. 

Protein abundance and localization of the R589H mutant in mIMCD3 cells have been shown in our previous publication in Supplementary Fig 5D and Supplementary Fig 2J [1]. This now indicated on lines 158-159. Our previous paper also presented a detailed study of the R607H dRTA mutant, the mouse model corresponding to the human R589H mutation. This is now indicated on lines 70, 118-119 and 180. The present study builds upon those published findings.

(3) This inconsistency is confusing, detracts from the usefulness of the study, and makes the comparative analysis of mutations incomplete. It is difficult to extrapolate from published studies in MDCK1 cells, which show different results on trafficking. 

The mIMCD3 cell line, which more closely resembles the physiology of the mouse collecting duct than MDCK cells, was selected for this study and our previous one [1]. Accordingly, the results obtained are better aligned with in vivo evidence. In contrast, differences in mutant protein expression and localization observed in other cell lines, like the MDCK cells, are likely attributable to differences in their cellular origin. 

(4) In Figure 2, could the authors explain why total LC3B is graphed for the data shown in mouse lysates, whereas the ratio of bands is analysed for cell lysates? Both sets of data show the two LC3B bands.

Total LC3B levels were significantly increased in the mutant compared to WT; however, no significant difference was observed in the lipidation ratio. For this reason, that graph is not shown in the main paper but has been included in the Supplementary Figure 1D. 

(5) In Figure 3, representative fluorescence images should be shown for all cell lines.

We have now included representative immunofluorescence images for all cell lines in Figure 3C.

(6) pH effects: Suggest that steady state pHi (Figure 3E) and rate of alkalization (Figure 1F) would be more effective together in Figure 1. The authors should show data for the effect of nigericin on cytoplasmic pH in Figure 3. If the rate of alkalinization in the mutant cells is reduced, shouldn't the intracellular steady state pH be more acidic? A cartoon depicting the transporter activity in the cell and the expected changes in pHi would be helpful. Is there a way to activate/inhibit NHE1 and rescue the effect of the mutant kAE1? It is unclear if the link between the mutant kAE1 and mitochondrial ATP production is a consequence of the intracellular pH or an indirect effect.

We opted to keep the effect of nigericin on pHi in Supplementary Fig1A given that Figure 3 already contains 11 panels. Also, in intercalated cells, the kAE1 protein physiologically exports 1 molecule of bicarbonate in exchange of 1 chloride ion import hence a reduced transport activity would result in a more alkaline intracellular pH. To clarify this point, we have included a diagram in Figure 1E as suggested. However, to calculate the rate of intracellular alkalinisation, the transporter is functioning in the opposite direction, i.e. extruding chloride and importing bicarbonate (see methods protocol for transport assay). Therefore, in this assay (Figure 1G), a defective chloride/bicarbonate activity results in a reduced rate of intracellular alkalinisation rate. This is now explained on lines 169-172.

Disruption of NHE1 function would impair sodium homeostasis and as such, potentially affect the activity of other proteins associated with acid-base balance and autophagy in collecting duct cells. Therefore, any resulting effects may not be confidently attributed specifically to the mutant kAE1. With nigericin, we aimed to alter pHi while affecting the least possible other ion concentration. Due to space considerations, Figure 1 has been reorganised to include the rate of alkalinisation and pHi (panels F and G). 

Reviewer #2 (Recommendations for the authors):

(1) The authors could improve the readability of this manuscript for a general audience by clarifying and summarizing the respective phenotype(s)/effect(s) of the different mutants in some kind of table in the main figures. It is hard to keep track of the different disease mutants alongside the KI mouse mutations, as the text frequently discusses multiple mutants at a time. 

As requested, we added two tables (Supplementary Tables 1 & 2) in Supplementary files summarizing the data obtained in this study. We hope this will help the readership to keep track of each variant’s phenotype.

(2) The subtitle of the results section of Figure 2 should be reworded to reflect that  whole kidney lysates are used for the KI mice and not the other mutants.

As requested, the title in the Results section has been modified (lines 178-179).

(3) More discussion of why the different mutants cause different strengths of phenotypes should be included.

Different variants induce different degree of functional defects as seen in Figure 1F & G. The kAE1 R295H, the only amino acid substitution in the amino-terminal cytosol causing dRTA, does not affect the transporter’s function or cells’ pHi. Therefore, this variant may cause dRTA via a different pathway than transport-defective S525F or partially inactive R589H variants that both affect pHi. Our study does not exclude that dRTA may be caused by other defects than pHi alterations, including defective proteinprotein interactions. This discussion is now included in the manuscript on lines 386-391.

Reviewer #3 (Recommendations for the authors):

In general, I found the subject matter of this manuscript interesting and of value to the scientific community. The interpretation of the data and how much it supports the conclusion that "kAE1 variants increases pHi which alters mitochondrial function and leads to reduced cellular energy levels that eventually attenuate energy-dependent autophagic pathways" is largely incomplete. There are significant concerns about the quantification of Western blot data. Additionally, including the R607H variant in the in vitro experiments would improve the interpretation and extrapolation of in vitro data to the kidney.

We apologize for the confusion with R589H and R607H variants. The R607H mutant is the murine ortholog to the human R589H dRTA variation. To clarify this, we have added this information on line 180, in addition to lines 118-119 and line 70.

Suggestions:

(1) Can an anion replacement experiment be performed in the mIMCD cells (no Cl or no HCO3) to determine that bicarbonate transport through AE1 is responsible for the reduced ATP rates in Figure 5? Inclusion of WT +dox control would be helpful to convince the reader of the effects.

Because Seahorse real-time cell metabolism ATP rates measurements require specific and patented buffers with un-specified compositions, it was not possible to modify the Cl⁻ or HCO₃⁻ content during the ATP measurement assay. All cell lines, including empty vector cells (EV) were treated with doxycycline; thus, WT + dox was already included. The empty vector cell line treated with doxycycline allowed the exclusion of specific effects of doxycycline on mitochondrial activity as a control. This is now clarified in Figure 5 legend, lines 655-656.

(2) Can the authors measure pHi in fresh kidney sections from the R607H mouse?

Unfortunately, we are not currently able to measure pHi in fresh kidney sections and although we recognize it would benefit greatly to our study, establishing a new collaboration to perform this measurement would significantly delay the publication of this work; therefore, these results will not be available for the present manuscript. 

(3) Does pH 7.0 media have any effect on autophagy, as shown in Figure 3? Why was pH 6.6 selected?

The idea was to artificially acidify pHi in mutant cell lines (that have a steady state alkaline pHi) and assess whether this acidification corrects autophagy defects. We first determined that incubation in cell culture medium at pH 6.6 with 0.033 µM nigericin (final potassium concentration: 168 mM) for 2 hours provided optimal conditions, i.e. ensuring cell viability over the 2-hour period while effectively lowering intracellular pH to 6.9, as demonstrated in Supplementary Figure 1A-C.

(4) In vitro experiments should be performed on polarized cells with kAE1 properly inserted in the basolateral membrane. Experiments on subconfluent, non-polarized cells do not support the hypothesis that transport functions of AE1 initiate the cascade of events attributed to these SLC4A1 mutations.

To address this point, we have performed cell surface biotinylations on 70-80 % confluent mIMCD3 cells expressing kAE1 WT, S525F or R589H mutants and show that cell surface abundance of the mutants is not significantly different from the WT protein. This is now shown in Figure 3 A&B. As cell surface biotinylation provides a more quantitative assessment of protein cell surface abundance, we have removed the immunofluorescence images from non-polarised cells and replaced them with representative immunoblots from a cell surface biotinylation assay.

Concerns:

(1) No information about the B1 ATPase antibody used.

Now provided in Supplementary Material, ATP6V1B1 Antibody from Bicell cat#20901.

(2) No actin band in Figure 1E (as prepared).

Actin bands are provided for each blot in Figure 1D.

(3) Figures 1E and 1F are labelled wrong in the figure versus the results section. 

Thank you for letting us know, this is now corrected.

(4) The cortical sections shown in Figure 4 for the KI/KI do not appear to have the morphology of a CCD. The authors may want to consider including glomeruli to convince the reader of the localization of the tubules. Same concern with Figure 5G and I. The WT image in 5G does not have the morphology of a CCD. Principal cells should be predominant, and ICs should be dispersed.

Both figures 4 and 5 have been updated with images showing glomeruli (light blue “G” on figure) with neighbour and dispersed IC staining.

(5) The quantification of LAMP1 in Figure 4 is unclear. How did the authors determine the boundary of AICs, and how did they calculate the volume of lysosomes? If a zstack was used, how are the authors sure that their 10um section includes the entire AIC?

The quantification of LAMP1 is detailed under “Image analysis”, then “Volocity” sections in Supplementary Material. The boundary of A-IC was manually detected in Volocity based on the presence of the H⁺-ATPase before Volocity analysis for lysosomal volume as described in the Methods.

The 10 micron sections are expected to include full AIC as well as partial AIC, but the frequency of these events should be the same between WT and variants’ sections, therefore they were all included in the analysis if cells displayed H⁺-ATPase signal. 

(6) Figure 5: There is no description of how ATP rates are calculated from the provided traces.

We used Agilent Seahorse XF ATP rate assay kit for this experiment. In this assay, the total ATP rate is the sum of ATP production rate from both glycolysis and oxidative phosphorylation. Glycolysis releases protons in a 1:1 ratio with ATP hence the glycolytic ATP rate is calculated from the glycolytic proton efflux rate (glycoPER). GlycoPER is determined by subtracting respiration linked proton efflux from total proton efflux by inhibiting complex I and III. This information is now added to Supplementary Material, in the “Metabolic Flux analysis” section.

(7) Figure labels in Figure 5 are wrong. It seems 5H (as presented) should actually be labeled 5G. In 5H (G?), why did some cells not have any TOM20 pixel intensity for S525F and R589H variants?

Confocal image acquisition in this experiment was kept under the same settings to allow comparison between samples. Therefore, some cells show dimer fluorescence than others. From the figure 5 panels, all cells showed TOM 20 pixel intensity. Figure 5H panel has been relabelled Figure 5G.

(8) In Figure 2, the summary graphs show analysis of more samples than are visible on the included western blots. What is the rationale for this? Why does S525F have 9 samples in BafA1 while R295H only has 3 (2H)? Yet, R295H has 6 samples in 2I. In 2D, S525F has at least 9 samples. Explain.

Figure 2A-C shows representative immunoblots, among several ones independently conducted. Therefore, the final number of samples is higher than showed on Figure 2. This is now indicated in Figure 2 legend, line 603. It became clear quite early in our study that the recessive kAE1 R295H variant does not behave similarly to the other variants studied, maybe because it affects the cytosolic domain, so we did not perform as many replicates for this variant as we did for the others. However, we felt it was valuable to the research community to report the characterization of this variant and decided to keep it in our study. 

(9) In general, the actin loading does not appear to be equal between samples. And some figures show the same actin blot twice (2A, C) while some show independent actin bands for LC3B and p62. Equal loading seems a fairly significant control, considering the importance of quantification in the figures.

In addition to performing protein assays, we systematically conduct immunoblot with anti-b-actin antibody to control for loading variability. When possible, two or three proteins, including actin, are detected on the same blot, when molecular weight differ enough. This sometimes results in b-actin being used as a loading control for two different proteins, as seen on Figure 2A and 2C. This is now indicated on lines 605606.

(10) In the Supplemental Figure 2, which band is being quantified for mature CTSD at 33kDa? Same for intermediate CTSD. The quantification of V-ATPase seems questionable based on the actin variance shown in the blot. Surely the ratio of the fourth sample is greater than 1.

Supplementary Figure 2 has been updated to include arrows indicating which band was selected for the quantification. After verifying the measurements of band intensities from “Image Lab” quantification software, we confirm the results, including that fourth KI/KI sample has a ratio of 0.78 (Adj Total Band Vol (Int), lanes 10). Screen shots of quantifications are attached below.

Author response image 1.

Author response image 2.

(11) Why are the experiments performed on non-confluent IMCD cells? Figure 1D shows good basolateral localization of AE1, yet the other experiments in the manuscript appear to use IMCD cells in low confluent states, without proper localization of AE1. Figure 3A shows AE1 dispersed throughout the cytoplasm. Why have the authors decided to study the effects of an anion exchanger without it being properly localized to the basolateral membrane? Shouldn't all experiments be performed in polarized IMCDs? If AE1 isnt properly in the membrane, and the cells do not have defined apico-basolateral polarity, then what role can AE1-mediated intracellular pH change have on the results of the experiments? Were the pHi experiments in 3E performed on polarized cells? Or even 1F?

To address this point, we have performed cell surface biotinylations on 70-80 % confluent mIMCD3 cells expressing kAE1 WT, S525F or R589H mutants and show that cell surface abundance of the mutants is not significantly different from the WT protein. This is now shown in Figure 3A & B. As it provides a more quantitative assessment of protein cell surface abundance, we have removed the immunofluorescence images from non-polarised cells and replaced them with a representative immunoblot from a cell surface biotinylation assay.

(12) As mentioned in the public comments, how is the ratio A/(A+B) greater than 1? With A and B > 0. In Figure 3, the data is reasonable, but in Figure 2, the data is simply impossible. What is the explanation for this phenomenon? Why was this presentation of data approved? Is it supposedly a fold of WT, like 2K and 2L? Is the reader also to believe that total LC3B is 2-fold greater in KI/KI mice, as shown in 2K? My eyes, though not densitometry equipment, cannot confirm this. The actin bands are not equal. Yet again, there are 4 lanes of KI/KI mice, but the quantification shows 5 samples.

The ratios in figure 2D, 2F, 2H and 2L have been re-calculated and corrected. As indicated above, immunoblots are representative and quantification of additional blots has been included in the graphs.

(12) Spelling error Figure 4B: cels.

Corrected

References 

(1) Mumtaz, R. et al. Intercalated Cell Depletion and Vacuolar H+-ATPase Mistargeting in an Ae1 R607H Knockin Model. Journal of the American Society of Nephrology 28, 1507–1520 (2017).

eLife Assessment

This important study reports convincing evidence of associations between 35 polygenic indices (PGIs) for social, behavioural, and psychological traits, as well as other health conditions (e.g., BMI) and all-cause mortality, based on data from Finnish population-based surveys and a twin cohort linked to administrative registers. PGIs for education, depression, alcohol use, smoking, BMI, and self-rated health showed the strongest associations with all-cause mortality, in the order of ~10% increment in risk per PGI standard deviation. Effect sizes from twin-difference analyses tended to be slightly larger than those from population cohorts, a pattern opposite that generally observed when testing PGI associations with their target phenotypes, and supporting the robustness of findings to confounding by population stratification.

Reviewer #1 (Public review):

Lahtinen et al. evaluated the association between polygenic scores and mortality. This question has been intensely studied (Sakaue 2020 Nature Medicine, Jukarainen 2022 Nature Medicine, Argentieri 2025 Nature Medicine), where most studies use PRS as an instrument to attribute death to different causes. The presented study focuses on polygenic scores of non-fatal outcomes and separates the cause of death into "external" and "internal". The majority of the results are descriptive, and the data doesn't have the power to distinguish effect sizes of the interesting comparisons: (1) differences between external vs. internal (2) differences between PGI effect and measured phenotype.

Comments on revised version:

The authors answered my concerns well. I don't have any further comments.

Reviewer #2 (Public review):

Summary:

This study provides a comprehensive evaluation of the association between polygenic indices (PGIs) for 35 lifestyle and behavioral traits and all-cause mortality, using data from Finnish population- and family-based cohorts. The analysis was stratified by sex, cause of death (natural vs. external), age at death, and participants' educational attainment. Additional analyses focused on the six most predictive PGIs, examining their independent associations after mutual adjustment and adjustment for corresponding directly measured baseline risk factors.

Strengths:

Large sample size with long-term follow-up.

Use of both population- and family-based analytical approaches to evaluate associations.

