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Parmjit

Design is also practice, it's a step in-between theory and application. It's about understanding logistics from the inside without causing real havoc or backfire. It's about learning to predict, to see the holes and gaps that may arise before they do. Design, at the end, is about bridging the theory-application divide. It helps solidfy theories while seeing their limitations in a safe space, dispelling the myth of sudden talent (from an illusion of explanatory depth), and warning against creeping normality by remaining revisionist (iterating) through the practice.

eLife Assessment

The authors investigated the potential role of IgG N-glycosylation in Haemorrhagic Fever with Renal Syndrome (HFRS), which may offer significant insights for understanding molecular mechanisms and for the development of therapeutic strategies for this infectious disease. The findings are thought to be valuable to the field and the strength of evidence to support the findings is solid.

Reviewer #1 (Public review):

Summary:

The authors investigated the potential role of IgG N-glycosylation in Haemorrhagic Fever with Renal Syndrome (HFRS), which may offer significant insights for understanding molecular mechanisms and for the development of therapeutic strategies for this infectious disease.

Comments on revisions:

While the majority of the issues have been addressed, a few minor points still remain unresolved.

Quality control should be conducted prior to the analysis of clinical samples. However, the coefficient of variation (CV) value was not provided for the paired acute and convalescent-phase samples from 65 confirmed HFRS patients, which were analyzed to assess inter-individual biological variability. It is important to note that biological replication should be evaluated using general samples, such as standard serum.

Reviewer #2 (Public review):

This work sought to explore antibody responses in the context of hemorrhagic fever with renal syndrome (HFRS) - a severe disease caused by Hantaan virus infection. Little is known about the characteristics or functional relevance of IgG Fc glycosylation in HFRS. To address this gap, the authors analyzed samples from 65 patients with HFRS spanning the acute and convalescent phases of disease via IgG Fc glycan analysis, scRNAseq, and flow cytometry. The authors observed changes in Fc glycosylation (increased fucosylation and decreased bisection) coinciding with a 4-fold or greater increased in Haantan virus-specific antibody titer. The study also includes exploratory analyses linking IgG glycan profiles to glycosylation-related gene expression in distinct B cell subsets, using single-cell transcriptomics. Overall, this is an interesting study that combines serological profiling with transcriptomic data to shed light on humoral immune responses in an underexplored infectious disease. The integration of Fc glycosylation data with single-cell transcriptomic data is a strength.

The authors have addressed the major concerns from the initial review. However, one point to emphasize is that the data are correlative. While the associations between Fc glycosylation changes and recovery are intriguing, the evidence does not establish causation. This is not a weakness, as correlative studies can still be highly valuable and informative. However, the manuscript would be strengthened by making this distinction clear, particularly in the title.

Author response:

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

Reviewer #1 (Public review):

(1) The authors should provide a detailed description of the pathogenesis of Haemorrhagic Fever with Renal Syndrome (HFRS) and elaborate on the crucial role of IgG proteins in the disease's progression (line 65).

As suggested, we have now provided a detailed description of the pathogenesis of HFRS and elaborated on the crucial role of IgG proteins in the disease's progression:

"Hantaviruses are tri-segmented, single-stranded, negative-sense RNA viruses, whose genomes consist of three regions: large (L), medium (M), and small (S). The glycoproteins Gn and Gc, encoded by the M segment, can infect target cells - primarily vascular endothelial cells - via β3 integrin receptors (Pizarro et al., 2019). Simultaneously, they could also infect other cell types, such as mononuclear macrophages and dendritic cells, leading to systemic viral infection. Although hantavirus replication is thought to occur primarily in the vascular endothelium without direct cytopathic effects, a plethora of innate immune cells mediate host antiviral defenses. These include natural killer cells, neutrophils, monocytes, and macrophages, together with pattern recognition receptors (PRRs), interferons (IFNs), antiviral proteins, and complement activation, e.g., via the pentraxin 3 (PTX3) pathway, which can exacerbate HFRS disease progression leading to immunopathological damage through cytokine/chemokine production, cytoskeletal rearrangements in endothelial cells, ultimately amplifying vascular dysfunction (Tariq & Kim, 2022). Rapid and effective humoral immune responses, however, such as neutralizing antibody responses targeting the glycoproteins Gn/Gc, contribute to rapid recovery from HFRS and are critical for protection from severe disease (Engdahl & Crowe, 2020; Li et al., 2020)." Please see the Introduction (Page 4, lines 65-81).

(2) An additional discussion on the significance of glycosylation, particularly IgG N-glycosylation, in viral infections should be included in the Introduction section.

Thank you for the suggestion and we have added an additional discussion on the significance of glycosylation in viral infections in the revised Introduction section.

"Immunoglobulin G (IgG) N-linked glycosylation mediates critical functions modulating antiviral immunity during viral infection. Changes in the conserved N-linked glycan Asn297 in the Fc region of IgG typically by fucosylation, galactosylation, or sialylation can alter antibody effector function. A reduction in core fucosylation decreases IgG binding to NK cell FcγRIIIa promotes antibody-dependent cellular cytotoxicity (ADCC) necessary for clearance of viruses, including SARS-CoV-2, dengue and HIV-1 whereas sialylation can attenuate immune responses resulting in immune evasion (Ash et al., 2022; Haslund-Gourley et al., 2024; Hou et al., 2021; Wang et al., 2017). Changes in IgG and other protein N-linked glycosylation profiles therefore shape virus-host interactions and disease progression." (Page 4, lines 82-91).

(3) In the abstract section, the authors state that HTNV-specific IgG antibody titers were detected and IgG N-glycosylation was analyzed. However, the analysis of plasma IgG N-glycans is described in the Methods section. Therefore, the authors should clarify the glycome analysis process. Was the specific IgG glycome profile similar to the total IgG N-glycome? Given the biological relevance of specific IgG in immunological diseases, characterizing the specific IgG N-glycome profile would be more significant than analyzing the total plasma IgG.

We are grateful to the reviewer for the comments. Previous studies on viral infections have revealed that the pattern of virus-specific IgG N-glycans may be similar to that of total IgG N-glycome, and we therefore analyzed the total plasma IgG glycosylation profiling in the HFRS patients. However, we have discussed this in the Discussion section.

"Despite establishing a well-characterized patient cohort and performing systematic IgG glycosylation profiling based on HTNV NP antibody status, this study has several noteworthy limitations. Most notably, while preliminary comparisons suggested similar patterns between virus-specific and total IgG N-glycome, our total plasma IgG analysis may have introduced confounding factors in the observed associations. This methodological constraint could potentially affect the interpretation of certain disease-specific glycosylation signatures." Please see the Discussion (Page 12, lines 274-280). 

References

(1) Mads Delbo Larsen, Erik L de Graaf, Myrthe E Sonneveld, et al. Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity. Science . 2021 Feb 26;371(6532):eabc8378.

(2) Chakraborty S, Gonzalez J, Edwards K, et al. Proinflammatory IgG Fc structures in patients with severe COVID-19. Nat Immunol. 2021 Jan;22(1):67-73.

(3) Tea Petrović, Amrita Vijay, Frano Vučković, et al. IgG N-glycome changes during the course of severe COVID-19: An observational study. EBioMedicine. 2022 Jul ;81: 104101. 

(4) Hou H, Yang H, Liu P, et al. Profile of Immunoglobulin G N-Glycome in COVID-19 Patients: A Case-Control Study. Front Immunol. 2021 Sep 23;12:748566.

(4) Further details regarding the N-glycome analysis should be provided, including the quantity of IgG protein used and the methodology employed for analyzing IgG N-glycans (lines 286-287).

As suggested, we have provided further details regarding the N-glycome analysis in the Method section.

"Briefly, the diluted plasma samples were transferred onto a 96-well protein G monolithic plate (BIA Separations, Slovenia) for the isolation of IgG. The isolated IgG was eluted with 1 mL of 0.1 M formic acid and was immediately neutralized with 170 µL of 1M ammonium bicarbonate.

The released N-glycans were labelled with 2-aminobenzamide (2-AB) and were then purified from a mixture of 100% acetonitrile and ultrapure water in a 1:1 ratio (v/v). This was then analyzed by hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC; Walters Corporation, Milford, MA) (Hou et al., 2019). As previously reported, the chromatograms were separated into 24 IgG glycan peaks (GPs) (Menni et al., 2018)." Please see the Method section (Page 15, lines 346-355).

(5) Additional statistical analyses should be performed, including multiple comparisons with p-value adjustment, false discovery rate (FDR) control, and Pearson correlation (line 291).

As suggested, we have performed additional statistical analyses and mentioned the results in the revised manuscript.

"Positive correlations were observed between the ASM subsets and both galactosylation (p=0.017, r_s=0.418) and sialylation (p=0.008, r_s=0.458) in the antibody Fc region, as well as between the PB subsets and sialylation (p=0.036, r_s=0.372) (Figure 4A-C). (Page 8, lines 180-183)"

"The Benjamini - Hochberg (BH) method was used to adjust the raw p-values from DEG analysis, controlling the false discovery rate (FDR)." Please see the Materials and Methods (Page 16, lines 369-371).

(6) Quality control should be conducted prior to the IgG N-glycome analysis. Additionally, both biological and technical replicates are essential to assess the reproducibility and robustness of the methods.

Thank you for the suggestion. We have added descriptions on the biological and technical replicates in the Method section.

"Our study incorporated both biological and technical replicates to ensure a robust glycomic profiling analysis. Specifically, we analyzed paired acute/convalescent-phase samples from 65 confirmed HFRS patients to assess inter-individual biological variability, while technical reproducibility was validated through comparison with standard chromatographic peak plots (Vučković et al., 2016). This dual-replicate strategy enabled a comprehensive evaluation of both biological heterogeneity and assay precision." (Page 15, lines 356-362).

(7) Multiple regression analysis should be conducted to evaluate the influence of genetic and environmental factors on the IgG N-glycome.

As suggested, we have conducted multiple regression analysis to evaluate the influence of genetic and environmental factors on the IgG N-glycome. These results have been provided in the revised Result section.

"Multivariate linear regression was employed to mitigate potential confounding by genetic and environmental factors in the glycomics analysis. While no significant associations were observed for most glycan models (fucosylation, p=0.526; bisecting GlcNAc, p=0.069; and sialylation, p=0.058), we discovered sex showed a potentially influential effect on galactosylation (p=0.001) (Supplementary files 5-8). These results suggest that while most glycan features appear unaffected by the examined covariates, galactosylation may be subject to sex-specific biological regulation." (Page 7, lines 153-160).

(8) Line 196. Additional discussions should be included, focusing on the underlying correlation between the differential expression of B-cell glycogenes and the dysregulated IgG N-glycome profile, as well as the potential molecular mechanisms of IgG N-glycosylation in the development of HFRS.

Thank you for your suggestions. We have added these contents in the Discussion section.

"Antibody-related glycogenes are significantly activated following Hantaan virus infection. We noted that ribophorin I and II (RPN1 and RPN2) were significantly upregulated in the ASM/IM/PB/RM subsets after Hantaan virus infection, which linked the high mannose oligosaccharides with asparagine residues found in the Asn-X-Ser/Thr consensus motif (Hwang et al., 2025). We speculate that they continuously attach the synthesized glycan chains to the constant region of antibodies during antibody synthesis. Similarly, fucosyltransferase 8 (FUT8) in the ASM subset, catalyzing the alpha1-2, alpha1-3, and alpha1-4 fucose addition (Wang & Ravetch, 2019; Yang et al., 2015), was downregulated in the mRNA translation, and the levels of fucosylated antibodies were naturally lower in the acute HFRS patients. Meanwhile, the beta-1,4-galactosyltransferase (beta4GalT) gene expression was significantly elevated in the ASM subpopulation during the acute phase, which also correlated with increased levels of galactosylated antibodies in serum (Wang & Ravetch, 2019). However, we did not observe significant upward changes in sialyltransferase mRNA expression in the acute HFRS patients, similar with the finding from severe COVID-19 cohorts (Haslund-Gourley et al., 2024). The neuraminidase 1 (NEU1) gene is strikingly upregulated and may potentially explain the decreased sialylation on the secreted HTNV-specific IgG antibodies during convalescence. Overall, the glycosylation of immunoglobulin G is regulated by a large network of B-cell glycogenes during HTNV infection." Please see the Discussion (Page 11, lines 254-273).

Reviewer #2 (Public review):

(1) While it is great to reference prior publications in the Materials and Methods section, the current level of detail is insufficient to clearly understand the study design and experimental procedures performed. Readers should not be expected to consult multiple previous papers to grasp the core methodological aspects of the present paper. For instance, the categorization of HFRS patients into different clinical subtypes/ courses, and the methods for measuring Fc glycosylation should be explicitly described in the Materials and Methods section of this manuscript. 

Many thanks for your comments. We have added more details regarding the study design and experimental procedures in the Materials and Methods section. "Clinical specimens were collected from HFRS patients who were hospitalized in Baoji Central Hospital between October 2019 and January 2022. Patients were categorized into four clinical subtypes (mild, moderate, severe, and critical) based on the diagnostic criteria for HFRS issued by the Ministry of Health (Ma et al., 2015). This study was approved by the ethics committee of the Shandong First Medical University & Shandong Academy of Medical Sciences (R201937). Written informed consent was obtained from each participant or their guardians.

The clinical course of HFRS is grouped into acute (febrile, hypotensive, and oliguric stages) and convalescent (diuretic and convalescent stages) phases. The acute phase was defined as within 12 days of illness onset, and the convalescent phase was defined as a period of illness lasting 13 days or longer (Tang et al., 2019; Zhang et al., 2022). The earliest sample was selected if there were multiple blood samples available in the acute phase and the last available sample before discharge was selected if there were multiple blood samples in the convalescent phase.

Briefly, the diluted plasma samples were transferred onto a 96-well protein G monolithic plate (BIA Separations, Slovenia) for the isolation of IgG. The isolated IgG was eluted with 1 mL of 0.1 M formic acid and was immediately neutralized with 170 µL of 1M ammonium bicarbonate.

The released N-glycans were labelled with 2-aminobenzamide (2-AB) and were then purified from a mixture of 100% acetonitrile and ultrapure water in a 1:1 ratio (v/v). This was then analyzed by hydrophilic interaction liquid chromatography using ultra-performance liquid chromatography (HILIC-UPLC; Walters Corporation, Milford, MA) (Hou et al., 2019). As previously reported, the chromatograms were separated into 24 IgG glycan peaks (GPs) (Menni et al., 2018)." Please see the Materials and Methods (Page 13, lines 290-303, and Page 15, lines 346-355).