Comments on revised version:

I am happy with the revision. No further comments.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Lahtinen et al. evaluated the association between polygenic scores and mortality. This question has been intensely studied (Sakaue 2020 Nature Medicine, Jukarainen 2022 Nature Medicine, Argentieri 2025 Nature Medicine), where most studies use PRS as an instrument to attribute death to different causes. The presented study focuses on polygenic scores of non-fatal outcomes and separates the cause of death into "external" and "internal". The majority of the results are descriptive, and the data doesn't have the power to distinguish effect sizes of the interesting comparisons: (1) differences between external vs. internal (2) differences between PGI effect and measured phenotype. I have two main comments:

(1) The authors should clarify whether the p-value reported in the text will remain significant after multiple testing adjustment. Some of the large effects might be significant; for example, Figure 2C

We have now added Benjamini-Hochberg multiple-testing adjusted p-values in the text each time we present nominal p-values. Additionally, supplementary tables S5 and S6 provide multiple-adjusted p-values for all analysed PGIs.

Although this was not always the case, many comparisons remained significant after multiple testing adjustments, especially in Figure 2C that the reviewer commented on. In the revised version, we have placed more emphasis on describing these HRs that have low p-values after multiple-test adjustment. The revised text for Figure 2C in the Results section now reads:

Panel C analyses mortality in three age-specific follow-up periods. The PGIs were more predictive of death in younger age groups, although the difference between the 25–64 and 65–79 age groups was small, except for the PGI of ADHD (HR=1.14, 95% CI 1.08; 1.21 for 25–64-year-olds; HR=1.04, 95% CI 1.00; 1.08 for 65–79-year-olds; p=0.008 for difference, p=0.27 after multiple-testing adjustment). PGIs predicted death only negligibly among those aged 80+, and the largest differences between the age groups 25–64 and 80+ were for PGIs of self-rated health (HR 0.87, 95% CI 0.82; 0.93 for 25–64-year-olds, HR 1.00, 95% CI 0.94; 1.04 for 80+ year-olds, p=2*10^-4 for difference, p=0.006 after multiple-testing adjustment), ADHD (HR 1.14, 95% CI 1.08; 1.21 for 25–64-year-olds, HR 0.99, 95% CI 0.95; 1.03 for 80+ year-olds, p=7*10^-4 for difference, p=0.012 after multiple-testing adjustment) and depressive symptoms (HR 1.12, 95% CI 1.06; 1.18 for 25–64-year-olds, HR 1.00, 95% CI 0.96; 1.04 for 80+ year-olds, p=0.002 for difference, p=0.032 after multiple-testing adjustment). Additionally, the difference in HRs between these age groups achieved significance after multiple testing adjustment at the conventional 5% level for PGIs of cigarettes per day, educational attainment, and ever smoking.

We have also included the recent study by Argentieri et al. (2025) in the literature review, which was missing from our previous version. We appreciate the reference. Other references mentioned were already included in the previous version of the manuscript.

(note that the small prediction accuracy of PGI in older age groups has been extensively studied, see Jiang, Holmes, and McVean, 2021, PLoS Genetics).

We would like to thank the reviewer for suggesting the relevant reference by Jiang et al. We have now expanded on the discussion of age-specific differences in the discussion section and included this reference.

(2) The authors might check if PGI+Phenotype has improved performance over Phenotype only. This is similar to Model 2 in Table 1, but slightly different.

The reviewer raises an interesting angle to approach the analysis. We have now added an analysis assessing the information criteria and the significance of improvement between nested models in Supplementary table S8. All the tested PGI+phenotype models show improvement over the phenotype-only model that is statistically significant at all conventional levels when tested by likelihood-ratio tests between nested models . Additionally,  improvement was found when using Akaike and Bayesian (Schwarz) information criteria (albeit sometimes modest in size). We have added a passage in the results section briefly summarising this analysis:

Supplementary table S8 presents information criteria and significance tests on corresponding models. Models with PGI+phenotype (Models 2a–f) showed improvement over models with the phenotype only (Models 1a, 1c, 1e, 1g, 1i, 1k, with a p=0.0006 or lower) in terms of both Akaike information criterion (AIC) as well as Bayesian (Schwarz) information criterion (BIC) with a p=0.0006 or lower in all comparisons. The full Model 4 again showed improvement over the model with all PGIs jointly (Model 3b, with a p=0.0002 or p=0.00002, depending on continuous/categorical phenotype measurement), which had a lower AIC but not BIC.

Reviewer #2 (Public review): 

Summary:

This study provides a comprehensive evaluation of the association between polygenic indices (PGIs) for 35 lifestyle and behavioral traits and all-cause mortality, using data from Finnish population- and family-based cohorts. The analysis was stratified by sex, cause of death (natural vs. external), age at death, and participants' educational attainment. Additional analyses focused on the six most predictive PGIs, examining their independent associations after mutual adjustment and adjustment for corresponding directly measured baseline risk factors.

Strengths:

Large sample size with long-term follow-up.

Use of both population- and family-based analytical approaches to evaluate associations.

Weaknesses:

It is unclear whether the PGIs used for each trait represent the most current or optimal versions based on the latest GWAS data.

To our reading, this comment is closely related to the “recommendations for the author” number 3 by reviewer 2, and we thus address them together. 

If the Finnish data used in this study also contributed to the development of some of the PGIs, there is a risk of overestimating their associations with mortality due to overfitting or "double-dipping." Similar inflation of effect sizes has been observed in studies using the UK Biobank, which is widely used for PGI construction.

To our reading, this comment is closely related to the “recommendations for the author” 4 by reviewer 2, and we thus address them together.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Specific comments:

(1) Cited reference 1 also investigated the PRS association with life span; cited reference 8 explains PRS association with healthy lifespan. Can authors be clearer about what is new in the context of these references? Specifically, what are the PGIs studied here that were not analyzed in the cited analyses?

Although some previous studies on the topic do exist, our analysis arguably has novelty in touching upon several unstudied or scarcely studied themes. These include:

A set of PGIs focusing on social, psychological, and behavioural phenotypes or PGIs for typically non-fatal health conditions.

An assessment of direct genetic effects/ confounding with a within-sibship design.

An assessment of potential heterogeneous effects by several socio-demographic characteristics.

An analysis of external causes of deaths (which can be hypothesised to be particularly relevant here, given the choice of our PGIs not focusing directly on typical causes of death).

A detailed assessment of the interplay of the most predictive PGIs with their corresponding phenotypes.

We have substantially revised the Introduction section focusing on making these novel contributions more explicit.

(2) In the Methods section, it is not very clear why the authors specifically study the "within-sibship" samples. Is this for avoiding nurturing effects from parental genotypes or for controlling assortative mating? The authors should clarify the rationale behind the design.

The substance-related rationale behind this approach was briefly discussed in the Introduction section while in the Methods section, we focused more on the technical description of our analyses. However, it is certainly worthwhile to clarify to the reader why within-sibship methods have been used. The revised passage in the methods section now states:

“In addition to this population sample, we used a within-sibship analysis sample to assess the extent of direct and indirect genetic associations captured by the PGIs, as discussed in the introduction.”

(3) Residual correlations of PGIs were no more than 0.050..." As a minor comment, since PGIs is a noisy variable, the correlation would be low; however, I don't think there are better ways to evaluate Cox assumptions, and in many cases, this assumption is not correct for strong predictors.

Yes, these points are true. Overall, it is often implausible that empirical distributions exactly match distributional assumptions in statistical models. For example, it may not be realistic to expect that the mortality hazards across categories of independent variables stay exactly proportional during long mortality-follow-ups; some deviations from constant proportions are almost inevitable. However, there are reasonable grounds to argue that in case of moderate violations of the proportional hazards assumption, the estimates still remain interpretable for practical uses. They can be read as approximating average relative hazards over the study period (for discussion, see pages 42–47 in Allison P. 2014. Event history and survival analysis: Regression for longitudinal event data (second edition). Thousand Oaks: SAGE).

(4) "PGI of ADHD (HR=1.08 95%CI 1.04;1.11 among men; HR=1.01 95%CI 0.97;1.05 among women; p=0.012 for difference)." Is this difference significant after multiple testing correction?

We have presented multiple-testing adjusted p-values together with nominal ones in this and in all other instances where they are mentioned in the text. Additionally, Supplementary tables S5–S6 present multiple-adjusted p-values for each PGIs studied.

(5) "Panel D displays that most PGIs had stronger associations with external (accidents, violent, suicide, and alcohol related deaths) than natural causes of death." Similar to the comment above, are there any results that are significantly different between internal and external?

We have added the p-values of those variables that had larger differences in the revised text. Quoting from the revised article: “The HR differences between external and natural causes of death were nominally significant at the conventional 5% level for cannabis use (p=0.016), drinks per week (p=0.028), left out of social activity (p=0.029), ADHD (p=0.031), BMI (p=0.035) and height (p=0.049), but none of these differences remained significant after adjusting for 35 multiple tests. “

(6) Table 1: The effect of the phenotype is stronger than the PGI; this is expected as PGI is a weak predictor and can be considered as "noised" measurement of true genetic value (Becker 2021 Nature Human behavior). Is there a way to adjust for the impact of noise in PGI at tagging genetic value and compare if the PGI effect is different from the phenotype effect?

PGIs are certainly imperfect measures that contain a lot of noise. However, extracting new information from what is unknown is an extremely demanding exercise, and still further complicated for example, by that we do not know the exact benchmark of total genetic effect we should be aiming at. Different methods of heritability estimation, for instance, often give dramatically differing results – for reasons that are still up to scrutiny.

We are thus not familiar with a method that could achieve satisfactory answer for this challenging task.

Reviewer #2 (Recommendations for the authors):

(3) Justification and Selection of PGIs:

For several traits, such as BMI, multiple polygenic indices (PGIs) are currently available. The criteria used to select specific PGIs for this study are not clearly described. A more systematic and reproducible approach-for example, leveraging metadata from the PGS Catalog-could strengthen the justification for PGI selection and enhance the study's generalizability.

There are numerous PGIs developed in the extensive GWAS literature, but a finite set of PGIs always needs to be chosen for any analysis. The rationale behind our decision to include every PGI from the repository of Becker et al. 2021 (full reference in the manuscript, see also https://www.thessgac.org/pgi-repository) that was available for the Finnish data (including the possibility to exclude overlapping samples, see our response to the next comment for more discussion) was to provide rigorous analysis by limiting the researchers degrees of freedom in arbitrarily choosing PGIs. Although it would have been tempting to not use some PGIs that were not expected to substantially correlate with mortality, we believe that our conservative strategy increases the credibility of the reported p-values, particularly the multiple adjustment should now work as intended. 

We also mention now this rationale when discussing the chosen PGIs in the methods section: “As the independent variables of main interest, we used 35 different PGIs in the Polygenic Index repository by Becker et al., which were mainly based on GWASes using UK Biobank and 23andMe, Inc. data samples, but also other data collections. They were tailored for the Finnish data, i.e., excluding overlapping individuals between the original GWAS and our analysis and performing linkage-disequilibrium adjustment. We used every single-trait PGI defined in the repository (except for subjective well-being, for which we were unable to obtain a meta-analysis version that excluded the overlapping samples). By limiting the researchers’ freedom in selecting the measures, this conservative strategy should increase the validity of our estimates, particularly with regards to multiple-testing adjusted p-values.”

(4) Overlap Between PGI Training Data and Study Sample:

The authors should describe any overlap between the data used to develop the PGIs and the current study sample. If such overlap exists, it may lead to overestimation of effect sizes due to "double-dipping." A discussion of this issue and its potential implications is warranted, as similar concerns have been raised in studies using UK Biobank data.

This is, fortunately, not a concern of our analysis. Overlapping samples were excluded in creating the PGIs that we used. We have now described this more clearly in the revised methods section.

(1) Clarify the Methodology for Family-Based Cox Analysis:

It is unclear what specific method was used to perform Cox regression in the family-based analysis. Please provide additional methodological details. ”

We have described the method further and added an additional reference in the revision. The text now stands:

“We compared these models to the corresponding within-sibship models, using the sibship identifier as the strata variable. This method employs a sibship-specific (instead of a whole-sample-wide baseline hazard in the population models) baseline hazard, and corresponds to a fixed-effects model in some other regression frameworks (e.g., linear model with sibship-specific intercepts)”

(2) Clarify Timing of Measured Risk Factors Relative to Follow-Up:

The main text should provide more detailed information regarding the timing of data collection for directly measured risk factors. Specifically, it should be clarified whether the measurements used correspond to the first available data for each individual after the start of follow-up, or if a different criterion was applied.

BMI, self-rated health, alcohol consumption and smoking status were measured at the baseline survey of each dataset. Education was registered as the highest completed degree up to the end of 2019. Depression was a composite of survey self-report (at the time of the baseline survey), as well as depression-related medicine purchases and hospitalizations over a two-year period before the start of the individual’s follow-up.

We have added more comprehensive information on the measurement of the phenotypes of interest in Supplementary table 2, including the timing of the measurement.

Could be made by some ribbon company like Alpad who sold Olivetti compatible ribbons/spools.

6mm diameter center holes on spools are indicative of a Gr4 typewriter spool.

via u/Koponewt at https://www.reddit.com/r/typewriters/comments/1qcocn1/does_anyone_recognise_this_spool/

test

McPhee draws a direct parallel between the rock and the Pilgrims, suggesting that migration and displacement define both the land and the people who claim it.

This opening line establishes the central idea that the rock itself is foreign and displaced, mirroring the experience of the Pilgrims and introducing the tension between scientific reality and national myth.

I think this is emphasizing that meaning is temporary and subject to time despite the reverence people attach to it.

I think this is the contrast of the symbolic meaning of the rock mentioned earlier. This shows the rock was used as an object than a symbol. So it shows that meaning is assigned by the people over time.

This is an example of how people assign meaning to physical landscapes. Like we talked about in class, there is no evidence that this rock is anything else so people can easily assign meaning and stick to it.

Ordinary things can be considered sacred, depending on what happened and when.

Shows that the task of preserving the past for future generations is not one that is taken lightly.

Interesting parallel. What I gather from this is that the land itself, just as the colonists, was originally European, and is now populated again by Europeans.

Interesting to compare the Plymouth Rock to the actual human pilgrims.

Blatant disrespect for the customs and traditions of the Natives

Could be seen as a metaphor for our nation becoming more divided over time.

Interesting symbolism separating the Crown from the Colony.

SLAY

interesting note - could link to miskell

metion of walton and his important

shows how industry was the main focus!

significant quote to reference

good quote of reference

historiography on welsh seaside resorts were originally sprase despite their huge presence

the focus is usually only on the docks - the industrial aspects are looked at but not the leisure aspect

The operating systems are essential in controlling hardware and offering a platform to the software applications. Knowledge of operating systems is an essential aspect of computer science education, and students should be familiar with it. The course assists in the creation of knowledge in system architecture, resource management and interaction of software thus allowing the students to acquire skills that are critical in these careers in software development, system administration, and network management.

The textbook has been set up successfully, and the annotations feature operates as expected. It is now possible for me to add remarks and observations to the content, which will improve my learning experience and enable me to follow the key concepts all through the book. An operating system (OS) is an important interface between hardware and software applications of a computer. It takes care of hardware resources such as CPU, memory, and storage by making sure that programs and processes are performed efficiently.

This Operating systems concepts text book also gives an extensive overview of the fundamentals and architectures in the design of an OS. This provides a clear idea of the mediatory role that operating systems assume in the interaction between computer hardware and computer software which is crucial to a novice making a study about system architecture and programming.

מדוע צריך את האקסל הזה? מיותר לדעתי

start of the jim craw laws

This section made me realize that storing personal data on social media is not just a technical question, but also an ethical one. For example, age can be stored as a number, but platforms still need to decide how precise it should be and how it might be used or misused. It also made me question whether some data, like exact address, really needs to be stored at all given the privacy risks.

In fact, I have always been puzzled about the collection of information such as "region" and "age". Is it really "necessary" for companies to collect such information? These pieces of information do not guarantee that the account is used by a real person - fake accounts can also randomly generate combinations of these pieces of information, but it will increase the risk of user information leakage

I found the discussion about representing gender as data especially thoughtful, because it shows how technical design decisions can have real social consequences. Treating gender as a simple binary might make data easier to process, but it can erase people’s identities and experiences. I also like the idea of combining preset options with an “other” field, since it balances inclusivity with the need for usable and consistent data.