(2) The authors should explain the nature of their cohort in a bit more detail. While it appears that HFRS cases were identified based on IgM ELISA and/or PCR, these are indicators of the Haantan virus infection. My understanding is that not all Haantan virus infections progress to HFRS. Thus, it is unclear whether all patients in the HFRS group actually had hemorrhagic fever. This distinction is critical for interpreting how the results observed relate to disease severity.

We are sincerely grateful for this valuable suggestion. We have carefully revised Figure 1 and the texts (Page 5, lines 104-107) in the revised manuscript.

"To characterize the humoral immune profiles in HFRS patients, we enrolled 166 suspected HTNV-infected patients who were admitted to Baoji Central Hospital in Shaanxi Province, China, between October 2019 and January 2022. Among them, 65 met the inclusion criteria and were included in the study (Figure 1)."

(3) The authors state that: "A 4-fold or greater increase in HTNV-NP-specific antibody titers usually indicates a protective humoral immune response during the acute phase", but they do not cite any references or provide any context that supports this claim. Given that in their own words, one of the most significant findings in the study is changes in glycosylation coinciding with this 4-fold increase, it is important to ground this claim in evidence. Without this, the use of a 4-fold threshold appears arbitrary and weakens the rationale for using this immune state as a proxy for protective immunity.

Thank you for the suggestion and we have provided relevant references in the Results section (Page 8, lines 171-173).

According to the Expert Consensus on Prevention and Treatment of Hemorrhagic  Fever with Renal Syndrome (HFRS) (https://ts-cms.jundaodsj.com/file/163823638693909.pdf), a confirmed diagnosis requires, based on a suspected or clinical diagnosis, one of the following: positive serum-specific IgM antibodies, detection of Hantavirus RNA in patient specimens, a four-fold or greater rise in titer of serum-specific IgG antibodies in the convalescent phase compared to the acute phase, or isolation of Hantavirus from patient specimens. A four-fold or greater rise in titer of convalescent serum-specific IgG antibodies compared to the acute phase not only suggests a recent Hantaan virus infection, but also the production of antibodies helping to combat the viral infection. In addition, the antibody glycosylation modifications may thus play a significant role in the antiviral immune response.

(4) The authors also claim that changes in Fc glycosylation influence recovery from HFRS - a point even emphasized in the manuscript title. However, this conclusion is not well supported by the data for two main reasons. First, the authors appear to measure bulk IgG Fc glycans, not Fc glycans of Hantaan virus-specific antibodies. While reasonable, this is something that should be communicated in the manuscript. Hantaan virus-specific antibodies are likely a very small fraction of total circulating IgG antibodies (perhaps ~1%), even during acute infection. As a result, changes in bulk Fc glycosylation may (or may not) accurately reflect the glycosylation state of Hantaan virus-specific antibodies. Second, even if the bulk Fc glycan shifts do mirror those of Hantaan virus-specific antibodies, it remains unclear whether these changes causally drive recovery or are merely a consequence of the infection being resolved. Thus, while the differences in Fc glycosylation observed are interesting - and it is tempting to speculate on their functional significance - the manuscript treats the observed correlations as causal mechanistic insight without sufficient data or justification.

Thank you for your valuable comments. This study measured bulk IgG Fc glycans, not Fc glycans of Hantaan virus-specific antibodies. We have described this limitation in the Discussion section (Page 12, lines 274-280). As reported in previous studies (references provided below), the changed pattern of virus-specific IgG N-glycans may reflect the total IgG N-glycome. Nevertheless, more studies are clearly needed to directly measure virus-specific IgGs and to clarify the causal mechanistic insights.

References

(1) Mads Delbo Larsen, Erik L de Graaf, Myrthe E Sonneveld, et al. Afucosylated IgG characterizes enveloped viral responses and correlates with COVID-19 severity. Science. 2021 Feb 26;371(6532): eabc8378.

(2) Chakraborty S, Gonzalez J, Edwards K, et al. Proinflammatory IgG Fc structures in patients with severe COVID-19. Nat Immunol. 2021 Jan;22(1):67-73.

(3) Tea Petrović, Amrita Vijay, Frano Vučković, et al. IgG N-glycome changes during the course of severe COVID-19: An observational study. EBioMedicine. 2022 Jul ;81: 104101. 

(4) Hou H, Yang H, Liu P, et al. Profile of Immunoglobulin G N-Glycome in COVID-19 Patients: A Case-Control Study. Front Immunol. 2021 Sep 23;12: 748566.

(5) Fc glycosylation is known to be influenced by covariates such as age and sex. While it is helpful that the authors stratified the patients by age group and looked for significant differences in glycosylation across them, a more robust approach would be to directly control for these covariates in the statistical analysis - such as by using a linear mixed effects model, in which disease state (e.g., acute vs. convalescent), age, and sex are treated as fixed effects, and subject ID is included as a random effect to account for repeated measures. This would allow the authors to assess whether observed differences in Fc glycosylation remain significant after accounting for potential confounders. This could be important given that some of the reported differences are quite small, for example, 94.29% vs. 94.89% fucosylation.

Thank you for your valuable suggestion. As suggested, we have conducted multiple regression analysis to evaluate the influence of genetic and environmental factors on the IgG N-glycome, and have provided these results in the revised Result section.

"Multivariate linear regression was employed to mitigate potential confounding by genetic and environmental factors in the glycomics analysis. While no significant associations were observed for most glycan models (fucosylation, p=0.526; bisecting GlcNAc, p=0.069; and sialylation, p=0.058), we discovered sex showed a potentially influential effect on galactosylation (p=0.001) (Supplementary files 5-8). These results suggest that while most glycan features appear unaffected by the examined covariates, galactosylation may be subject to sex-specific biological regulation." (Page 7, lines 153-160).

(6) The manuscript states that there are limited studies on antibody glycosylation in the context of HFRS, but does not cite any relevant literature. If prior work exists, it should be cited to contextualize the current study. If no prior studies have been conducted/reported, to the author's knowledge, that should be stated explicitly to show the novelty of the work.

Thank you for your suggestion. To our knowledge, there has been no prior reports regarding the regulation of IgG glycosylation in HFRS, particularly in relation to seroconversion. We have reworded this sentence in the revised manuscript. "Importantly, there have not been prior studies specifically examining plasma IgG N-glycome profiles derived from chromatographic peak data in HFRS patients, particularly in relation to seroconversion status. This gap in our knowledge motivated our systematic investigation of both total and virus-specific IgG glycosylation dynamics during acute infection." Please see the Introduction (Page 5, lines 92-96).

Reviewer #2 (Recommendations for the authors):

Minor points:

(1) Line 47, 78: The use of the word 'However' appears to be an incorrect expression.

We have made this correction.

(2) Line 127: The term 'glycome' should be replaced with 'N-glycome,' and all relevant expressions should be corrected accordingly, such as 'N-glycosylation.

We have made this correction.

(3) Line 84-87: The sentence 'A total of 166 HFRS patients...' contains a grammatical error.

We have made tis correction (Page 5, lines 99-101).

change

will 100% be on the test

Sous forme canonique ?

Il manque le dr, à reformuler pour traçer une réponse temporelle

eLife Assessment

This study addresses an important question in liver biology: how zonal hepatocytes balance survival and proliferation following injury; using spatial transcriptomics, mechanistic perturbations, and functional assays, the authors propose that a mid-zone Atf4-Chop axis to Btg2 program temporarily suppresses proliferation to promote survival during APAP-induced hepatotoxicity. The idea that distinct intrahepatic zones mount tailored stress responses is conceptually significant and has implications for regeneration and toxicology. The dataset is rich and the methodology modern, but several conclusions rely on assumptions about zonation under injury, limited injury models, and incomplete functional validation of the Atf4-Chop-Btg2 axis. With targeted revisions and additional experiments, the work has the potential to provide strong mechanistic insights into liver zonation and injury responses.

Reviewer #1 (Public review):

Summary:

The authors present evidence that during acetaminophen (APAP)-induced liver injury, mid-zone hepatocytes activate an integrated stress response (ISR) program via Atf4 and Chop, leading to induction of Btg2. This program suppresses proliferation in the early phase of injury, prioritizing hepatocyte survival before regeneration begins. The study uses spatial transcriptomics, immunohistochemistry, CUT&RUN, and AAV overexpression to support this model.

Strengths:

(1) Innovative use of spatial transcriptomics to capture zonal differences in hepatocyte stress responses.

(2) Identification of a mid-zone specific ISR signature and candidate downstream regulator Btg2.

(3) Functional experiments with Atf4-Chop-Btg2 modulation provide causal evidence linking ISR activation to proliferation inhibition.

(4) Conceptually significant model that hepatocytes actively balance survival and regeneration dynamically in a zone-specific manner.

Weaknesses:

(1) Zonation definition under injury has been shown to be sustained broadly, but is not sufficiently validated and quantified, especially considering the resolution of the 10x Visium system and the potential variation of outcomes based on how to define zones.

(2) The model is built entirely in APAP injury, which specifically targets pericentral hepatocytes. It remains unclear whether the proposed mechanism applies to other liver injuries (e.g., partial hepatectomy, CCl4).

(3) Baseline proliferation appears higher than expected in homeostasis (Figure 1B), and fold change analysis (not absolute counts) may be needed to assess zonal proliferation suppression (Figure 1D).

(4) AAV-based overexpression raises potential confounds (altered CYP activity before injury) and shows incomplete penetrance that is not quantified. (Figure 5 - Figure 6).

(5) The functional link between proliferation suppression and improved survival is inferred, but direct survival /injury readouts are limited.

Reviewer #2 (Public review):

The manuscript reports protection of midlobular hepatocytes from APAP toxicity by activation of Atf4-CHOP (Ddit3)-mediated cell cycle arrest and stress response. The authors acknowledge that their finding is unexpected because CHOP typically induces cell death. Therefore, they functionally validate several aspects of the proposed Atf4-CHOP mechanism. Along these lines, the mitigation of APAP toxicity by AAV expression of Atf4 or Btg2, the latter identified as CHOP effector, is impressive. Whether Atf4 indeed acts through CHOP and whether midlobular hepatocytes are protected because of cell cycle arrest is less clear. These and other criticisms are described in the following.

Major points:

(1) Starting with the basics, one wonders why midlobular hepatocytes manage to mount a defensive response to APAP but pericentral hepatocytes don't. Is this because midlobular hepatocytes express the relevant Cyps (2e1, but also 1a2 and 3a11) at lower levels, which mitigates toxicity and buys them time? This would be supported by F2A but not by F3B, at least not for the most important Cyp2e1. A moderate difference is shown for Cyp1a2 expression in F3D, but is that enough to explain the different fates? Or are additional post-transcriptional effects on these Cyps at work?

(2) The evidence presented in support of cell cycle arrest of midlobular hepatocytes is not fully convincing: there is no overt difference in S and G2/M gene scores in F2F; the marker genes used for S phase and G1 to S progression in F2G are unusual. Along these lines, one wonders if spatial transcriptomics confirmed the Ki67 immunostaining results in F1 also for specific zones, not only overall, as shown in F2E?

(3) The authors conclude in line 364 that halting of proliferation by Btg2 favors survival, which raises the question of whether Btg2 knockout causes death in midlobular hepatocytes in F6K. Data addressing this question, that is, the localization and extent of tissue necrosis and ALT levels after APAP, are missing. The efficiency of the knockout of Btg2 is also not given.

(4) Related to the previous question, the BTG2 immunostaining in F6F is not convincing when compared to F6D. One also wonders if it is necessary to apply APAP to find induction of BTG2 by AAV-Ddit3?

(5) Related to the previous question, the proposed Atf4-Ddit3 axis is challenged by the lack of midlobular induction of Atf4 in the APAP scRNA-seq data published by another group, presented in S4F and G. Further analysis of AAV-Atf4 samples generated for F5 could address whether it is really Atf4 that acts on Ddit3 in APAP toxicity.

(6) Related to the previous question, the ATF4 immunostaining in F5A doesn't look convincing, with many brown pigments appearing to be outside of the nucleus.

(7) It is not ruled out that AAV expression of Atf4 or Btg2 reduces hepatocyte sensitivity to APAP by affecting the expression of the Cyps needed for activation. In other words, does AAV-Atf4 or AAV-Btg2 change the expression of any of the Cyps relevant to APAP in the 3 weeks before APAP application (F5B)?

(8) It is laudable that the authors tried to extend their findings to humans by using snRNA-seq data from a published study (line 391), but it is unclear why they didn't analyze all 10 patients in that study but instead focused on 2 and stated that this small sample number prevented drawing definitive conclusions and could therefore only be mentioned in the discussion.

Reviewer #3 (Public review):

Summary:

This paper by Zhu et al explores zonal gene expression changes and stress responses in the liver after APAP injury. 3-6 hours after APAP, zone 2 hepatocytes demonstrate important gene expression changes. There is an increase in stress response/cell survival genes such as Hmox1, Hspa8, Atf3, and protein degradation/autophagy genes such as Ubb, Ubc, and Sqstm1. This is hypothesized to be a "stress adaption" which happens during the initial phases of acute liver injury. Furthermore, there is a spatial redistribution of Cyp450 expression that then establishes the Mid-zone as the primary site of APAP metabolism during early AILI. This particular finding was identified previously by other groups in several single-cell papers. Ddit3 (Chop) expression also increases in zone 2. The authors focused mostly on the Atf4-Ddit3 axis in stress adaptation. Importantly, they probe the functionality of this axis by overexpressing either ATF4 or DDIT3 using AAV tools, and they show that these manipulations block APAP-induced injury and necrosis. This is somewhat convincing evidence that these stress response proteins are probably important during injury and regeneration.

Strengths:

Overall, I think this is a useful study, showing that the Mid-lobular zone 2 hepatocytes turn on a stress-responsive gene program that suppresses proliferation, and that this is functionally important for efficient, long-term regeneration and homeostasis. This adds to the body of literature showing the importance of zone 2 cells in hepatic regeneration, and also provides an additional mechanism that tells us how they are better at surviving chemical injuries.