I like how this example shows that even something that seems simple like a “data field” actually involves a lot of value judgments. Every way of storing gender has tradeoffs between inclusivity, usability, and data cleanliness, and there isn’t a purely technical solution. It also made me stop and think about whether collecting certain data is even necessary in the first place.

Can we remove this line for US?

Skill 和 skills

examples

Data constraint plays a really important role in many social media platforms as they help set realistic boundaries when a person fills out their personal information. This also helps companies keep a record of what age the users usually are that uses their social media. Moreover, it all help prevent any possible trolls who will put random informations just to use the social media.

This is an important thing to consider when choosing how we store data and how we want to represent it. It is unrealistic to for example have someone who is 1000 years old. Another good case is if we only want to include a specific set of data but the user enters invalid characters which may distort our dataset.

Dont understand this formula

The pixels that only have three color components have always made me really curious, as there is only green, blue,e and red, ed but once they are in a group,oup tcane to create a whole new different color that sometimes seems impossible. Additionally, one of the most intruiging thing about these grids is that with only these three colors, they can create the color white.

It’s cool to see how images are really just grids of pixels with RGB values, and even something like microRGB fits into that same idea of breaking color down into tiny components. Thinking about images this way makes them feel a lot less mysterious and more like something you can actually work with in code.

It’s interesting to think about how sound is really just a list of numbers that tell a speaker how to move, moment by moment, to recreate a noise or a voice. Once you see it that way, audio feels a lot less abstract and more like something you can store, edit, and mess with just like any other data.

I notice this sort of glitch sometimes when I'm using the app BeReal. When the notification goes off for everyone at the same time (no matter what time zone you are), the way the content is displayed to you is based entirely on what country you're currently in. Example- I have a friend who was visiting South Korea, and when the notification went off for us to take a photo through the app, it indicated that hers was 17 hours late. Interesting how there's a lack of solutions when technology has advanced so fast.

I find it so intriguing that, by simply posting a photo or tweet, a platform can gather immense amounts of data from the user. This type of data (metadata) is typically accessible to those who know their way around a computer, and one can assume how dangerous it can be when given to the wrong people.

As an international student, I have experience with this. Many social media platforms display the posting time based on the time zone of the viewer, i.e. the device time zone, when the publisher posts. That is to say, if you view the release time of the same tweet in different time zones, you will find that their release time has changed

I recently worked on a project using sound. All of the sound was stored as numbers like described here. The whole process of measuring physical sound waves is very interesting to learn about.

Images, sounds, videos, and dates require complex representations that simplify reality; choices such as compression and time zone definitions shape what data we see and how we interpret social media activity, raising ethical concerns about accuracy, context, and fairness.

I find the discussion about the ambiguity of yesterday particularly insightful because it highlights how objective data like a timestamp is actually dependent on the observer's context, if a social media platform's automated system flags behavior based on a specific day, but that day starts and ends at different times for the user and the server. This creates a data friction that can lead to unfair outcomes, which indicates that information systems aren't neutral tools, they are specific temporal assumptions, and things might change quickly and might not reflect the lived experience of global users.

This clearly explains the use and importance of metadata. Although I often hear the term in computer science classes, I hadn’t fully understood why it is so important. In this context, I’ve learned that beyond the visible content in images, sounds, or videos, there is additional information such as time, location, or device type. This metadata may not interest the viewer directly but can be valuable for platform management, data analysts, or other stakeholders.

epidemiology focuses on preventing these diseases from occurring.

Very very nice - industry and leisurewere instricibly linked for the often working-class miners visiting Barry - their life was industry and so fittingly, their leisure (and pleasure) was watching their hardwork be shipped off across the globe from a beautiful vantage point on the beaches of Barry

Very interesting! Mitskell' arguement suggests how port and resort could co-exist peacefully, Croll goes further to argue that port and resort aided the growth of the other. In a prior chapter, Croll goes into depth with how the island's origins as a bathing resort brung attention to the area for industrialization, this was prohibited by the later owner Lord Windsor, however, upon his approval, the industrilisation of the area resulted in a boost for tourism which had suffered under Lord Windsor's ban!

Bathing machines were a significantly good sign - used for ladies to change and bath - it wasn't just a rough plae but a place where ladies could bathe and feel safe

idk need to waffle but brain cant lol

Highlights the leisure too - these were not tourists but residents. seaside resorts also became a place of genral recreation like the big parks in london - this is something mitskell doesn't highlight, but could be due to the resorts purpose moreso as a high-class resort - it still woulda had workers in the town tho

Very good - he highlights the weaknesses of primary sources available instead of making sweeping assumptions

Due to the ban, natural tourism of the beach was restricted - industrialisation helped revive this through the new 'industrial tourists', which then re-awakened the natural tourism again, people going against the visitor ban to barry island

Here we see a shift from a tourism based on natural beauty to industrial wonder - industrialisation here became a tourist attraction

Interesting use of primary source to back up his argument

Unlike Mitskell's article, Croll highlights how industrial elements could become a key part of the leisure industry through the advertisement of industrial ports as a tourist attraction, leisure and industrialisation having a strong and positive relationship in this example.

Naming a section of his work 'industrial tourists', Croll highlights a strog relationship between industrialisation and leisure through the new industrial workers who sought to utilise their new spending power and freetime through a trip to seaside resorts like Barr

Unlike Mitskell's choice of case study, Croll's decision of Barry has clear differences, it alludes greater to the impact of external factors like landowners on the relationship between industrialisation and tourism, with Lord Windsor, upon his purchase of Barry Island, Croll notes, banning visitors from the Island and prohibiting the becoming industrialisation of the Island. As such, Croll's choice of case study is interesting, and broadens the (complexities) of studying Welsh seaside resorts further. Through the case study, he suggests how landowners often decided the nature of the relationship between industrialisation and leisure, with the ammenities required for each at the whim of (blah)

Alludes to a differing relationship - industrialisation had caused the creation of large settlements of workers, who, with the railway, could now access (and afford) to engage in leisure activities in Barry

Industrialisation had hampered and then helped tourism, altho now largely for a more different class. Swansea seemed to remain more for the upperclass aided by industrialisation. This was unlike Barry which saw it's clientel shift more towards the woring classes.

Mitskell's point never really saw this break and overtake of industry, relationship was less frictional i think

• mitskell's case study doesn't seem to have this

confliction between industrialisation and leisure

Evidence of friction - the tourists didn't always like the industrialisation. Barry was especially known for it's lack of urbanisation and natural beuaty

Recommending Mitskell's article in a footnote at th eend of his introduction, Croll takes a similar view to his 2011 predeccessor, the example of Barry further proo that 'tourism could flourish alongside a commercial port', (do thing from option thing).

Written nine years after Mitskell's article, Croll places his work neatly within the historiography of the Welsh seaside, highlighting Borsay and Walton's thesis of the (expand girly). Like Mitskell, Borsay is a key historian of reference, and as such, it is unsurprising that both article's appear to highlight a less frictional relationship between industry and leisure through their different case studys.

eLife Assessment

This work significantly advances our understanding of chromatin organization within regions of repetitive sequences in the parasitic protozoan Trypanosoma brucei. Using cutting edge interdisciplinary tools, the authors provide compelling evidence for two discrete types of repetitive DNA element-associated proteins- one set involved in essential centromere function; and, the other involved in glycoprotein antigenic variation via homologous recombination. Thus, these fundamental findings have implications for this parasite's biology, and for therapeutic targeting in kinetoplastid diseases. This work will be exciting to those in the centromere/mitosis and parasite immunity fields.

[Editors' note: this paper was reviewed by Review Commons.]

Reviewer #1 (Public review):

Summary:

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeat-containing intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Strengths and Weaknesses:

The manuscript was previously reviewed through Review Commons. As noted there, the experiments are well controlled, the claims are well supported, and the methods are clearly described. The conclusions are convincing. All concerns I raised have been addressed except one (minor point #8):

"The way the authors mapped the ChIP-seq data is potentially problematic when analyzing the same repeat type in different genomic regions. Reads with multiple equally good mapping positions were assigned randomly. This is fine when analyzing repeats by type, independent of genomic position, which is what the authors do to reach their main conclusions. However, several figures (Fig. 3B, Fig. 4B, Fig. 5B, Fig. 7) show the same repeat type at specific genomic locations." Due to the random assignment, all of these regions merely show the average signal for the given repeat. I find it misleading that this average is plotted out at "specific" genomic regions.<br /> Initially, I suggested a workaround, but the authors clarified why the workaround was not feasible, and their explanation is reasonable to me. That said, the figures still show a signal at positions where they can't be sure it actually exists. If this cannot be corrected analytically, it should at least be noted in the figure legends, Results, or Discussion.

Importantly, the authors' conclusions do not hinge on this point; they are appropriately cautious, and their interpretations remain valid regardless.

Significance:

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with mini-chromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Comments on revised version:

All my recommendations have been addressed.

Reviewer #2 (Public review):

The Trypanosoma brucei genome, like that of other eukaryotes, contains diverse repetitive elements. Yet, the chromatin-associated proteome of these regions remains largely unexplored. This study represents a very important conceptual and technical advancement by employing synthetic TALE DNA-binding proteins fused to YFP to selectively capture proteins associated with specific repetitive sequences in T. brucei chromatin. The data presented here are convincing, supported by appropriate controls and a well-validated methodology, aligned with current state-of-the-art approaches.

The authors used synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in T. brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to identify specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and a protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosomes.

This study represents a significant conceptual and technical advancement. To the best of our knowledge, it is the first report of employing TALE-YFP for affinity-based detection of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding the organization in these important regions of the trypanosomal chromatin and provides the foundation for investigating the functional roles of associated proteins in parasite biology. These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as to scientists investigating the roles of repetitive genomic elements in chromatin structure and their functional role in higher eukaryotes.

Importantly, any essential or unique interacting partners identified using the approach employed here, could serve as a potential target for therapeutic intervention in severe tropical diseases cause by kinetoplastids.

Author response:

Point-by-point description of the revisions:

Reviewer #1 (Evidence, reproducibility and clarity):

Summary

In this article, the authors used the synthetic TALE DNA binding proteins, tagged with YFP, which were designed to target five specific repeat elements in Trypanosoma brucei genome, including centromere and telomeres-associated repeats and those of a transposon element. This is in order to detect and identified, using YFP-pulldown, specific proteins that bind to these repetitive sequences in T. brucei chromatin. Validation of the approach was done using a TALE protein designed to target the telomere repeat (TelR-TALE) that detected many of the proteins that were previously implicated with telomeric functions. A TALE protein designed to target the 70 bp repeats that reside adjacent to the VSG genes (70R-TALE) detected proteins that function in DNA repair and the protein designed to target the 177 bp repeat arrays (177R-TALE) identified kinetochore proteins associated T. brucei mega base chromosomes, as well as in intermediate and mini-chromosomes, which imply that kinetochore assembly and segregation mechanisms are similar in all T. brucei chromosome.

Major comments:

Are the key conclusions convincing?

The authors reported that they have successfully used TALE-based affinity selection of proteinassociated with repetitive sequences in the T. brucei genome. They claimed that this study has provided new information regarding the relevance of the repetitive region in the genome to chromosome integrity, telomere biology, chromosomal segregation and immune evasion strategies. These conclusions are based on high-quality research, and it is, basically, merits publication, provided that some major concerns, raised below, will be addressed before acceptance for publication.

(1) The authors used TALE-YFP approach to examine the proteome associated with five different repetitive regions of the T. brucei genome and confirmed the binding of TALE-YFP with Chip-seq analyses. Ultimately, they got the list of proteins that bound to synthetic proteins, by affinity purification and LS-MS analysis and concluded that these proteins bind to different repetitive regions of the genome. There are two control proteins, one is TRF-YFP and the other KKT2-YFP, used to confirm the interactions. However, there are no experiment that confirms that the analysis gives some insight into the role of any putative or new protein in telomere biology, VSG gene regulation or chromosomal segregation. The proteins, which have already been reported by other studies, are mentioned. Although the author discovered many proteins in these repetitive regions, their role is yet unknown. It is recommended to take one or more of the new putative proteins from the repetitive elements and show whether or not they (1) bind directly to the specific repetitive sequence (e.g., by EMSA); (2) it is recommended that the authors will knockdown of one or a small sample of the new discovered proteins, which may shed light on their function at the repetitive region, as a proof of concept.

The main request from Referee 1 is for individual evaluation of protein-DNA interaction for a few candidates identified in our TALE-YFP affinity purifications, particularly using EMSA to identify binding to the DNA repeats used for the TALE selection. In our opinion, such an approach would not actually provide the validation anticipated by the reviewer. The power of TALE-YFP affinity selection is that it enriches for protein complexes that associate with the chromatin that coats the target DNA repetitive elements rather than only identifying individual proteins or components of a complex that directly bind to DNA assembled in chromatin.

The referee suggests we express recombinant proteins and perform EMSA for selected candidates, but many of the identified proteins are unlikely to directly bind to DNA – they are more likely to associate with a combination of features present in DNA and/or chromatin (e.g. specific histone variants or histone post-translational modifications). Of course, a positive result would provide some validation but only IF the tested protein can bind DNA in isolation – thus, a negative result would be uninformative.

In fact, our finding that KKT proteins are enriched using the 177R-TALE (minichromosome repeat sequence) identifies components of the trypanosome kinetochore known (KKT2) or predicted (KKT3) to directly bind DNA (Marciano et al., 2021; PMID: 34081090), and likewise the TelR-TALE identifies the TRF component that is known to directly associate with telomeric (TTAGGG)n repeats (Reis et al 2018; PMID: 29385523). This provides reassurance on the specificity of the selection, as does the lack of cross selectivity between different TALEs used (see later point 3 below). The enrichment of the respective DNA repeats quantitated in Figure 2B (originally Figure S1) also provides strong evidence for TALE selectivity.

It is very likely that most of the components enriched on the repetitive elements targeted by our TALE-YFP proteins do not bind repetitive DNA directly. The TRF telomere binding protein is an exception – but it is the only obvious DNA binding protein amongst the many proteins identified as being enriched in our TelR-TALE-YFP and TRF-YFP affinity selections.

The referee also suggests that follow up experiments using knockdown of the identified proteins found to be enriched on repetitive DNA elements would be informative. In our opinion, this manuscript presents the development of a new methodology previously not applied to trypanosomes, and referee 2 highlights the value of this methodological development which will be relevant for a large community of kinetoplastid researchers. In-depth follow-up analyses would be beyond the scope of this current study but of course will be pursued in future. To be meaningful such knockdown analyses would need to be comprehensive in terms of their phenotypic characterisation (e.g. quantitative effects on chromosome biology and cell cycle progression, rates and mechanism of recombination underlying antigenic variation, etc) – simple RNAi knockdowns would provide information on fitness but little more. This information is already publicly available from genome-wide RNAi screens (www.tritrypDB.org), with further information on protein location available from the genome-wide protein localisation resource (Tryptag.org). Hence basic information is available on all targets selected by the TALEs after RNAi knock down but in-depth follow-up functional analysis of several proteins would require specific targeted assays beyond the scope of this study.

(2) NonR-TALE-YFP does not have a binding site in the genome, but YFP protein should still be expressed by T. brucei clones with NLS. The authors have to explain why there is no signal detected in the nucleus, while a prominent signal was detected near kDNA (see Fig.2). Why is the expression of YFP in NonR-TALE almost not shown compared to other TALE clones?

The NonR-TALE-YFP immunolocalisation signal indeed is apparently located close to the kDNA and away from the nucleus. We are not sure why this is so, but the construct is sequence validated and correct. However, we note that artefactual localisation of proteins fused to a globular eGFP tag, compared to a short linear epitope V5 tag, near to the kinetoplast has been previously reported (Pyrih et al, 2023; PMID: 37669165).

The expression of NonR-TALE-YFP is shown in Supplementary Fig. S2 in comparison to other TALE proteins. Although it is evident that NonR-TALE-YFP is expressed at lower levels than other TALEs (the different TALEs have different expression levels), it is likely that in each case the TALE proteins would be in relative excess.

It is possible that the absence of a target sequence for the NonR-TALE-YFP in the nucleus affects its stability and cellular location. Understanding these differences is tangential to the aim of this study.

However, importantly, NonR-TALE-YFP is not the only control for used for specificity in our affinity purifications. Instead, the lack of cross-selection of the same proteins by different TALEs (e.g. TelR-TALE-YFP, 177R-TALE-YFP) and the lack of enrichment of any proteins of interest by the well expressed ingiR-TALE-YFP or 147R-TALE-YFP proteins each provide strong evidence for the specificity of the selection using TALEs, as does the enrichment of similar protein sets following affinity purification of the TelR-TALE-YFP and TRF-YFP proteins which both bind telomeric (TTAGGG)n repeats. Moreover, control affinity purifications to assess background were performed using cells that completely lack an expressed YFP protein which further support specificity (Figure 6).

We have added text to highlight these important points in the revised manuscript:

Page 8:

“However, the expression level of NonR-TALE-YFP was lower than other TALE-YFP proteins; this may relate to the lack of DNA binding sites for NonR-TALE-YFP in the nucleus.”

Page 8:

“NonR-TALE-YFP displayed a diffuse nuclear and cytoplasmic signal; unexpectedly the cytoplasmic signal appeared to be in the vicinity the kDNA of the kinetoplast (mitochrondria). We note that artefactual localisation of some proteins fused to an eGFP tag has previously been observed in T. brucei (Pyrih et al, 2023).”

Page 10:

Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4). Thus, the most enriched proteins are specific to TelR-TALE-YFP-associated chromatin rather than to the TALE-YFP synthetic protein module or other chromatin.

(3) As a proof of concept, the author showed that the TALE method determined the same interacting partners enrichment in TelR-TALE as compared to TRF-YFP. And they show the same interacting partners for other TALE proteins, whether compared with WT cells or with the NonR-TALE parasites. It may be because NonR-TALE parasites have almost no (or very little) YFP expression (see Fig. S3) as compared to other TALE clones and the TRF-YFP clone. To address this concern, there should be a control included, with proper YFP expression.

See response to point 2, but we reiterate that the ingi-TALE -YFP and 147R-TALE-YFP proteins are well expressed (western original Fig. S3 now Fig. S2) but few proteins are detected as being enriched or correspond to those enriched in TelR-TALE-YFP or TRF-YFP affinity purifications (see Fig. S9). Therefore, the ingi-TALE -YFP and 147R-TALE-YFP proteins provide good additional negative controls for specificity as requested. To further reassure the referee we have also included additional volcano plots which compare TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP to the ingiR-TALE-YFP affinity selection (new Figure S8). As with No-YFP or NonR-TALE-YFP controls, the use of ingiR-TALE-YFP as a negative control demonstrates that known telomere associated proteins are enriched in TelR-TALE-YFP affinity purification, RPA subunits enriched with 70R-TALE-YFP and Kinetochore KKT poroteins enriched with 177RTALE-YFP. These analyses demonstrate specificity in the proteins enriched following affinity purification of our different TALE-YFPs and provide support to strengthen our original findings.

We now refer to use of No-YFP, NonR-TALE-YFP, and ingiR-TALE -YFP as controls for comparison to TelR-TALE-YFP, 70R-TALE-YFP or 177R-TALE-YFP in several places:

Page10:

“Moreover, a similar set of enriched proteins was identified in TelR-TALE-YFP affinity purifications whether compared with cells expressing no YFP fusion protein (No-YFP), the NonR-TALE-YFP or the ingiR-TALE-YFP as controls (Fig. S7B, S8A; Tables S3, S4).”

Page 11:

“Thus, the nuclear ingiR-TALE-YFP provides an additional chromatin-associated negative control for affinity purifications with the TelR-TALE-YFP, 70R-TALE-YFP and 177R-TALE-YFP proteins (Fig. S8).”

“Proteins identified as being enriched with 70R-TALE-YFP (Figure 6D) were similar in comparisons with either the No-YFP, NonR-TALE-YFP or ingiR-TALE-YFP as negative controls.”

Top Page 12:

“The same kinetochore proteins were enriched regardless of whether the 177R-TALE proteomics data was compared with No-YFP, NonR-TALE or ingiR-TALE-YFP controls.”

Discussion Page 13:

“Regardless, the 147R-TALE and ingiR-TALE proteins were well expressed in T. brucei cells, but their affinity selection did not significantly enrich for any relevant proteins. Thus, 147R-TALE and ingiR-TALE provide reassurance for the overall specificity for proteins enriched TelR-TALE, 70R-TALE and 177R-TALE affinity purifications.”

(4) After the artificial expression of repetitive sequence binding five-TALE proteins, the question is if there is any competition for the TALE proteins with the corresponding endogenous proteins? Is there any effect on parasite survival or health, compared to the control after the expression of these five TALEs YFP protein? It is recommended to add parasite growth curves, for all the TALE proteins expressing cultures.

Growth curves for cells expressing TelR-TALE-YFP, 177R-TALE-YFP and ingiR-TALE-YFP are now included (New Fig S3A). No deficit in growth was evident while passaging 70R-TALE-YFP, 147R-TALE-YFP, NonR-TALE-YFP cell lines (indeed they grew slightly better than controls).

The following text has been added page 8:

“Cell lines expressing representative TALE-YFP proteins displayed no fitness deficit (Fig. S3A).”

(5) Since the experiments were performed using whole-cell extracts without prior nuclear fractionation, the authors should consider the possibility that some identified proteins may have originated from compartments other than the nucleus. Specifically, the detection of certain binding proteins might reflect sequence homology (or partial homology) between mitochondrial DNA (maxicircles and minicircles) and repetitive regions in the nuclear genome. Additionally, the lack of subcellular separation raises the concern that cytoplasmic proteins could have been co-purified due to whole cell lysis, making it challenging to discern whether the observed proteome truly represents the nuclear interactome.

In our experimental design, we confirmed bioinformatically that the repeat sequences targeted were not represented elsewhere in the nuclear or mitochondrial genome (kDNA). The absence of subcellular fractionation could result in some cytoplasmic protein selection, but this is unlikely since each TALE targets a specific DNA sequence but is otherwise identical such that cross-selection of the same contaminating protein set would be anticipated if there was significant non-specific binding. We have previously successfully affinity selected 15 chromatin modifiers and identified associated proteins without major issues concerning cytoplasmic protein contamination (Staneva et al 2021 and 2022; PMID: 34407985 and 36169304). Of course, the possibility that some proteins are contaminants will need to be borne in mind in any future follow-up analysis of proteins of interest that we identified as being enriched on specific types of repetitive element in T. brucei. Proteins that are also detected in negative control, or negative affinity selections such as No-YFP, NoR-YFP, IngiR-TALE or 147R-TALE must be disregarded.

(6) Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

As mentioned earlier, the author claimed that this study has provided new information concerning telomere biology, chromosomal segregation mechanisms, and immune evasion strategies. But there are no experiments that provides a role for any unknown or known protein in these processes. Thus, it is suggested to select one or two proteins of choice from the list and validate their direct binding to repetitive region(s), and their role in that region of interaction.

As highlighted in response to point 1 the suggested validation and follow up experiments may well not be informative and are beyond the scope of the methodological development presented in this manuscript. Referee 2 describes the study in its current form as “a significant conceptual and technical advancement” and “This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology.”

The Referee’s phrase ‘validate their direct binding to repetitive region(s)’ here may also mean to test if any of the additional proteins that we identified as being enriched with a specific TALE protein actually display enrichment over the repeat regions when examined by an orthogonal method. A key unexpected finding was that kinetochore proteins including KKT2 are enriched in our affinity purifications of the 177R-TALE-YFP that targets 177bp repeats (Figure 6F). By conducting ChIP-seq for the kinetochore specific protein KKT2 using YFP-KKT2 we confirmed that KKT2 is indeed enriched on 177bp repeat DNA but not flanking DNA (Figure 7). Moreover, several known telomere-associated proteins are detected in our affinity selections of TelRTALE-YFP (Figure 6B, FigS6; see also Reis et al, 2018 Nuc. Acids Res. PMID: 29385523; Weisert et al, 2024 Sci. Reports PMID: 39681615).

Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

The answer for this question depends on what the authors want to present as the achievements of the present study. If the achievement of the paper was is the creation of a new tool for discovering new proteins, associated with the repeat regions, I recommend that they add a proof for direct interactions between a sample the newly discovered proteins and the relevant repeats, as a proof of concept discussed above, However, if the authors like to claim that the study achieved new functional insights for these interactions they will have to expand the study, as mentioned above, to support the proof of concept.

See our response to point 1 and the point we labelled ‘6’ above.

Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

I think that they are realistic. If the authors decided to check the capacity of a small sample of proteins (which was unknown before as a repetitive region binding proteins) to interacts directly with the repeated sequence, it will substantially add of the study (e.g., by EMSA; estimated time: 1 months). If the authors will decide to check the also the function of one of at least one such a newly detected proteins (e.g., by KD), I estimate the will take 3-6 months.

As highlighted previously the proposed EMSA experiment may well be uninformative for protein complex components identified in our study or for isolated proteins that directly bind DNA in the context of a complex and chromatin. RNAi knockdown data and cell location data (as well as developmental expression and orthology data) is already available through tritrypDB.org and trtyptag.org

Are the data and the methods presented in such a way that they can be reproduced? Yes

Are the experiments adequately replicated, and statistical analysis adequate?

The authors did not mention replicates. There is no statistical analysis mentioned.

The figure legends indicate that all volcano plots of TALE affinity selections were derived from three biological replicates. Cutoffs used for significance: P < 0.05 (Student's t-test).

For ChiP-seq two biological replicates were analysed for each cell line expressing the specific YFP tagged protein of interest (TALE or KKT2). This is now stated in the relevant figure legends – apologies for this oversight. The resulting data are available for scrutiny at GEO: GSE295698.

Minor comments:

Specific experimental issues that are easily addressable.

The following suggestions can be incorporated:

(1) Page 18, in the material method section author mentioned four drugs: Blasticidine, Phleomycin and G418, and hygromycin. It is recommended to mention the purpose of using these selective drugs for the parasite. If clonal selection has been done, then it should also be mentioned.

We erroneously added information on several drugs used for selection in our labaoratory. In fact all TALE-YFP construct carry the Bleomycin resistance genes which we select for using Phleomycin. Also, clones were derived by limiting dilution immediately after transfection. We have amended the text accordingly:

Page 17/18:

“Cell cultures were maintained below 3 x 106 cells/ml. Pleomycin 2.5 µg/ml was used to select transformants containing the TALE construct BleoR gene.”

“Electroporated bloodstream cells were added to 30 ml HMI-9 medium and two 10-fold serial dilutions were performed in order to isolate clonal Pleomycin resistant populations from the transfection. 1 ml of transfected cells were plated per well on 24-well plates (1 plate per serial dilution) and incubated at 37°C and 5% CO2 for a minimum of 6 h before adding 1 ml media containing 2X concentration Pleomycin (5 µg/ml) per well.”

(2) In the method section the authors mentioned that there is only one site for binding of NonR-TALE in the parasite genome. But in Fig. 1C, the authors showed zero binding site. So, there is one binding site for NonR-TALE-YFP in the genome or zero?

We thank the reviewer for pointing out this discrepancy. We have checked the latest Tb427v12 genome assembly for predicted NonR-TALE binding sites and there are no exact matches. We have corrected the text accordingly.

Page 7:

“A control NonR-TALE protein was also designed which was predicted to have no target sequence in the T. brucei genome.”

Page 17:

“A control NonR-TALE predicted to have no recognised target in the T. brucei geneome was designed as follows: BLAST searches were used to identify exact matches in the TREU927 reference genome. Candidate sequences with one or more match were discarded.”

(3) The authors used two different anti-GFP antibodies, one from Roche and the other from Thermo Fisher. Why were two different antibodies used for the same protein?

We have found that only some anti-GFP antibodies are effective for affinity selection of associated proteins, whereas others are better suited for immunolocalisation. The respective suppliers’ antibodies were optimised for each application.

(4) Page 6: in the introduction, the authors give the number of total VSG genes as 2,634. Is it known how many of them are pseudogenes?

This value corresponds to the number reported by Consentino et al. 2021 (PMID: 34541528) for subtelomeric VSGs, which is similar to the value reported by Muller et al 2018 (PMID: 30333624) (2486), both in the same strain of trypanosomes as used by us. Based on the earlier analysis by Cross et al (PMID: 24992042), 80% of the identified VSGs in their study (2584) are pseudogenes. This approximates to the estimation by Consentino of 346/2634 (13%) being fully functional VSG genes at subtelomeres, or 17% when considering VSGs at all genomic locations (433/2872).

(5) I found several typos throughout the manuscript.

Thank you for raising this, we have read through the manuscipt several times and hopefully corrected all outstanding typos.

(6) Fig. 1C: Table: below TOTAL 2nd line: the number should be 1838 (rather than 1828)

Corrected- thank you.

- Are prior studies referenced appropriately? Yes

- Are the text and figures clear and accurate? Yes

- Do you have suggestions that would help the authors improve the presentation of their data and conclusions? Suggested above

Reviewer #1 (Significance):

Describe the nature and significance of the advance (e.g., conceptual, technical, clinical) for the field:

This study represents a significant conceptual and technical advancement by employing a synthetic TALE DNA-binding protein tagged with YFP to selectively identify proteins associated with five distinct repetitive regions of T. brucei chromatin. To the best of my knowledge, it is the first report to utilize TALE-YFP for affinity-based isolation of protein complexes bound to repetitive genomic sequences in T. brucei. This approach enhances our understanding of chromatin organization in these regions and provides a foundation for investigating the functional roles of associated proteins in parasite biology. Importantly, any essential or unique interacting partners identified could serve as potential targets for therapeutic intervention.

- Place the work in the context of the existing literature (provide references, where appropriate). I agree with the information that has already described in the submitted manuscript, regarding its potential addition of the data resulted and the technology established to the study of VSGs expression, kinetochore mechanism and telomere biology.

- State what audience might be interested in and influenced by the reported findings. These findings will be of particular interest to researchers studying the molecular biology of kinetoplastid parasites and other unicellular organisms, as well as scientists investigating chromatin structure and the functional roles of repetitive genomic elements in higher eukaryotes.

- (1) Define your field of expertise with a few keywords to help the authors contextualize your point of view. Protein-DNA interactions/ chromatin/ DNA replication/ Trypanosomes

- (2) Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. None

Reviewer #2 (Evidence, reproducibility and clarity):

Summary

Carloni et al. comprehensively analyze which proteins bind repetitive genomic elements in Trypanosoma brucei. For this, they perform mass spectrometry on custom-designed, tagged programmable DNA-binding proteins. After extensively verifying their programmable DNA-binding proteins (using bioinformatic analysis to infer target sites, microscopy to measure localization, ChIP-seq to identify binding sites), they present, among others, two major findings: 1) 14 of the 25 known T. brucei kinetochore proteins are enriched at 177bp repeats. As T. brucei's 177bp repeatcontaining intermediate-sized and mini-chromosomes lack centromere repeats but are stable over mitosis, Carloni et al. use their data to hypothesize that a 'rudimentary' kinetochore assembles at the 177bp repeats of these chromosomes to segregate them. 2) 70bp repeats are enriched with the Replication Protein A complex, which, notably, is required for homologous recombination. Homologous recombination is the pathway used for recombination-based antigenic variation of the 70bp-repeat-adjacent variant surface glycoproteins.

Major Comments

None. The experiments are well-controlled, claims well-supported, and methods clearly described. Conclusions are convincing.

Thank you for these positive comments.

Minor Comments

(1) Fig. 2 - I couldn't find an uncropped version showing multiple cells. If it exists, it should be linked in the legend or main text; Otherwise, this should be added to the supplement.

The images presented represent reproducible analyses, and independently verified by two of the authors. Although wider field of view images do not provide the resolution to be informative on cell location, as requested we have provided uncropped images in new Fig. S4 for all the cell lines shown in Figure 2A.