Weaknesses:

The main concern is that the overexpression of ATF4 and DDIT3 is causing reduced cell death and damage by APAP. This makes it harder to understand if these genes are truly increasing survival or if they are just reducing the injury caused by APAP. It may be better to perform overexpression immediately after, or at the same time as APAP delivery. Alternatively, loss-of-function experiments using AAV-shRNAs against these targets could be useful.

eLife Assessment

This study presents an important finding by identifying OPG as a novel stromal checkpoint influencing T-cell anti-tumor responses, thereby shedding new light on the complex interplay between the tumor microenvironment and immune regulation. The data are robust and the experimental approaches are sound, providing solid support for the study's conclusions; however, there are a number of additional questions raised by the data. Of particular note are the questions raised on the mechanistic effects of TRAIL versus RANKL. In addition, it would broaden the interest in this study to include more translational human data to complement the work presented.

Reviewer #1 (Public review):

Summary:

Wang et al. present a compelling study investigating a novel immunosuppressive mechanism within the tumor microenvironment (TME) mediated by a subset of cancer-associated fibroblasts (CAFs)-specifically, inflammatory CAFs (iCAFs) that secrete osteoprotegerin (OPG). Utilizing both genetic and antibody-mediated OPG inhibition in murine breast and pancreatic cancer models, the authors demonstrate that blocking OPG enhances infiltration and effector function of cytotoxic T cells, which leads to significant tumor regression. Their data further show that OPG blockade induces a population of IFN-licensed CAFs characterized by increased expression of antigen presentation genes and immunomodulatory properties that favour T cell infiltration. The manuscript proposes that OPG functions as a "stromal immune checkpoint" and could represent a promising therapeutic target to convert "cold" tumors into "hot," immunotherapy-responsive tumours.

Strengths:

(1) Novel role for OPG+ CAF as T-cell immune suppressors:<br /> This study introduces a novel role for OPG+ iCAFs as active suppressors of T cell function and highlights stromal OPG as a critical negative regulator of antitumor immunity.

(2) Methodological Rigor:<br /> The manuscript is underpinned by a thorough and systematic experimental design, combining genetic mouse models, antibody interventions, in vitro functional assays, single-cell RNA-seq, and human RAN-seq datasets analyses.

(3) Translational Relevance:<br /> By identifying OPG as a stromal immune checkpoint, the study opens exciting opportunities for developing new immunotherapeutic strategies in stromatogenic tumors.

(4) Clear and Comprehensive Data Presentation:<br /> The use of high-dimensional single-cell technologies and logical, detailed data presentation supports the study's reproducibility and transparency.

Weaknesses:

(1) The manuscript lacks definitive data identifying the cellular origin of OPG, particularly establishing iCAFs as the exclusive functional source.

(2) There is a paucity of translational evidence directly correlating OPG+ iCAFs with T cell exclusion in human tumors.

(3) The scope is limited by the reliance on two murine models, including a subcutaneous pancreatic cancer model, which may not fully recapitulate native tumor microenvironments.

(4) Long-term outcomes and durability of response following OPG blockade, including possible effects on bone homeostasis, are not addressed.

(5) Mechanistic experiments related to the blockade of TRAIL and RANKL remain incomplete, and alternative pathways are not thoroughly explored.

Reviewer #2 (Public review):

Summary:

The work identified a protein called OPD secreted by a particular subtype of cancer-associated fibroblasts and found that it regulated T cell function in the tumor microenvironment. They showed that an antibody that targeted this protein could induce infiltration of immune cells into the tumour and could convert a cold tumor lacking tumour infiltration to a hot tumour with an immune-rich tumour microenvironment. They have supported the conclusion with the data in animal work as well as human tissue data. The authors also stated that it remains unclear whether the IFN-stimulated CAF subset after antibody treatment of OPG is due to reprogramming of existing iCAFs or arises de novo from progenitor populations. Despite their preclinical data suggesting the latter, they rightly suggested that in vivo lineage tracing is needed to further prove the origin and fate of these CAF populations. Overall, this is a well-designed and important study that would benefit from further mechanistic clarification and minor revision.

Strengths:

The strength of their data is that they utilized an immunocompetent orthotopic breast cancer model using the GFP-labelled tumor cell line EO771 in C57BL/6J mice, a well-established model for interrogating the role of stromal-immune interactions in carcinogenesis and tumor growth. They also performed scRNA-seq of the sorted stromal cells of the implanted EO771 cells as well as stromal cells from human esophageal carcinoma using tumor samples and matched adjacent non-malignant tissues from patients.

Weaknesses:

The key mechanistic aspects remain unclear, in particular the relative contributions of the TRAIL versus RANKL pathways to immunosuppression. The dual inhibition of TRAIL and RANKL by OPG is proposed, but the contribution of each axis to immune suppression was not clearly dissected. It would strengthen the paper to evaluate the effects of TRAIL versus RANKL signalling (e.g., with selective ligands or antagonists), which warrants deeper mechanistic exploration. Moreover, while CD4⁺ T cell cytotoxicity was observed, its functional role was underexplored.

embarrassed, flustered

female_pervert

for - adjacency - Trump - Inequality

hoe groot en zwaar het efefct is van groepsverschillen

dus bepaalde constraten, eerst word de contrast groep vergeleken met alle experimentele groepen en als je iets uit het conntrast haalt kan het niet terugkomen

ootstrapping is een statistische techniek die wordt gebruikt om de nauwkeurigheid van schattingen te beoordelen en betrouwbaarheidsintervallen te berekenen zonder aannames te maken over de verdeling van de data. Het is een herhalingsproces waarbij steekproeven worden genomen uit de oorspronkelijke dataset, met vervanging, om een groot aantal nieuwe steekproeven te genereren. Deze steekproeven worden vervolgens gebruikt om de variabiliteit van een statistiek te schatten.) opvallend het neemt herhaaldelijk een steekproef uit een sample met teruglegging wat betekend dat elke observatiie meerdere keren kan worden geslecteerd in een enkele steekproef het vereeist geen aanames over de verdeling van de data waardoor je het kan gebruiken als iets niet normaal verdeeld is.

Testing

I think it’s interesting how the ordinary diving equipment becomes symbolic, like “black rubber body armor” and “awkward mask,” suggesting emotional or psychological protection.

DOI: 10.34133/research.0911

Resource: (BCRJ Cat# 0395, RRID:CVCL_0168)

Curator: @evieth

SciCrunch record: RRID:CVCL_0168

What is this?

DOI: 10.34133/research.0911

Resource: (BCRJ Cat# 0331, RRID:CVCL_B260)

Curator: @scibot

SciCrunch record: RRID:CVCL_B260

What is this?

DOI: 10.34133/research.0911

Resource: (CCLV Cat# CCLV-RIE 1035, RRID:CVCL_0023)

Curator: @scibot

SciCrunch record: RRID:CVCL_0023

What is this?

DOI: 10.34133/research.0911

Resource: (ICLC Cat# HTL06001, RRID:CVCL_1511)

Curator: @scibot

SciCrunch record: RRID:CVCL_1511

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: (IMSR Cat# JAX_008462,RRID:IMSR_JAX:008462)

Curator: @evieth

SciCrunch record: RRID:IMSR_JAX:008462

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: None

Curator: @evieth

SciCrunch record: RRID:IMSR_JAX:039221

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: Abbott Diagnostics (RRID:SCR_008392)

Curator: @scibot

SciCrunch record: RRID:SCR_008392

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: Agilent Technologies (RRID:SCR_013575)

Curator: @scibot

SciCrunch record: RRID:SCR_013575

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: Cell Signaling Technology (RRID:SCR_002071)

Curator: @scibot

SciCrunch record: RRID:SCR_002071

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: JAX Mice and Services (RRID:SCR_016408)

Curator: @scibot

SciCrunch record: RRID:SCR_016408

What is this?

DOI: 10.1158/2159-8290.CD-24-1555

Resource: AmpliconArchitect (RRID:SCR_023150)

Curator: @scibot

SciCrunch record: RRID:SCR_023150

What is this?

DOI: 10.1126/sciadv.adt7825

Resource: RRID:BDSC_1495

Curator: @maulamb

SciCrunch record: RRID:BDSC_1495

What is this?

DOI: 10.1101/2025.09.29.679213

Resource: RRID:BDSC_30564

Curator: @maulamb

SciCrunch record: RRID:BDSC_30564

What is this?

DOI: 10.1101/2025.09.29.679213

Resource: RRID:BDSC_11173

Curator: @maulamb

SciCrunch record: RRID:BDSC_11173

What is this?

DOI: 10.1101/2025.09.29.679213

Resource: RRID:BDSC_17285

Curator: @maulamb

SciCrunch record: RRID:BDSC_17285

What is this?

DOI: 10.1101/2025.09.29.679213

Resource: RRID:BDSC_33644

Curator: @maulamb

SciCrunch record: RRID:BDSC_33644

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_31316

Curator: @maulamb

SciCrunch record: RRID:BDSC_31316

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_36779

Curator: @maulamb

SciCrunch record: RRID:BDSC_36779

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_30139

Curator: @maulamb

SciCrunch record: RRID:BDSC_30139

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_40937

Curator: @maulamb

SciCrunch record: RRID:BDSC_40937

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_11191

Curator: @maulamb

SciCrunch record: RRID:BDSC_11191

What is this?

DOI: 10.1101/2025.09.10.675304

Resource: RRID:BDSC_52268

Curator: @maulamb

SciCrunch record: RRID:BDSC_52268

What is this?

DOI: 10.1101/2025.08.11.669650

Resource: RRID:BDSC_36547

Curator: @maulamb

SciCrunch record: RRID:BDSC_36547

What is this?

DOI: 10.1101/2025.08.11.669650

Resource: RRID:BDSC_8151

Curator: @maulamb

SciCrunch record: RRID:BDSC_8151

What is this?

DOI: 10.1101/2025.03.28.645549

Resource: (ATCC Cat# CRL-3278, RRID:CVCL_AQ09)

Curator: @evieth

SciCrunch record: RRID:CVCL_AQ09

What is this?

DOI: 10.1101/2025.03.28.645549

Resource: (NCI-DTP Cat# MCF7, RRID:CVCL_0031)

Curator: @evieth

SciCrunch record: RRID:CVCL_0031

What is this?

DOI: 10.1101/2025.01.28.635292

Resource: RRID:BDSC_5137

Curator: @maulamb

SciCrunch record: RRID:BDSC_5137

What is this?

DOI: 10.1101/2024.09.02.610816

Resource: (RRID:CVCL_1721)

Curator: @evieth

SciCrunch record: RRID:CVCL_1721

What is this?

DOI: 10.1093/g3journal/jkaf236

Resource: Bloomington Drosophila Stock Center (RRID:SCR_006457)

Curator: @maulamb

SciCrunch record: RRID:SCR_006457

What is this?

DOI: 10.1080/01677063.2025.2561596

Resource: RRID:BDSC_80908

Curator: @maulamb

SciCrunch record: RRID:BDSC_80908

What is this?

DOI: 10.1038/s41419-025-08038-5

Resource: (ATCC Cat# CRL-10317, RRID:CVCL_0598)

Curator: @evieth

SciCrunch record: RRID:CVCL_0598

What is this?

DOI: 10.1038/s41419-025-08038-5

Resource: (ECACC Cat# 86082104, RRID:CVCL_0332)

Curator: @evieth

SciCrunch record: RRID:CVCL_0332

What is this?

DOI: 10.1038/s41419-025-08018-9

Resource: RRID:Addgene_12259

Curator: @evieth

SciCrunch record: RRID:Addgene_12259

What is this?

DOI: 10.1038/s41419-025-08018-9

Resource: (ATCC Cat# CRL-2755, RRID:CVCL_1923)

Curator: @evieth

SciCrunch record: RRID:CVCL_1923

What is this?

DOI: 10.1038/s41419-025-08018-9

Resource: (NCI-DTP Cat# BT-549, RRID:CVCL_1092)

Curator: @evieth

SciCrunch record: RRID:CVCL_1092

What is this?

DOI: 10.1038/s41419-025-08018-9

Resource: (RRID:CVCL_0553)

Curator: @evieth

SciCrunch record: RRID:CVCL_0553

What is this?

DOI: 10.1016/j.nbd.2025.107019

Resource: RRID:BDSC_458

Curator: @maulamb

SciCrunch record: RRID:BDSC_458

What is this?

DOI: 10.1007/s12672-025-03637-2

Resource: RRID:Addgene_12259

Curator: @evieth

SciCrunch record: RRID:Addgene_12259

What is this?

DOI: 10.3389/fimmu.2025.1648946

Resource: University of Freiburg Magnetic Resonance Development and Application Center Core Facility (RRID:SCR_021926)

Curator: @scibot

SciCrunch record: RRID:SCR_021926

What is this?

DOI: 10.3389/fimmu.2025.1589255

Resource: ImageJ (RRID:SCR_003070)

Curator: @scibot

SciCrunch record: RRID:SCR_003070

What is this?

DOI: 10.3389/fimmu.2025.1589255

Resource: ggplot2 (RRID:SCR_014601)

Curator: @scibot

SciCrunch record: RRID:SCR_014601

What is this?

DOI: 10.3389/fcimb.2025.1664733

Resource: RRID:Addgene_132180

Curator: @scibot

SciCrunch record: RRID:Addgene_132180

What is this?

DOI: 10.26508/lsa.202503414

Resource: (Miltenyi Biotec Cat# 130-052-301, RRID:AB_2877061)

Curator: @scibot

SciCrunch record: RRID:AB_2877061

What is this?

DOI: 10.26508/lsa.202503414

Resource: RRID:IMSR_JAX:000664

Curator: @scibot

SciCrunch record: RRID:IMSR_JAX:000664

What is this?

DOI: 10.1371/journal.pgen.1011885

Resource: University of Iowa Institute of Human Genetics Genomics Division Core Facility (RRID:SCR_023422)

Curator: @scibot

SciCrunch record: RRID:SCR_023422

What is this?

DOI: 10.1371/journal.pgen.1011581

Resource: University of Pittsburgh Center for Research Computing Core Facility (RRID:SCR_022735)

Curator: @scibot

SciCrunch record: RRID:SCR_022735

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# A-21235, RRID:AB_2535804)

Curator: @scibot

SciCrunch record: RRID:AB_2535804

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# A32727, RRID:AB_2633276)

Curator: @scibot

SciCrunch record: RRID:AB_2633276

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# A-21245, RRID:AB_2535813)

Curator: @scibot

SciCrunch record: RRID:AB_2535813

What is this?

DOI: 10.1242/bio.062213

Resource: (Roche Cat# 11093274910, RRID:AB_514497)

Curator: @scibot

SciCrunch record: RRID:AB_514497

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# A-11008, RRID:AB_143165)

Curator: @scibot

SciCrunch record: RRID:AB_143165

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# 700182, RRID:AB_2532293)

Curator: @scibot

SciCrunch record: RRID:AB_2532293

What is this?