In addition, we have included as supplementary images (Fig. S3B) additional images of TelRTALE-YFP, 177R-TALE-YFP and ingiR-TALE YFP localisation to provide additional support their observed locations presented in Figure 1. The set of cells and images presented in Figure 2A and in Fig S3B were prepared and obtained by a different authors, independently and reproducibly validating the location of the tagged protein.

(2) I think Suppl. Fig. 1 is very valuable, as it is a quantification and summary of the ChIP-seq data. I think the authors could consider making this a panel of a main figure. For the main figure, I think the plot could be trimmed down to only show the background and the relevant repeat for each TALE protein, leaving out the non-target repeats. (This relates to minor comment 6.) Also, I believe, it was not explained how background enrichment was calculated.

We are grateful for the reviewer’s positive view of original Fig. S1 and appreciate the suggestion. We have now moved these analysis to part B of main Figure 2 in the revised manuscript – now Figure 2B. We have also provided additional details in the Methods section on the approaches used to assess background enrichment.

Page 19:

“Background enrichment calculation

The genome was divided into 50 bp sliding windows, and each window was annotated based on overlapping genomic features, including CIR147, 177 bp repeats, 70 bp repeats, and telomeric (TTAGGG)n repeats. Windows that did not overlap with any of these annotated repeat elements were defined as "background" regions and used to establish the baseline ChIP-seq signal. Enrichment for each window was calculated using bamCompare, as log₂(IP/Input). To adjust for background signal amongst all samples, enrichment values for each sample were further normalized against the corresponding No-YFP ChIP-seq dataset.”

Note: While revising the manuscript we also noticed that the script had a nomalization error. We have therefore included a corrected version of these analyses as Figure 2B (old Fig. S1)

(3) Generally, I would plot enrichment on a log2 axis. This concerns several figures with ChIP-seq data.

Our ChIP-seq enrichment is calculated by bamCompare. The resulting enrichment values are indeed log2 (IP/Input). We have made this clear in the updated figures/legends.

(4) Fig. 4C - The violin plots are very hard to interpret, as the plots are very narrow compared to the line thickness, making it hard to judge the actual volume. For example, in Centromere 5, YFP-KKT2 is less enriched than 147R-TALE over most of the centromere with some peaks of much higher enrichment (as visible in panel B), however, in panel C, it is very hard to see this same information. I'm sure there is some way to present this better, either using a different type of plot or by improving the spacing of the existing plot.

We thank the reviewer for this suggestion; we have elected to provide a Split-Violin plot instead. This improves the presentation of the data for each centromere. The original violin plot in Figure 4C has been replaced with this Split-Violin plot (still Figure 4C).

(5) Fig. 6 - The panels are missing an x-axis label (although it is obvious from the plot what is displayed).

Maybe the "WT NO-YFP vs" part that is repeated in all the plot titles could be removed from the title and only be part of the x-axis label?

In fact, to save space the X axis was labelled inside each volcano plot but we neglected to indicate that values are a log2 scale indicating enrichment. This has been rectified – see Figure 6, and Fig. S7, S8 and S9.

(6) Fig. 7 - I would like to have a quantification for the examples shown here. In fact, such a quantification already exists in Suppl. Figure 1. I think the relevant plots of that quantification (YFPKKT2 over 177bp-repeats and centromere-repeats) with some control could be included in Fig. 7 as panel C. This opportunity could be used to show enrichment separated out for intermediate-sized, mini-, and megabase-chromosomes. (relates to minor comment 2 & 8)

The CIR147 sequence is found exclusively on megabase-sized chromosomes, while the 177 bp repeats are located on intermediate- and mini-sized chromosomes. Due to limitations in the current genome assembly, it is not possible to reliably classify all chromosomes into intermediate- or mini- sized categories based on their length. Therefore, original Supplementary Fig. S1 presented the YFP-KKT2 enrichment over CIR147 and 177 bp repeats as a representative comparison between megabase chromosomes and the remaining chromosomes (corrected version now presented as main Figure 2B). Additionally, to allow direct comparison of YFP-KKT2 enrichment on CIR147 and 177 bp repeats we have included a new plot in Figure 7C which shows the relative enrichment of YFP-KKT2 on these two repeat types.

We have added the following text , page 12:

“Taking into account the relative to the number of CIR147 and 177 bp repeats in the current T.brucei genome (Cosentino et al., 2021; Rabuffo et al., 2024), comparative analyses demonstrated that YFP-KKT2 is enriched on both CIR147 and 177 bp repeats (Figure 7C).”

(7) Suppl. Fig. 8 A - I believe there is a mistake here: KKT5 occurs twice in the plot, the one in the overlap region should be KKT1-4 instead, correct?

Thanks for spotting this. It has been corrected

(8) The way that the authors mapped ChIP-seq data is potentially problematic when analyzing the same repeat type in different regions of the genome. The authors assigned reads that had multiple equally good mapping positions to one of these mapping positions, randomly.

This is perfectly fine when analysing repeats by their type, independent of their position on the genome, which is what the authors did for the main conclusions of the work.

However, several figures show the same type of repeat at different positions in the genome. Here, the authors risk that enrichment in one region of the genome 'spills' over to all other regions with the same sequence. Particularly, where they show YFP-KKT2 enrichment over intermediate- and mini-chromosomes (Fig. 7) due to the spillover, one cannot be sure to have found KKT2 in both regions.

Instead, the authors could analyze only uniquely mapping reads / read-pairs where at least one mate is uniquely mapping. I realize that with this strict filtering, data will be much more sparse. Hence, I would suggest keeping the original plots and adding one more quantification where the enrichment over the whole region (e.g., all 177bp repeats on intermediate-/mini-chromosomes) is plotted using the unique reads (this could even be supplementary). This also applies to Fig. 4 B & C.

We thank the reviewer for their thoughtful comments. Repetitive sequences are indeed challenging to analyze accurately, particularly in the context of short read ChIP-seq data. In our study, we aimed to address YFP-KKT2 enrichment not only over CIR147 repeats but also on 177 bp repeats, using both ChIP-seq and proteomics using synthetic TALE proteins targeted to the different repeat types. We appreciate the referees suggestion to consider uniquely mapped reads, however, in the updated genome assembly, the 177 bp repeats are frequently immediately followed by long stretches of 70 bp repeats which can span several kilobases. The size and repetitive nature of these regions exceeds the resolution limits of ChIP-seq. It is therefore difficult to precisely quantify enrichment across all chromosomes.

Additionally, the repeat sequences are highly similar, and relying solely on uniquely mapped reads would result in the exclusion of most reads originating from these regions, significantly underestimating the relative signals. To address this, we used Bowtie2 with settings that allow multi-mapping, assigning reads randomly among equivalent mapping positions, but ensuring each read is counted only once. This approach is designed to evenly distribute signal across all repetitive regions and preserve a meaningful average.

Single molecule methods such as DiMeLo (Altemose et al. 2022; PMID: 35396487) will need to be developed for T. brucei to allow more accurate and chromosome specific mapping of kinetochore or telomere protein occupancy at repeat-unique sequence boundaries on individual chromosomes.

Reviewer #2 (Significance):

This work is of high significance for chromosome/centromere biology, parasitology, and the study of antigenic variation. For chromosome/centromere biology, the conceptual advancement of different types of kinetochores for different chromosomes is a novelty, as far as I know. It would certainly be interesting to apply this study as a technical blueprint for other organisms with minichromosomes or chromosomes without known centromeric repeats. I can imagine a broad range of labs studying other organisms with comparable chromosomes to take note of and build on this study. For parasitology and the study of antigenic variation, it is crucial to know how intermediate- and mini-chromosomes are stable through cell division, as these chromosomes harbor a large portion of the antigenic repertoire. Moreover, this study also found a novel link between the homologous repair pathway and variant surface glycoproteins, via the 70bp repeats. How and at which stages during the process, 70bp repeats are involved in antigenic variation is an unresolved, and very actively studied, question in the field. Of course, apart from the basic biological research audience, insights into antigenic variation always have the potential for clinical implications, as T. brucei causes sleeping sickness in humans and nagana in cattle. Due to antigenic variation, T. brucei infections can be chronic.

Thank you for supporting the novelty and broad interest of our manuscript

My field of expertise / Point of view:

I'm a computer scientist by training and am now a postdoctoral bioinformatician in a molecular parasitology laboratory. The laboratory is working on antigenic variation in T. brucei. The focus of my work is on analyzing sequencing data (such as ChIP-seq data) and algorithmically improving bioinformatic tools.

eLife Assessment

This important study examines the role of map3k1, a MAP3K family member that has both kinase and ubiquitin ligase domains, in the differentiation of progenitors in the flatworm Planaria. The convincing analyses demonstrate that map3k1 acts within progenitors to restrict their premature differentiation and to prevent formation of teratomas. This work would be of interest to researchers in the fields of regeneration, developmental biology, and aging.

Reviewer #1 (Public review):

Summary:

The authors assess the role of map3k1 in adult Planaria through whole body RNAi for various periods of time. The authors' prior work has shown that neoblasts (stem cells that can regenerate the entire body) for various tissues are intermingled in the body. Neoblasts divide to produce progenitors that migrate within a "target zone" to the "differentiated target tissues" where they differentiate into a specific cell type. Here the authors show that map3k1-i animals have ectopic eyes that form along the "normal" migration path of eye progenitors, ectopic neurons and glands along the AP axis and pharynx in ectopic anterior positions. The rest of the study shows that positional information is largely unaffected by loss of map3k1. However, loss of map3k1 leads to premature differentiated of progenitors along their normal migratory route. They also show that "long-term" whole body depletion of map3k1 results in mis-specified organs and teratomas. In short, this study convincingly demonstrates that in planaria, map3k1 maintains progenitor cells in an undifferentiated state, preventing premature fate commitment until they encounter the appropriate signals, either positional cues within a designated region or contact-dependent inputs from surrounding tissues.

Strengths:

(1) The study has appropriate controls, sample sizes and statistics.

(2) The work is high-quality.

(3) The conclusions are supported by the data.

(4) Planaria is a good system to analyze the function of map3k1, which exists in mammals but not other invertebrates.

Weaknesses:

None noted.

Reviewer #2 (Public review):

Summary:

The flatworm planarian Schmidtea mediterranea is an excellent model for understanding cell fate specification during tissue regeneration and adult tissue maintenance. Planarian stem cells, known as neoblasts, are continuously deployed to support cellular turnover and repair tissues damaged or lost due to injury. This reparative process requires great precision to recognize the location, timing, and cellular fate of a defined number of neoblast progeny. Understanding the molecular mechanisms driving this process could have important implications for regenerative medicine and enhance our understanding of how form and function are maintained in long-lived organisms such as humans. Unfortunately, the molecular basis guiding cell fate and differentiation remains poorly understood.

In this manuscript, Canales et al. identified the role of the map3k1 gene in mediating the differentiation of progenitor cells at the proper target tissue. The map3k1 function in planarians appears evolutionarily conserved as it has been implicated in regulating cell proliferation, differentiation, and cell death in mammals. The results show that the downregulation of map3k1 with RNAi leads to spatial patterning defects in different tissue types, including the eye, pharynx, and the nervous system. Intriguingly, long-term map3k1-RNAi resulted in ectopic outgrowths consistent with teratomas in planarians. The findings suggest that map3k1 mediates signaling, regulating the timing and location of cellular progenitors to maintain correct patterning during adult tissue maintenance.

Strengths:

The authors provide an entry point to understanding molecular mechanisms regulating progenitor cell differentiation and patterning during adult tissue maintenance.

The diverse set of approaches and methods applied to characterize map3k1 function strengthens the case for conserved evolutionary mechanisms in a selected number of tissue types. The creativity using transplantation experiments is commendable, and the findings with the teratoma phenotype are intriguing and worth characterizing.

Weaknesses:

The authors have satisfactorily addressed our previous concerns.

Author response:

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

Public Reviews:

Reviewer #1 (Public review):

Summary:

The authors assess the role of map3k1 in adult Planaria through whole body RNAi for various periods of time. The authors' prior work has shown that neoblasts (stem cells that can regenerate the entire body) for various tissues are intermingled in the body. Neoblasts divide to produce progenitors that migrate within a "target zone" to the "differentiated target tissues" where they differentiate into a specific cell type. Here the authors show that map3k1-i animals have ectopic eyes that form along the "normal" migration path of eye progenitors (Fig. 1), ectopic neurons and glands along the AP axis (Fig. 2) and pharynx in ectopic anterior positions (Fig. 3). The rest of the study show that positional information is largely unaffected by loss of map3k1 (Fig. 4,5). However, loss of map3k1 leads to premature differentiated of progenitors along their normal migratory route (Fig. 6). They also show that an ill-defined "long-term" whole body depletion of map3k1 results in mis-specified organs and teratomas.

Strengths:

(1) The study has appropriate controls, sample sizes and statistics.

(2) The work appears to be high-quality.

(3) The conclusions are supported by the data.

(4) Planaria is a good system to analyze the function of map3k1, which exists in mammals but not in other invertebrates.

Weaknesses:

(1) The paper is largely descriptive with no mechanistic insights. 

The mechanistic insights we aim to address are primarily at the cellular systems level – how adult progenitor cells produce pattern. Specifically, we uncovered strong evidence that regulation of differentiation is an active process occurring in migratory progenitors and that this regulation is a major component of pattern formation during the adult processes of tissue turnover and regeneration. The map3k1 phenotype provided a tool used to reveal the existence of this regulation, and to understand the patterning abnormalities prevented by this regulatory mechanism. We updated the text in several places to make clearer some of this emphasis. For example, in the Discussion: "We suggest that differentiation is restricted during migratory targeting as an essential component of pattern formation, with the map3k1 RNAi phenotype indicating the existence and purpose of this element of patterning." 

Naturally, identifying a particular molecule involved in this process is of interest for understanding molecular mechanism; this would allow for comparison to other cellular systems in other organisms and would focus future molecular inquiry. Future molecular studies into the mechanism of Map3k1 regulation and its downstream signaling will be fascinating as next steps towards understanding the process at the molecular level more deeply. We also added some discussion considering the types of upstream activation cues that could potentially be associated with Map3k1 regulation to suppress differentiation. 

(2) Given the severe phenotypes of long-term depletion of map3k1, it is important that this exact timepoint is provided in the methods, figures, figure legends and results. 

We removed the use of the term “long-term” and instead added timepoints used to all figure legends. We also added a summary of timepoints used in the methods section and included RNAi timepoint labels in figures where a phenotype progression over time is relevant to interpretation. For timecourses, we also added suitable time information to text in the results. 

(3) Figure 1C, the ectopic eyes are difficult to see, please add arrows. 

To improve visualization, we replaced the example animal in the original Figure 1C with one that has a stronger phenotype, including arrows pointing to every ectopic event. Additionally, we included magnified images of optic cup cells and photoreceptor neurons in the trunk and tail region. This is now Figure 1B.

(4) line 217 - why does the n=2/12 animals not match the values in Figure 3B, which is 11/12 and 12/12. The numbers don't add up. Please correct/explain. 

In Figure 3B in the submitted version (3/18 had cells in the tail) had more animals scored (6 animals from a replicate experiment where 1/6 showed the cells in the tail) than the total scored (2/12 had cells in the tail) in the text, which did not have the animals from the replicate added during writing. The results are the same, just different sample sizes were noted in those locations and we fixed this issue. In the updated Figure 3, the order of presentation has shifted (e.g., prior 3B is now in 3C and Figure 3_figure supplement 1). We made sure to include numbers to all figure panels. 

(5) Figure panels do not match what is written in the results section. There is no Figure 6E. Please correct.

Thank you for catching this. We have gone through figures and text after editing to make sure that text callouts are appropriately matched to the figures. 

Reviewer #2 (Public review):

Summary:

The flatworm planarian Schmidtea mediterranea is an excellent model for understanding cell fate specification during tissue regeneration and adult tissue maintenance. Planarian stem cells, known as neoblasts, are continuously deployed to support cellular turnover and repair tissues damaged or lost due to injury. This reparative process requires great precision to recognize the location, timing, and cellular fate of a defined number of neoblast progeny. Understanding the molecular mechanisms driving this process could have important implications for regenerative medicine and enhance our understanding of how form and function are maintained in long-lived organisms such as humans. Unfortunately, the molecular basis guiding cell fate and differentiation remains poorly understood.