DOI: 10.1242/bio.062213

Resource: (Roche Cat# 11814460001, RRID:AB_390913)

Curator: @scibot

SciCrunch record: RRID:AB_390913

What is this?

DOI: 10.1242/bio.062213

Resource: (Sigma-Aldrich Cat# E8897, RRID:AB_476955)

Curator: @scibot

SciCrunch record: RRID:AB_476955

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# 71-6000, RRID:AB_2533990)

Curator: @scibot

SciCrunch record: RRID:AB_2533990

What is this?

DOI: 10.1242/bio.062213

Resource: (Sigma-Aldrich Cat# C6219, RRID:AB_476857)

Curator: @scibot

SciCrunch record: RRID:AB_476857

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# 40-2300, RRID:AB_2533457)

Curator: @scibot

SciCrunch record: RRID:AB_2533457

What is this?

DOI: 10.1242/bio.062213

Resource: (Sigma-Aldrich Cat# L9393, RRID:AB_477163)

Curator: @scibot

SciCrunch record: RRID:AB_477163

What is this?

DOI: 10.1242/bio.062213

Resource: (Abcam Cat# ab290, RRID:AB_303395)

Curator: @scibot

SciCrunch record: RRID:AB_303395

What is this?

DOI: 10.1242/bio.062213

Resource: (BD Biosciences Cat# 610650, RRID:AB_397977)

Curator: @scibot

SciCrunch record: RRID:AB_397977

What is this?

DOI: 10.1242/bio.062213

Resource: (Thermo Fisher Scientific Cat# MA3-39100-A488, RRID:AB_2663169)

Curator: @scibot

SciCrunch record: RRID:AB_2663169

What is this?

DOI: 10.1242/bio.062213

Resource: (BD Biosciences Cat# 610182, RRID:AB_397581)

Curator: @scibot

SciCrunch record: RRID:AB_397581

What is this?

DOI: 10.3389/fcimb.2025.1631780

Resource: ImageJ (RRID:SCR_003070)

Curator: @scibot

SciCrunch record: RRID:SCR_003070

What is this?

DOI: 10.1242/bio.062197

Resource: DictyBase (RRID:SCR_006643)

Curator: @scibot

SciCrunch record: RRID:SCR_006643

What is this?

DOI: 10.1242/bio.062197

Resource: GraphPad Prism (RRID:SCR_002798)

Curator: @scibot

SciCrunch record: RRID:SCR_002798

What is this?

DOI: 10.1242/bio.062197

Resource: NIS-Elements (RRID:SCR_014329)

Curator: @scibot

SciCrunch record: RRID:SCR_014329

What is this?

DOI: 10.1242/bio.062197

Resource: ImageJ (RRID:SCR_003070)

Curator: @scibot

SciCrunch record: RRID:SCR_003070

What is this?

DOI: 10.1242/bio.062197

Resource: Microsoft Excel (RRID:SCR_016137)

Curator: @scibot

SciCrunch record: RRID:SCR_016137

What is this?

DOI: 10.1242/bio.061987

Resource: (Thermo Fisher Scientific Cat# 32460, RRID:AB_1185567)

Curator: @scibot

SciCrunch record: RRID:AB_1185567

What is this?

DOI: 10.1242/bio.061987

Resource: (Thermo Fisher Scientific Cat# 31430, RRID:AB_228307)

Curator: @scibot

SciCrunch record: RRID:AB_228307

What is this?

DOI: 10.1242/bio.061987

Resource: (Molecular Probes Cat# A-11031, RRID:AB_144696)

Curator: @scibot

SciCrunch record: RRID:AB_144696

What is this?

DOI: 10.1242/bio.061987

Resource: (Molecular Probes Cat# A-11011, RRID:AB_143157)

Curator: @scibot

SciCrunch record: RRID:AB_143157

What is this?

DOI: 10.1242/bio.061987

Resource: (Thermo Fisher Scientific Cat# A-11034, RRID:AB_2576217)

Curator: @scibot

SciCrunch record: RRID:AB_2576217

What is this?

DOI: 10.1242/bio.061987

Resource: (Thermo Fisher Scientific Cat# 13-8400, RRID:AB_2533039)

Curator: @scibot

SciCrunch record: RRID:AB_2533039

What is this?

DOI: 10.1242/bio.061987

Resource: (Cell Signaling Technology Cat# 2254, RRID:AB_2256024)

Curator: @scibot

SciCrunch record: RRID:AB_2256024

What is this?

DOI: 10.1242/bio.061987

Resource: (Thermo Fisher Scientific Cat# A-21245, RRID:AB_2535813)

Curator: @scibot

SciCrunch record: RRID:AB_2535813

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_3712333

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_2943578

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: None

Curator: @scibot

SciCrunch record: RRID:AB_3668963

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: (ChromoTek Cat# gtma-20, RRID:AB_2631358)

Curator: @scibot

SciCrunch record: RRID:AB_2631358

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: (CCLV Cat# CCLV-RIE 1035, RRID:CVCL_0023)

Curator: @scibot

SciCrunch record: RRID:CVCL_0023

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: (Cell Signaling Technology Cat# 4971, RRID:AB_2198425)

Curator: @scibot

SciCrunch record: RRID:AB_2198425

What is this?

DOI: 10.1210/endocr/bqaf140

Resource: (Proteintech Cat# 24050-1-AP, RRID:AB_2813890)

Curator: @scibot

SciCrunch record: RRID:AB_2813890

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Thermo Scientific TraceFinder (RRID:SCR_023045)

Curator: @scibot

SciCrunch record: RRID:SCR_023045

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: R Project for Statistical Computing (RRID:SCR_001905)

Curator: @scibot

SciCrunch record: RRID:SCR_001905

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Thermo Xcalibur (RRID:SCR_014593)

Curator: @scibot

SciCrunch record: RRID:SCR_014593

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Python Programming Language (RRID:SCR_008394)

Curator: @scibot

SciCrunch record: RRID:SCR_008394

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: cRAP protein sequences (RRID:SCR_018187)

Curator: @scibot

SciCrunch record: RRID:SCR_018187

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: RStudio (RRID:SCR_000432)

Curator: @scibot

SciCrunch record: RRID:SCR_000432

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Prokka (RRID:SCR_014732)

Curator: @scibot

SciCrunch record: RRID:SCR_014732

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: MEGAHIT (RRID:SCR_018551)

Curator: @scibot

SciCrunch record: RRID:SCR_018551

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: KEGG (RRID:SCR_012773)

Curator: @scibot

SciCrunch record: RRID:SCR_012773

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: SILVA (RRID:SCR_006423)

Curator: @scibot

SciCrunch record: RRID:SCR_006423

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: GTDB-Tk (RRID:SCR_019136)

Curator: @scibot

SciCrunch record: RRID:SCR_019136

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: UniProtKB (RRID:SCR_004426)

Curator: @scibot

SciCrunch record: RRID:SCR_004426

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: MOFA (RRID:SCR_022992)

Curator: @scibot

SciCrunch record: RRID:SCR_022992

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: None

Curator: @scibot

SciCrunch record: RRID:SCR_003364

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: DESeq2 (RRID:SCR_015687)

Curator: @scibot

SciCrunch record: RRID:SCR_015687

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: vegan (RRID:SCR_011950)

Curator: @scibot

SciCrunch record: RRID:SCR_011950

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Kraken (RRID:SCR_005484)

Curator: @scibot

SciCrunch record: RRID:SCR_005484

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: ggplot2 (RRID:SCR_014601)

Curator: @scibot

SciCrunch record: RRID:SCR_014601

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: Mantis (RRID:SCR_021001)

Curator: @scibot

SciCrunch record: RRID:SCR_021001

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: featureCounts (RRID:SCR_012919)

Curator: @scibot

SciCrunch record: RRID:SCR_012919

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: NetworkX (RRID:SCR_016864)

Curator: @scibot

SciCrunch record: RRID:SCR_016864

What is this?