In this manuscript, Canales et al. identified the role of the map3k1 gene in mediating the differentiation of progenitor cells at the proper target tissue. The map3k1 function in planarians appears evolutionarily conserved as it has been implicated in regulating cell proliferation, differentiation, and cell death in mammals. The results show that the downregulation of map3k1 with RNAi leads to spatial patterning defects in different tissue types, including the eye, pharynx, and the nervous system. Intriguingly, long-term map3k1-RNAi resulted in ectopic outgrowths consistent with teratomas in planarians. The findings suggest that map3k1 mediates signaling, regulating the timing and location of cellular progenitors to maintain correct patterning during adult tissue maintenance.

Strengths:

The authors provide an entry point to understanding molecular mechanisms regulating progenitor cell differentiation and patterning during adult tissue maintenance.

The diverse set of approaches and methods applied to characterize map3k1 function strengthens the case for conserved evolutionary mechanisms in a selected number of tissue types. The creativity using transplantation experiments is commendable, and the findings with the teratoma phenotype are intriguing and worth characterizing.

Thank you to the reviewer for the positive feedback

Weaknesses:

The article presents a provocative idea related to the importance of positional control for organs and cells, which is at least in part regulated by map3k1. Nonetheless, the role of map3k1 or its potential interaction with regulators of the anterior-posterior, mediolateral axes, and PCGs is somewhat superficial. The authors could elaborate or even speculate more in the discussion section and the different scenarios incorporating these axial modulators into the map3k1 model presented in Figure 8 

First, to strengthen the support for our finding that positional information is largely unaffected in map3k1 RNAi animals, we added data regarding the expression of additional relevant position control genes (PCGs) –ndl-4, ptk7, sp5, and wnt11-1 – to the PCG panel in Figure 5. The expression domain of ndl-4, an FGF receptor-like protein family member that contributes to head patterning and anterior pole maintenance, was normal in map3k1 RNAi. wnt11-1, a PCG with expression concentrated in the posterior end of the animal and with expression dependent on general Wnt activity, was also normal in map3k1 RNAi animals. ptk7, RNAi of which can result in supernumerary pharynges, also showed normal expression in map3k1 RNAi animals. Finally, sp5, a Wnt-activated gene with expression in the tail, also showed normal expression in map3k1 RNAi animals. 

Second, to further support the conclusion that cells are not suitably responding to positional information after map3k1 RNAi, which we argue normally dictates where differentiation should occur, we added examples of differentiated cell types that are ectopically positioned within an atypical PCG expression domain for that cell type (Figure 5C). This underscores that following map3k1 RNAi the PCG expression domains do not change, but the pattern of differentiated cell types relative to these domains does shift. We also added data showing that regenerating tails had a proper wntP-2 gradient, but an anterior regenerating pharynx appeared outside of this wntP-2⁺ zone and inside of an ndl-5⁺ zone (Figure 5- figure supplement 1E). We added some discussion of these new data in the Figure 5 results section. We also noted, regarding independent recent map3k1 work (Lo, 2025), some evidence exists that a minor posterior shift in ndl-5 expression can occur after map3k1 RNAi.

Next, we added a new element to the model figure (Figure 8B) depicting that PCG expression domains remain normal after map3k1 RNAi, with ectopic differentiation occurring in an incorrect positional information environment. We refer to this new panel in the discussion: "We suggest that map3k1 is not required for the spatial distribution of progenitor-extrinsic differentiation-promoting cues themselves, but for progenitors to be restricted from differentiating until these cues are received (Figure 8B)."; we then follow this statement with a summary in the Discussion of six pieces of evidence that support this model.

Finally, we added some additional text to the discussion section about candidate mechanisms by which extrinsic cues could potentially regulate Map3k1, pointing to potential future inquiry directions. We suggest that map3k1 is not involved in regulating PCG activity domains themselves, but instead acts as a brake on differentiation within migratory progenitors through active signaling. This brake is then lifted when the progenitors hit their correct PCG-based migratory target, or when they hit their target tissue. How that occurs mechanistically is unknown. One scenario is that each progenitor is tuned to respond to a particular PCG-regulated environment (such as a particular ECM or signaling environment) to generate a molecular change that inactivates Map3K1 signaling, such as by inactivating or disengaging an RTK signal. Alternatively, the migratory process in progenitors could engage the Map3K1 signal, enabling signal cessation with arrival at a target location. When Map3K1 is active it could result in a transcriptional state that prevents full expression of differentiated factors required for maturation, tissue incorporation, and cessation of migration. These considerations are now added to the discussion.

The article can be improved by addressing inconsistencies and adding details to the results, including the main figures and supplements. This represents one of the most significant weaknesses of this otherwise intriguing manuscript. Below are some examples of a few figures, but the authors are expected to pay close attention to the remaining figures in the paper.

Details associated with the number of animals per experiment, statistical methods used, and detailed descriptions of figures appear inconsistent or lacking in almost all figures. In some instances, the percentage of animals affected by the phenotype is shown without detailing the number of animals in the experiment or the number of repeats. Figures and their legends throughout the paper lack details on what is represented and sometimes are mislabeled or unrelated. 

We endeavored to ensure that these noted details are present throughout the legends and figures for all figure panels.

Specifically, the arrows in Figure 1A are different colors. Still, no reasoning is given for this, and in the exact figure, the top side (1A) shows the percentages and the number of animals below. 

The only reason for the different colored arrows was for visibility purposes. To avoid confusion, we now use white arrows for all FISH images in figure 1, and where ever else possible. We also replaced the percentages with n numbers in the bottom left corner of the live images in Figure 1A. 

Conversely, in Figures 1B, C, and D, no details on the number of animals or percentages are shown, nor an explanation of why opsin was used in Figure 1A but not 1B. 

The original Figure 1B represented a few different examples of ectopic eye/eye cell patterns in the map3k1 RNAi animals to demonstrate the variable and disorganized nature of the phenotype. To address this, we added further explanation in the legend. We also merged 1A and 1B for simplicity of interpretation. opsin was used in Figure 1A to label cell bodies of photoreceptors. anti-Arrestin was used in the example FISH images to see if these cells were interconnected via projections, which we now clarify in the legend and in the text. 

Is Figure 1B missing an image for the respective control? Figure 1C needs details regarding what the two smaller boxes underneath are. 

The control for Figure 1B was in Figure 1A; the merger of Figures 1A/B should address this. Boxes in Figure 1C were labelled with numbers corresponding to the image above them.

Figure 1C could use an AP labeling map in 10 days (e.g., AP6 has one optic cup present). Figure 1C and F counts do not match. 

We added a cartoon to 1C to show the region imaged. Note that the 36d trunk image (now Fig. 1B) has now been replaced with a full animal image and magnified boxes that show locations of example ectopic cells. That cell in 1C was categorized as in AP5. Note that additional animals were analyzed and data added to the distribution (now Fig. 1D). 

In Figure 1C, we do not know the number of animals tested, controls used, the scale bar sizes in the first two images, nor the degree of magnification used despite the pharynx region appearing magnified in the second image.  Figure 1C is also shown out of chronological order; 36 days post RNAi is shown before 10 days post RNAi. Moreover, the legends for Figures 1C and 1D are swapped.

We have endeavored to ensure sample numbers, control images, and appropriate scale bar notation in legends are present for all images. Figure 1C has now been split into two panels: Figure 1B and Figure 1C. It does not follow a chronological order in presentation for the following logic flow: we uncover and describe the phenotype; then, with knowledge of the defect, we walk back to see how early the phenotype starts after RNAi and what the pattern of ectopic cell distribution is when the phenotype starts to emerge (using the knowledge of which cells are affected from the overt phenotype described in 1A/B). 

Additionally, Figure 1F and many other figures throughout the paper lack overall statistical considerations. Furthermore, Figure 1F has three components, but only one is labeled. Labeling each of them individually and describing them in the corresponding figure legend may be more appropriate.

The main point of the graphs in 1F (now 1D) was the overt overall pattern difference with the wild-type, which never has ectopic eye cells in the midbody or tail, and that the ectopic eye cells progress throughout the entire AP axis. However, we concur that a statistical test is a reasonable thing to show here and that is now included in the legend. The 3 components (in Figure 1F, now Figure 1D) where kept together with one figure label (D) for simplicity, but were rearranged (top and bottom) with a cartoon to the side and with modified labeling for extra clarity. 

Figure 2C shows images of gene expression for two genes, but the counts are shown for only one in Figure 2D. It is challenging to follow the author's conclusions without apparent reasoning and by only displaying quantitative considerations for one case but not the other. These inconsistencies are also observed in different figures. 

In Figure 2C, FISH images of cintillo+ and dd_17258+ neurons are shown to display the specificity of this effect to some neurons and not others. Because cintillo+ cells did not expand at all (n=24/24 animals), the counts for them would all be zero values. We only counted data for dd_17258 cells because it was the neuron that expanded compared to the control animals. We have now added a note in the legend explaining this.

In Figure 2D, 24/24 animals were reported to show the phenotype, but only eight were counted (is there a reason for this?).

8 animals were used to quantitatively characterize the spread of cells along the AP axis, as it was deemed an adequate sample size to capture the change in distribution of 17258+ cells from being head restricted to being present throughout the body. Through multiple cohorts of animals in replicates, a total of 24/24 examined animals showed this expansion phenotype. Double FISH experiments were additionally carried out using dd_17258 and various PCGs; these data are now included in Figure 5C, and these animals were added to the total counts regarding quantitative analysis of the phenotype in Figure 2D. 

In Figure 2E, the expression for three genes is shown, with some displaying anterior and posterior regions while others only show the anterior picture. Is there a particular reason for this? 

The original first panel in Figure 2E showed an example of a non-expanding gland cell type, dd_9223, which is very restricted to the head in both control and map3k1 RNAi animals. Because we did not observe a phenotype for this cell type (no cells in all control and map3k1 RNAi animal tails), we only included tail images of cell types that showed an abnormal phenotype with clear expanded to the posterior (dd_8476 and dd_7131). However, we have now included tail images of dd_9223 cells and added data for dd_9223 to the graph in Figure 2E. 

Also, in Figure 2F, the counts are shown for only the posterior region of two genes out of the three displayed in Figure 2E. It is unclear why the authors do not show counts for the anterior areas considered in Figure 2E. Furthermore, the legend for Figure 2D is missing, and the legend for 2F is mislabeled as a description for Figure 2D.

We now include tail images for dd_9223 in Figure 2E to show that there are no ectopic cells in tails. We did not originally include counts of dd_9223 because there was no phenotype observed. dd_7131 and dd_8476 cell types appeared in the posterior of even control animals at a low frequency, unlike dd_9223 cells. However, we did now add counts for dd_9223 tail regions in the graph. We did not count the anterior regions of the animal because our goal was to show data for the visible phenotype (ectopic cells in the tail) not only with an example image, but also by showing the number of cells in the tail with a graph and statistical test. Legends have been updated with correct details.

Supplement Figure 1 B reports data up to 6 weeks, but no text in the manuscript or supplement mentions any experiment going up to 6 weeks. There are no statistics for data in Supplement Figure 1E. Any significance between groups is unclear.

More details about the RNAi feeding schedules have been added in the methods section. All RNAi timepoints are now specified specifically in the legends. The Figure 1F and Figure 1- figure supplement 1E (additional data: ovo⁺; smedwi-1^- cell counts) and legends now mention the statistical tests performed and annotations (not significant *ns) or p values have been added to the graphs. For simplicity, we decided to include all smedwi-1+ counts together rather than splitting them into low and high smedwi-1+ cells, because we weren't really making any claims about low and high cells. 

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

It would be good to acknowledge in the discussion the recent paper from the Petersen lab on map3k1, published in PLoS Genet 2025, especially if the results differ between the two labs.

We added reference/discussion regarding the recent PLoS Genetics Lo, 2025 map3k1 paper at several suitable points in the manuscript.

Reviewer #2 (Recommendations for the authors):

Please pay close attention to the description of experimental details and the consistency throughout the paper. It seems like the reader has to assume or come across information that is not readily available from the text or the legends in the paper. This is an interesting paper with intriguing findings. However, the version presented here appears rushed or put together on the flight.

Thank you for your thorough feedback. We have endeavored to ensure all appropriate details are present in figures and/or figure legends.

Simplifying data may frequently be convenient when creating a widely-applicable program, but it involves leaving at least one group or perspective out. Because of this, simplification of data often contains inherent bias and developers should be aware of this.

In the modern age, it is important to understand what truly counts as a “bot” considering the intricacies of automation and the philosophical question of autonomous AI. Can we consider bots as a valid representation of general public consensus as they become more prevalent?

It is helpful to connect a numerical value to a ballpark amount. This is especially practical when figuring out the amount of spam bots out on Twitter.

i find it very interesting how Twitter counts its bots to make the 5% claim. I also find it interesting how the small difference (and in wording allows them to get away with the claim

Its always important to remember, when looking at data, it isn't always objective. Data is made up of what the creator choose to include. Data can be missing important distinctions (like small or big apples), information (an apple is just outside the picture frame, or can be intentionally omitted. It is always useful to look at the parameters of a study

This definitely opened my perspective on data constraints. In the reflection before, I figured that the best way to store information for social media would be through pre-set categories (for things like relationship status, address, etc), but there are definitely important details that can be hard to simplify and cut out (though, I'm sure no one needs additional details on someone's relationship status). I guess that's why there are some instances where you're able to put down a permanent address and a temporary address for those who are only residing somewhere for a short-term opportunity.

People typically don’t expect to glean much useful information from bots. In my case, at least, I would typically block or ignore them. Additionally, it’s often easy to identify a bit, but in the age of AI these lines are becoming more blurred.

eLife Assessment

This important study employs a closed-loop, theta-phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats and reports that disrupting theta-timescale coordination impairs performance of challenging aspects of spatial behaviors, while sparing hippocampal replay and spatial coding in hippocampal place cells. The findings are expected to advance theoretical understanding of learning and memory operations and to provide practical implications for the application of similar optogenetic approaches. The experiments were viewed as technically rigorous, but the strength of evidence provided in the current version of the manuscript was viewed as incomplete, mostly due to limited analyses and the descriptions of some of the experimental protocols.

Reviewer #1 (Public review):

Summary:

This manuscript by Joshi and colleagues demonstrates that the precise theta-phase timing of spikes is causal for CA1 hippocampal theta sequences during locomotion on a linear track and is necessary for learning the cognitively demanding outbound component of a hippocampus-dependent alternation task (W-maze), independently of replay during immobility. To reach these conclusions, the authors developed a theta-phase-specific, closed-loop manipulation that used optogenetic activation of medial septal parvalbumin (PV) interneurons at the ascending phase of theta during locomotion. This protocol preserved immobility periods, allowing a clean and elegant dissociation from SWR-associated replay.

The manuscript is well written and was a pleasure to read. The work described is of high quality and introduces several notable advances to the field:

(a) It extends prior studies that manipulated theta oscillations by examining precise temporal structure (specifically theta sequences) rather than only LFP features.

(b) The closed-loop manipulation enabled dissociation between deficits in theta sequences during a behavioural task and SWR-associated replay activity.

(c) As controls, the authors included rats with suboptimal viral transduction or optic-fibre placement, and, within subjects, both stimulation-on (stim-on) and stimulation-off (stim-off) trials. Notably, sequence disruption persisted into stim-off periods within the same session.

Overall, this is a strong manuscript that will provide valuable insights to the field. I have only minor comments:

(1) As the authors note, it is striking that both behavioural performance and spike patterns are altered during stim-off trials. They propose that "disruption of theta sequences during the initial experience in an environment is sufficient to have lasting effects," implying that rapid, experience-dependent plasticity is driven by sequential firing. Does this imply that if rats were previously trained on the task, subsequent stim-on and stim-off trials would yield different outcomes, with stim-off trials showing improved performance and intact theta sequences? For example, if the sequence of one-third stim-on, one-third stim-off, one-third stim-on were inverted to off-on-off, would theta sequences be expected to emerge, disappear, and potentially re-emerge? While I am not asking for additional experiments, I think the discussion could be extended in this aspect.

Alternatively, could the number of stim-off trials (one third of the total) be insufficient to support learning/induce plasticity? In the controls, ~50-100 trials appear necessary to achieve high performance.

(2) In line with the point above, the authors characterise the behavioural changes induced by MS optogenetic stimulation specifically as a "learning deficit," as rats failed to improve across 300 trials in an initially novel environment (W-maze). While they present this as complementary to prior demonstrations of impaired performance on previously learned tasks (Zutshi et al., 2018; Quirk et al., 2021; Etter et al., 2023; Petersen et al., 2020), an alternative interpretation is a working-memory deficit. This would produce the same behavioural pattern, with reference memory (the less cognitively demanding trials) remaining intact despite stimulation and concomitant changes in theta sequences. This interpretation would also be consistent with work in certain disease models, where reduced synaptic plasticity and working-memory deficits co-occur with preserved place coding despite impaired theta sequences (e.g., Viana da Silva et al., 2024; Donahue et al., 2025).

(3) It was not immediately clear whether SWR-associated activity was derived from the interleaved ~15-min rest sessions in a rest box, or from periods of immobility or reward consumption in the maze (aSWR, as in Jadhav et al 2012). Regardless, it would be informative to compare aSWR events within the maze to rest-box SWRs that may occur during more prolonged slow-wave episodes (even if not full sleep). This contrasts with Liu et al. (2024), who analysed replay during ~1.5-h sleep sessions.

Reviewer #2 (Public review):

Summary:

The authors of this study developed a closed-loop optogenetic stimulation system with high temporal precision in rats to examine the effect of medial septum (MS) stimulation on the disruption of hippocampal activity at both behavioral and compressed time scales. They found that this manipulation preserved hippocampus single-cell-level spatial coding but affected theta sequences and performance during a spatial alternation task. The performance deficits were observed during the more cognitively demanding component of the task and even persisted after the stimulation was turned off. However, the effects of this disruption were confined to locomotor periods and did not impact waking rest replay, even during the early phase of stimulation-on. Their conclusion is consistent with previous findings from the Pastalkova lab, where MS disruption (using different methods) affected theta sequences and task performance but spared replay (Wang et al., 2015; Wang et al., 2016). However, it differs from a recent study in which optogenetic disruption of EC inputs during running affected both theta sequences and replay (Liu et al., 2023).

Strengths:

The experiments were well designed and controlled, and the results were generally well presented.

Weaknesses:

Major concerns are primarily technical but also conceptual. To further increase the impact of this study by contrasting findings from different disruptions, it is necessary to better align the analysis and detection methods.

Major concerns:

(1) To show that MS disruption does not affect spatial tuning, the authors computed the KL divergence of tuning curves between stimulation-on and stimulation-off conditions. I have two main questions about this analysis:

(1.1) The authors seem to impose stringent inclusion criteria requiring a large number of spikes and a strong concentration of tuning curves. These criteria may have selected strongly spatially tuned cells, which are typically more stable and potentially less vulnerable to perturbations. Based on the Figure 2 caption, it seems that fewer than 10% of cells were included in the KL divergence analysis, which is lower than the usual proportion of place cells reported in the literature. What is the rationale for using such strict inclusion criteria? What happens to the cells that are not as strongly tuned but are still identified as significant place cells?

(1.2) The KL divergence was computed between stimulation-on and stimulation-off conditions within the same animal group. However, the authors also showed that MS stimulation had lasting effects on theta sequences and performance even during stimulation-off periods. Would that lasting effect also influence spatial tuning? Based on these questions, the authors should perform additional analyses that directly measure spatial tuning quality and compare results across control and experimental groups - for example, spatial information of spikes (Skaggs et al., 1996), tuning stability, field length, and decoding error during running.

(2) The authors compared their results with those from Liu et al. (2023) and proposed that the different outcomes could be explained by different sites of disruption. However, the detection and quantification methods for theta sequences and replay differ substantially between the two studies, emphasizing different aspects of the phenomenon. I am not suggesting that either method is superior, but providing additional analyses using aligned detection methods would better support the authors' interpretations and benefit the field by enabling clearer comparisons across studies. In the current analysis, the power spectrum of the decoded ahead/behind distance only indicates that there is a rhythmic pattern, without specifying the decoding features at different theta phases. Moreover, the continuous non-local representations during ripples could include stationary representations of a location or zigzag representations that do not exhibit a linear sequential trace. Given that, the authors should show averaged decoding results corrected by the animal's actual position within theta cycles and compute a quadrant ratio. For replay analysis, they could use a linear fit (as in Liu et al., 2023) and report the proportion of significant replay events.

(3) The finding that theta sequences and performance were impaired even during stimulation-off periods is particularly interesting and warrants deeper exploration. In the Discussion, the authors claim that this may arise from "the rapid plasticity engaged during early learning." However, this explanation does not fully account for the observation. Previous studies have shown that theta sequences can develop very rapidly (Feng et al., Foster lab, 2015; Zhou et al., Dragoi lab, 2025). If the authors hypothesize that rapid plasticity during early stimulation-on disrupts the theta sequence, then the plasticity window must also be short and terminate during the subsequent stimulation-off period. Otherwise, why can't animals redevelop theta sequences during stimulation-off? The authors should conduct additional analyses during the stimulation-off periods of the W-maze task. For example:

(3.1) What is the spike-theta phase relationship? Do the phases return to normal or remain altered as during stimulation-on?

(3.2) Is there a significant place-field remapping from stimulation-on to stimulation-off? (Supplementary Figure 3F includes only a small subset of cells; what if population vector correlations are computed across all cells, or Bayesian decoding of stimulation-on spikes is performed using stimulation-off tuning curves?)

(3.3) The authors should also discuss why the stimulation-off epochs were not sufficient to support learning, and if the stimulation-off place cell sequences could have supported replay.

(4) Citations and/or discussion of key studies relevant to the current work are missing: Wang et al. in Pastalkova lab 2015-2016 studies for disruption of theta sequence (but not place cell sequence) disrupting learning but not replay, Drieu et al. in Zugaro lab 2018 study on disruption of theta sequence affecting sleep replay, Farooq and Dragoi 2019 for association between a lack of theta sequence and presence of waking rest replay during postnatal development, etc. The authors should discuss what the conceptually new findings in the current study are, given the findings of the previous literature above.

(5) The assessment of theta sequence is not state-of-the-art:

(5.1) Detecting the peak of cross-correlograms between neurons (CCG) relates to behavioral timescale CCG, not the theta sequence one; for the theta sequence, the closest to zero local peak should be used instead.

(5.2) How were other methods of detecting theta sequences performing on the stimulation-on/stimulation-off data: Bayesian decoding, firing sequences?

(5.3) How was phase precession during stimulation-on/stimulation-off?

(6) It would be important to calculate additional variables in the replay part of the study to compare the quality of replay across the 2 groups:

(6.1) Proportion of significant replay events out of the detected multiunit events.

(6.2) The average extent of trajectory depicted by the significant replay events in the targeted compared to the control, stimulation-on/stimulation-off.

Reviewer #3 (Public review):

Joshi et al. present an elegant and technically rigorous study examining how the temporal structure of hippocampal spiking during locomotion contributes to spatial learning. Using a closed-loop, theta phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats, the authors demonstrate that disrupting theta-timescale coordination impairs performance on the cognitively demanding component outbound trajectory of a spatial alternation task, while sparing hippocampal replay, place coding, and the simpler inbound learning. The work aims to dissociate the role of theta-associated temporal organization during navigation from sharp-wave ripple-associated replay during subsequent rest periods, providing a mechanistic link between theta sequences and learning. The findings have important implications for models of septo-hippocampal coordination and the functional segregation between online (theta) and offline (SWR) network states. That said, there are a few conceptual and methodological issues that need to be addressed.

One concern is the overall novelty of this work; the dissociation between online temporal sequence and offline replay events following memory deficits has previously been shown by Wang et al., 2016 elife. While the authors discuss Lui et al., 2023, which demonstrates MEC activation of inhibitory neurons at gamma frequencies during locomotion disrupts theta sequences, subsequent replay and learning (line 65-66), they do not reference Wang et al., 2016 who performed a very similar study with MS pharmacological inactivation, and report large decreases in theta power, attenuated theta frequencies together with behavioural deficits but SWR replay persisted. Given strong similarities in the manipulation and findings, this study should be discussed.

Along the same lines, it should be noted that Brandon et al. (2014, Neuron) demonstrated that hippocampal place codes can still form in novel environments despite MS inactivation and loss of theta, indicating that spatial representations can emerge without intact septal drive. Referencing this study would strengthen the discussion of how temporal coordination, rather than spatial coding per se, underlies the learning deficits observed here.

The conclusion that disrupting "theta microstructure" impairs learning relies on the assumption that the observed behavioral deficits arise from altered temporal coding from within hippocampal CA1 only. However, optogenetic modulation of medial septal PV neurons influences multiple downstream regions (entorhinal cortex, retrosplenial cortex) via widespread GABAergic projections. While the authors do touch on this, their discussion should expand to include the network-level consequences of entorhinal grid-cell disruption and how this could affect temporal coding both online and offline.

The finding that replay content, rate, and duration are unchanged is critical to the paper's claim of dissociation. However, the analysis is restricted to immobility on the track. Given evidence for distinct awake vs. sleep replay, confirming that off-track rest and post-session sleep replays are similarly unaffected would confirm the conclusions of the paper. If these data are unavailable, the limitation should be acknowledged explicitly. Moreover, statistical power for detecting subtle differences in replay organization or spatial bias should be added to the supplement (n of events per animal, variability across sessions).

The exact protocol for optogenetic stimulation is a bit confusing. For the task, the first and final third (66%) of trials were disrupted and were only stimulated when away from the reward well and only when the animal was moving. What proportion of time within "stimulated" trials remained unstimulated? Why were only 66% of trials stimulated?

Author response:

We thank all reviewers for their overall assessment, thoughtful comments, and suggestions. We are working to address each reviewer’s comment in detail. In this provisional response, we provide clarifications regarding our experimental approach and the novelty of our work, and include additional analyses that we have performed since the submission of the manuscript. We are also happy to report that we have now shared the raw data, intermediate analysis files, and the complete repository to facilitate replication of the analysis and figures.

Code repo: github.com/LorenFrankLab/ms_stim_analysis

Data repo: dandiarchive.org/dandiset/001634

Docker containers (see GitHub repo for use instructions):

Database: https://hub.docker.com/r/samuelbray32/spyglass-db-ms_stim_analysis

Python notebooks: https://hub.docker.com/r/samuelbray32/spyglass-hub-ms_stim_analysis

(1) Novelty and contrast with earlier manipulations:

We thank the reviewers for suggesting that we explicitly contrast our results with prior pharmacological (Wang et al., 2016; Wang et al., 2015; Koenig et al., 2011; Brandon et al., 2014), systemic (Robbe & Buzsaki 2009; Petersen and Buzsáki 2020), and behavioral (Drieu et al., 2018) manipulations that also assessed some of the physiological features we evaluated. We will add a discussion of these studies, which will help us emphasize both the insights and discrepancies observed using these prior approaches. We will also more clearly explain the the novelty and importance of our specific approach for temporally and physiologically precise manipulation. Specifically, our approach (closed-loop theta-phase stimulation during locomotion) provides a level of physiological specificity that made it possible to dissociate theta-state dynamics from other hippocampal processes. This in turn allowed us to address a question that has remained unresolved across prior studies: Are hippocampal spatial sequences during locomotion (i.e., theta sequences) necessary to learn a novel hippocampal-dependent task?

(2) Additional analysis on SWRs during rest:

since submitting the manuscript, we have conducted additional analysis on the rate and length of SWRs in the rest box and found that their rate and length are also indistinguishable between targeted and control animals (effect of manipulation between control and targeted animals; rSWR rate: p=0.45; rSWR length: p=0.94, mixed effect model). We also find evidence for sequential neural representations in the rest box, when the encoding was performed in the behavioral arena. Example trajectories are shown below. These results are consistent with our observations on SWRs rate, length, and content in the behavioral arena. Additionally, we are in the process of evaluating and quantifying the results of decoding the rSWRs and will include those in the next version of the manuscript.

Author response image 1.

Sequential replay events observed in the rest box

(3) Theta sequence measurement in the absence of theta:

In the next version of the manuscript, we will explicitly explain why our manipulation makes it is more appropriate to measure sequential hippocampal representations during locomotion (i.e., theta sequences) without using theta oscillation or an epoch-averaged relatively large sliding window as a reference. The key insight here is that our manipulation suppresses theta and thus makes it difficult or impossible to accurately identify theta phase. We understand that theta-phase based approaches were used in prior work; however, these prior analyses may have confounded the absence of hippocampal theta sequences during locomotion by the inability to detect theta oscillatory phase reliably. We will show that our method of using clusterless Bayesian decoding in which we estimate the decoded position at every 2ms timestep is indeed able to capture endogenous hippocampal sequences even without imposing any requirements of aligning to theta oscillations, thus providing an unbiased estimate of the rhythmicity of hippocampal spatial representations.

(4) Additional analysis on place cell stability and tuning:

We thank the reviewer for this question. For the KL divergence analysis, we have imposed a spike-count criterion (100 spikes for each interval type —stimulation-off, stimulation-on, and the stimulus sub-interval) and a coverage criterion (50% HPD of the units’ spatial firing distribution was contained within 40cm on the linear track and 100cm on the w-track). These criteria were chosen to ensure that spatial tuning curves were sufficiently well sampled and localized to allow reliable estimation of KL divergence, which is particularly sensitive to noise arising from low spike counts or diffuse firing. Based on the reviewer’s suggestion, we have relaxed the unit inclusion criteria for KL divergence by relaxing the criteria for number of spikes and spatial coverage criterion to include more weakly tuned place cells and replicated our results (p=.146). Further, we have also evaluated the stability of place field order between stimulation-on and stimulation-off conditions using more standard methods (as in Wang et. al., 2015; spearman correlation of place field order, control vs targeted, p = .920, t-test). These results are consistent with our observations about place field stability during stimulation-off and stimulation-on conditions (Fig. 2F).

Author response image 2.

Spearman correlation of place field order during stimulation-on and stimulation-off conditions.

Cher Tony Gheeraert,

Merci pour cet article, que j'ai vraiment apprécié. Parce que c'est une chronique, elle pourrait être publiée telle quelle. j'ai fait un certain nombre de commentaires, que vous être libre d'utiliser ou non, qui ne s'insèrent pas toujours dans la logique de l'article (reprendre la théorie marxiste de la création de valeurs et essayer de l'appliquer à la situation présente de l'IA) et que vous êtes bien évidemment libre de reprendre ou non.

Reprenons les différents critères d'évaluation :

Pertinence de la réflexion

Cet article propose une relecture marxiste de l'économie de l'IA générative, de la bulle spéculative qu'elle forme, etc. Même pour un non-marxiste, cette relecture est intéressante: dans mon expérience de chercheur non-marxiste, les écrits marxistes (orthodoxes ou hétérodoxes) m'ont toujours forcé à regarder des situations avec un autre regard et, donc, à varier mes analyses.

Deux exemple: le livre de Gavin Mueller qui essaye de réconcilier luddisme et marxisme (Mueller Gavin, Breaking things at work: the Luddites are right about why you hate your job, London New York, Verso, 2021.) J'avoue que je me contrefiche un peu de la compatibilité du luddisme avec le marxisme (sauf par intérêt historique). Mais cela a poussé Mueller à analyser la nature du mouvement du logiciel libre comme forme de luddisme technophile, idée que je repends depuis à mon tompte.

Second exemple, très loin de ce qui nous préoccupe ici: ce sont notamment des analyses marxistes hétérodoxes qui ont poussé les historiens et historiennes à regarder de plus près les politiques financière, budgétaires des dictatures fascistes et nazies, dès la fin des années 1940.

Le seul problème de cette démarche de relecture marxiste est qu'elle peut être souvent frustrante pour le lecteur. Est-ce qu'il y a des moyens d'éviter cela, je n'en suis pas sûr.

Je reste cela dit peu convaincu par l'entrée en matière de l'article. Le texte de gemini est vraiment mauvais et caricatural (et en outre, j'aime bien avoir les prompts quand quelqu'un cite une IA).

Subjectivité et démarche

Je renvoie à la section précédente sur ce point, car la démarche, une relecture marxiste, y est bien commentée.

Contribution au champ disciplinaire

Il est indéniable que cet artcile participe à quelque chose d'important, démystifier l'IA générative. Ce que je regrette un peu, c'est le fait que l'auteur ne fait pas complètement le tri (de manière explicite, s'entend) entre certains mythes de l'IA et la réalité économique de l'IA. Je reconnais que c'est assez difficile, dans la mesure où certains éléments relèvent des deux, la question de la bulle spéculative en premier lieu. Mais on a parfois l'impression que lauteur succombe lui-même un peu au mythe de l'IA (ce que je ne juge pas, moi-même y succombant parfois aussi). Mais je ne peux qu'être d'accord avec la logique d'ensemble de l'article et notamment la section "Par-delà « le libre »".

Avis général sur la publication

Comme c'est une chronique, je dirais que l'article peut être publié sans modification. À l'auteur, ou à l'éditeurice, de voir s'il souhaite prendre en compte certaines de mes remarques.

Bien à vous.

oui! C'est aussi le raisonnement de Bender et Hannah dans The AI Con.

eLife Assessment

This is a useful study that investigates the role of the long non-coding RNA Dreg1 for the development, differentiation, or maintenance of group 2 ILC (ILC2). The authors generate Dreg1-/- mice and show a reduction of group 2 innate lymphoid cells (ILC2). However, the strength of evidence supporting the impact of Dreg1 on Gata3 expression, a transcription factor required for ILC2 cell fate decisions, and the cell-intrinsic requirement of Dreg1 for ILC2 remain incomplete. This study will be of interest to immunologists.

Reviewer #1 (Public review):

Summary:

This study examines the role of the long non-coding RNA Dreg1 in regulating Gata3 expression and ILC2 development. Using Dreg1-deficient mice, the authors show a selective loss of ILC2s but not T or NK cells, suggesting a lineage-specific requirement for Dreg1. By integrating public chromatin and TF-binding datasets, they propose a Tcf1-Dreg1-Gata3 regulatory axis. The topic is relevant for understanding epigenetic regulation of ILC differentiation.

Strengths:

(1) Clear in vivo evidence for a lineage-specific role of Dreg1.

(2) Comprehensive integration of genomic datasets.

(3) Cross-species comparison linking mouse and human regulatory regions.

Weaknesses:

(1) Mechanistic conclusions remain correlative, relying on public data.

(2) Lack of direct chromatin or transcriptional validation of Tcf1-mediated regulation.

(3) Human enhancer function is not experimentally confirmed.

(4) Insufficient methodological detail and limited mechanistic discussion.

Reviewer #2 (Public review):

The authors investigate the role of the long non-coding RNA Dreg1 for the development, differentiation, or maintenance of group 2 ILC (ILC2). Dreg1 is encoded close to the Gata3 locus, a transcription factor implicated in the differentiation of T cells and ILC, and in particular of type 2 immune cells (i.e., Th2 cells and ILC2). The center of the paper is the generation of a Dreg1-deficient mouse. While Dreg1-/- mice did not show any profound ab T or gd T cell, ILC1, ILC3, and NK cell phenotypes, ILC2 frequencies were reduced in various organs tested (small intestine, lung, visceral adipose tissue). In the bone marrow, immature ILC2 or ILC2 progenitors were reduced, whereas a common ILC progenitor was overrepresented, suggesting a differentiation block. Using ATAC-seq, the authors find that the promoter of Dreg1 is open in early lymphoid progenitors, and the acquisition of chromatin accessibility downstream correlates with increased Dreg1 expression in ILC2 progenitors. Examining publicly available Tcf1 CUT&Run data, they find that Tcf1 was specifically bound to the accessible sites of the Dreg1 locus in early innate lymphoid progenitors. Finally, the syntenic region in the human genome contains two non-coding RNA genes with an expression pattern resembling mouse Dreg1.

The topic of the manuscript is interesting. However, there are various limitations that are summarized below.

(1) The authors generated a new mouse model. The strategy should be better described, including the genetic background of the initially microinjected material. How many generations was the targeted offspring backcrossed to C57BL/6J?

(2) The data is obtained from mice in which the Dreg1 gene is deleted in all cells. A cell-intrinsic role of Dreg1 in ILC2 has not been demonstrated. It should be shown that Dreg1 is required in ILC2 and their progenitors.

(3) The data on how Dreg1 contributes to the differentiation and or maintenance of ILC2 is not addressed at a very definitive level. Does Dreg1 affect Gata3 expression, mRNA stability, or turnover in ILC2? Previous work of the authors indicated that knockdown of Dreg1 does not affect Gata3 expression (PMID: 32970351).

(4) How Dreg1 exactly affects ILC2 differentiation remains unclear.

When I think about how data is used on the web, I think the concept of "utility computing" is actually useful, because it reminds us: do we really see all the data before deciding whether something is "more beneficial than harmful"? Many times we only use the information we have, but the missing data may be the most important part. I also agree with the text about "harmful ignorance", because in reality, it is really easy for people to ignore some data that makes them uncomfortable or not in line with their own position, so the results will be more like supporting the choice they want to make. This is especially true in social media and algorithmic recommendations, where we may be seeing things that are already filtered, so if we don't ask, "What's missing?" we may be biased in our utility calculations.

I agree with this piece of info, I believe that it is helpful to know the bigger picture. When completing calculations with data, it is vital that we have all of the correct data and information.

It may be also important to know the expected utility, if surveyed for potential affected persons, their responses may not be the truth. A person will never know what a punch feels like until it hits them. Building off of simplification of of data, what one person feels may not be what another ends up feeling. Thus, net utility is never one hundred percent certain.

One example I can think of for pernicious ignorance is an art influencer on social media doing a paid ad for an AI company. Even though AI is a huge threat to other artists, the influencer I saw either chose to disregard or avoid learning this fact. Their promotion of it only encourages their fans (who are likely also artists or interested in the subject) to support AI that could put them out of jobs.

The realization that "text" on social media encompasses more than just English letters, but also spaces, punctuation, characters from diverse languages, and emojis, was significant. Inconsistent encoding or character handling can result in garbled text, inaccurate length calculations, and adverse effects on subsequent text cleaning, keyword statistics, and sentiment analysis. Consequently, preprocessing strings is essential prior to undertaking data analysis.

This got me thinking: numbers aren't kept with perfect accuracy. Memory constraints and the way data types are defined lead to floating-point errors, rounding discrepancies, and the potential for overflow. When we apply this to social media analytics, it means that those "objective" metrics we rely on—likes, retweets, and the like—can also be affected by calculation and display errors. Consequently, we need to factor in these technical limitations when we analyze the results.

I think it’s interesting how bots are frequently used to push a certain message, often political. While this may be able to boost positive movements and spread information, it is a dangerous capability and misconstrues the true standings of most people’s beliefs.

This is an impetus in my own research! My work deals with the ways in which algorithms shape identity construction, and the role they serve in mediating culture. This importance means that the designers of the algorithm have undue influence over the flow of culture and subcultures that exists on these platforms, despite not being participatory in these subcultures nuances and needs. For example, a white coder who is in charge of some textual aspect of the algorithm might not include autocomplete options which reflect the language nuances of black or brown users. This aspect of coding is in my opinion one of the most important concepts related to digital existence today.

I think this is an interesting data with constraints that shift along cultural axes. While the other data types like age, name, and address can vary from culture to culture (such as characters used to input), the answers will all be relatively similar. People might for example measure their age using different calendars, or by amount of winters experienced, but a full annual cycle is used pretty much worldwide. For relationship status though, there are a lot of variables even in one culture that must be negotiated. Does dating count as different than a relationship? What about new terms like situationship? What about cultures with multiple partners? There's so many value judgements about what counts as a relationship in the act of reifying it in code. It makes me think about the ways in which our cultural ideology is represented in code, more than we often think about.

I found that many websites have different gender options. I think it's a hard option to collect. Many times what everyone thinks gender is not even on the website. In order to be fair and treat each user equally, we need to provide them with the most appropriate options.

Is it necessary to have a character limit for personal information like this? I feel like in a way, that can be a little demeaning for those with longer last names, especially because I feel like some ethnic groups have names that might go over the character limit.

I think this applies heavily to the ethics and also generalization that social media programmers make. It's difficult to find a balance between catering towards a certain audience or the majority while also maintaining freedom and inclusivity to create and navigate these apps and programs.

Are these relationships similar to those we would find in an ecosystem? I never thought about microbe-microbe interactions, and how that could affect the microbiome.

Host-microbe interactions are the whole reason why we study microbiology, and that relationship is super important.

An important concept is that there are not many parasitic microbes, but the ones that are parasitic have had a huge impact on the world. This is why so many people are afraid of microbes, because they think they are all bad and harmful.

This is super important and I like how the concept of diversity is important for pretty much everything in science.

I wonder what changed this to the point of when women barely had any rights.

good rule of thumb to really understand the reading

looking at it from a different perspective

I think it’s very important to understand the certain types of patterns and how they can be used.

This is a key distinction that literary analysis applies to literature.

Emphasizes the part of literary analysis that is a structured method of looking at texts closely.

Did they think they were going to be the first to discover the land?

This paragraph highlights that a memory is held by an individual, but is shaped and formed by a group. It is these groups that give the memory a significance and structure.

I think it works both ways. The present can explain the past, past can explain the present. The present can shape how the past is remembered and the past can shape how we interpret the present. It's all a collective memory.

Thanksgiving was created based on society's needs, and its meaning was shaped and revised over time based on people.

This ties back to what I assumed about the tradition of Thanksgiving football. Time to spend all your money and punch people in the face on black friday, because that's what the season is really all about, right?

This was my experience growing up. The story of the Pilgrims and Native Americans was celebrated, but the darker history was seldom talked about.

Interesting shift in the view of sports through the eyes of Christians.

I had no idea that the tradition of Football on Thanksgiving dated all the way back to the 19th century. I would've assumed it was a more modern thing meant to sell advertisements on television and radio.

Uncle Sam's Thanksgiving shows the need for unity after the tumultuous years of the Civil War and Reconstruction.

Despite the fact that the American Revolution wouldn't happen for another 150 years. Interesting to consider the Pilgrims "Patriotic"

New memories can also be added, changing some traditions for the better.

And some people today outright refuse to celebrate Thanksgiving due to the past treatment of Native Americans. I'm not one of those people, but that's because when I think of Thanksgiving, I think of cooking a meal and spending time with my family. No one has to venerate the past if they don't want to.

How come if they had boats and other technologies for travel did they not bring animals over?

I wonder how some communities were so much more advanced than others.

I've heard the term metadata a few times in the past, but never understood what it meant. It now makes a lot of sense that it's data about data. It's helpful to know about the data we're collecting

I've always heard the term metadata but never really knew what it meant. Very interesting to see how it is categorized and the amount of information metadata contains.

This example provides a very clear explanation of what metadata is. I used to struggle with understanding or defining metadata, but this helped me realize that metadata refers to the contextual details about the main data. For instance, if a product’s ingredients are the main data, then information about when the ingredients were purchased or the composition of those ingredients would be the metadata.

This part made me realize how “metadata” can be just as revealing as the main content, even if it seems harmless—like time, location, or who replied. In social media, you can sometimes learn more from patterns in metadata (posting frequency, networks, timing) than from what someone actually said. It also feels like a big privacy issue, because people might not realize they’re “sharing” all that extra info just by using a platform.

I wonder where the original idea of a pyramid originated from. And its crazy to me how buildings like apartment complexes have been around for so long.

Was this one of the earliest written languages documented?

I think I will be most interested in how the things we eat affect our skin health, coming from someone who has struggled with acne for a long time. This would be super beneficial for me to maybe find some foods that can help acne.

This is definitely something I dread, but I need to be more comfortable with reading them so this is the perfect opportunity to learn in a comfortable setting.

This is super exciting to learn about as someone who is passionate about nutrition and wellness. We truly are what we eat!

Student hours are meant to assist students with understanding and improving upon course material. These hours are highly encouraged and are available during the set hours or when an instructor is available to meet.

This information and examples are very helpful, informative and important for all. We are surrounded with people with different cultures, religions and beliefs and should try to be open-minded.

This connects very well with me because I am an emotional mess. Stress and anxiety can interfere with daily life and struggles for not just me but for many.

This means that when you "lock yourself in" to a person or a goal you love, you finally feel like you have a purpose, which is the realest kind of freedom.

logos- logical comparison

logos- data

pathos- inspiring

ETHOS He practices what he preaches

The Author: David Brooks (a well-known columnist).

The Problem : People are lonelier than ever. Statistics show that marriage, dating, and even hanging out with friends are at record lows.

The Audience: Mostly young people (Gen Z) and adults who feel disconnected or overwhelmed by work and "independence."

The Goal: To convince you that being "independent" is lonely, and that committing to things (like a partner, a hobby, or a community) is what actually makes life happy.

Shrinking habitat space must be more and more heavily managed and maintained the smaller it is, as it becomes less and less self-sustaining, and is cut off more and more to become (in some cases) a sort of 'inland island". Consider also the ongoing cost of defending these spaces in public policy.

What to remember from this? Conservation of large predators is very complicated. The actual territory size of the animal is almost irrelevant in comparison to the range requirements of the other species it relies on.

A college writing course is necessary for a student because writing plays a crucial role in every major and career, due to it being a way of communicating. Enrolling in a writing course also helps students develop greater skills that will benefit them in the future.

This quote reminds me how often experts dismiss criticism by calling it “emotional” or “uninformed.” It’s important to always remember / acknowledge that emotional reactions can reveal ethical blind spots.

This metaphor flips the researcher's perspective in a haunting way. It helps me understand how even well-meaning data collection can feel invasive or oppressive to those being observed.

This shows why rules aren’t enough in fast-changing tech environments. The idea that ethical reasoning should be communicated. It adds a layer of transparency to the ethics process.

the mountain gets so thin its like a model's catwalk

the peak in this context provides a safety like a home

simile

example of taxonomy

simile

despite the sea teaching harsh lessons about life to the author it's also a place of relaxation for them not only because of the childhood memories but also because it also shows with chaos there is also calmness

metaphor to describe the strong current the sea is not literally against her

describing every color in the 'scene' makes it come to life

It it important to understand the ideas and text

let's party

Comment

basically people watching to see how they act naturally

I think that likes, comments, shares and recent activities should be immediately accessible. I think that within the share feature users should have access to multiple different methods of sharing (copy link, send on iMessages, etc.)

key point for review

key point for review

I wonder if them saying that the first woman was born from the first feather means anything. It makes you think that the first humans were created through more delicate means than just simply evolving over millions of years. I think it was a beautiful way to represent the emergence of humans.

The Cherokee believe that the Earth is being held up with seemingly invisible chords or strings that stretch to the heavens which I think is a very interesting way to think about it.

But what if a student doesn't budge/reflect on their interpretation and without facilitator/peer guidance comes to fully believe their incorrect interpretation?

this is the WORST!

But what is they are objectively incorrect intepretations?

Each commit is going to save permanent snapshots of the project

I really like how the whole class is centered around community and I wonder how different it will be to write about community in 3 different ways for each paper.

This section makes it click that a “tweet” isn’t just one thing—it’s basically a bundle of lists (a list of images, a list of likes, a list of replies, etc.). Thinking of it that way also helps explain why social media data gets huge fast, because each post can point to multiple growing lists. It’s kind of wild that even something simple like “who liked this” is literally stored as a list of accounts behind the scenes.

What comes to mind when I'm meeting my friends out has to be the sounds and what I seen. Before reading this text I never realized how much I actually communicate with myself. Every action I take my inner monologue is talking like right now as I'm typing this response.

After reading the article, it is true everything said above. I don't think about a lot of the behavioral stuff most of the time just because I am still working on making sure the music sounds good. I think for the most part all you need to do is be Christian and a lot of these problems get solved. You need a good fear of God so that you give mercy to those who are around you.

Take my advice about the same river!