DOI: 10.1186/s40168-025-02227-2

Resource: rstatix (RRID:SCR_021240)

Curator: @scibot

SciCrunch record: RRID:SCR_021240

What is this?

DOI: 10.1177/15330338251382839

Resource: GeneMANIA (RRID:SCR_005709)

Curator: @scibot

SciCrunch record: RRID:SCR_005709

What is this?

DOI: 10.1177/15330338251382839

Resource: TIMER (RRID:SCR_018737)

Curator: @scibot

SciCrunch record: RRID:SCR_018737

What is this?

DOI: 10.1162/jocn.a.82

Resource: Analysis of Functional NeuroImages (RRID:SCR_005927)

Curator: @scibot

SciCrunch record: RRID:SCR_005927

What is this?

DOI: 10.1162/jocn.a.82

Resource: ICBM 152 Nonlinear atlases version 2009 (RRID:SCR_008796)

Curator: @scibot

SciCrunch record: RRID:SCR_008796

What is this?

DOI: 10.1158/2767-9764.CRC-24-0582

Resource: (NCI-DTP Cat# HOP-62, RRID:CVCL_1285)

Curator: @scibot

SciCrunch record: RRID:CVCL_1285

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Thermo Fisher Scientific Cat# MA5-15738, RRID:AB_10977387)

Curator: @scibot

SciCrunch record: RRID:AB_10977387

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: Gene Expression Omnibus (GEO) (RRID:SCR_005012)

Curator: @scibot

SciCrunch record: RRID:SCR_005012

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Santa Cruz Biotechnology Cat# sc-5274, RRID:AB_2288090)

Curator: @scibot

SciCrunch record: RRID:AB_2288090

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab4566, RRID:AB_304523)

Curator: @scibot

SciCrunch record: RRID:AB_304523

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: GraphPad Prism (RRID:SCR_002798)

Curator: @scibot

SciCrunch record: RRID:SCR_002798

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Agilent Cat# M0750, RRID:AB_2281105)

Curator: @scibot

SciCrunch record: RRID:AB_2281105

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Santa Cruz Biotechnology Cat# sc-539, RRID:AB_632264)

Curator: @scibot

SciCrunch record: RRID:AB_632264

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (OriGene Cat# TA802077, RRID:AB_2626200)

Curator: @scibot

SciCrunch record: RRID:AB_2626200

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Proteintech Cat# 66329-1-Ig, RRID:AB_2881710)

Curator: @scibot

SciCrunch record: RRID:AB_2881710

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Cell Signaling Technology Cat# 12210, RRID:AB_2797846)

Curator: @scibot

SciCrunch record: RRID:AB_2797846

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Millipore Cat# AB5983, RRID:AB_92188)

Curator: @scibot

SciCrunch record: RRID:AB_92188

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab75710, RRID:AB_2631971)

Curator: @scibot

SciCrunch record: RRID:AB_2631971

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab55268, RRID:AB_942015)

Curator: @scibot

SciCrunch record: RRID:AB_942015

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab125022, RRID:AB_10975095)

Curator: @scibot

SciCrunch record: RRID:AB_10975095

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab181130, RRID:AB_2732891)

Curator: @scibot

SciCrunch record: RRID:AB_2732891

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab272494, RRID:AB_2916032)

Curator: @scibot

SciCrunch record: RRID:AB_2916032

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Cell Signaling Technology Cat# 3538, RRID:AB_1903989)

Curator: @scibot

SciCrunch record: RRID:AB_1903989

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Proteintech Cat# 16750-1-AP, RRID:AB_2756394)

Curator: @scibot

SciCrunch record: RRID:AB_2756394

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Cell Signaling Technology Cat# 5153, RRID:AB_10691711)

Curator: @scibot

SciCrunch record: RRID:AB_10691711

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab53715, RRID:AB_882208)

Curator: @scibot

SciCrunch record: RRID:AB_882208

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Cell Signaling Technology Cat# 7074, RRID:AB_2099233)

Curator: @scibot

SciCrunch record: RRID:AB_2099233

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: Samtools (RRID:SCR_002105)

Curator: @scibot

SciCrunch record: RRID:SCR_002105

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: clusterProfiler (RRID:SCR_016884)

Curator: @scibot

SciCrunch record: RRID:SCR_016884

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: R Project for Statistical Computing (RRID:SCR_001905)

Curator: @scibot

SciCrunch record: RRID:SCR_001905

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: ImageJ (RRID:SCR_003070)

Curator: @scibot

SciCrunch record: RRID:SCR_003070

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Cell Signaling Technology Cat# 7076, RRID:AB_330924)

Curator: @scibot

SciCrunch record: RRID:AB_330924

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab4729, RRID:AB_2118291)

Curator: @scibot

SciCrunch record: RRID:AB_2118291

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: rna-star (RRID:SCR_004463)

Curator: @scibot

SciCrunch record: RRID:SCR_004463

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: MultiQC (RRID:SCR_014982)

Curator: @scibot

SciCrunch record: RRID:SCR_014982

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Millipore Cat# 07-449, RRID:AB_310624)

Curator: @scibot

SciCrunch record: RRID:AB_310624

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: FastQC (RRID:SCR_014583)

Curator: @scibot

SciCrunch record: RRID:SCR_014583

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab8580, RRID:AB_306649)

Curator: @scibot

SciCrunch record: RRID:AB_306649

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: edgeR (RRID:SCR_012802)

Curator: @scibot

SciCrunch record: RRID:SCR_012802

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: CRISPick (RRID:SCR_025148)

Curator: @scibot

SciCrunch record: RRID:SCR_025148

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: BioRad QuantaSoft Analysis Software (RRID:SCR_025696)

Curator: @scibot

SciCrunch record: RRID:SCR_025696

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_12260

Curator: @scibot

SciCrunch record: RRID:Addgene_12260

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: Primer3Plus (RRID:SCR_003081)

Curator: @scibot

SciCrunch record: RRID:SCR_003081

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: Cas OFFinder (RRID:SCR_023390)

Curator: @scibot

SciCrunch record: RRID:SCR_023390

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_12259

Curator: @scibot

SciCrunch record: RRID:Addgene_12259

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (Abcam Cat# ab8895, RRID:AB_306847)

Curator: @scibot

SciCrunch record: RRID:AB_306847

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (ECACC Cat# 90112714, RRID:CVCL_0035)

Curator: @scibot

SciCrunch record: RRID:CVCL_0035

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_108301

Curator: @scibot

SciCrunch record: RRID:Addgene_108301

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_137776

Curator: @scibot

SciCrunch record: RRID:Addgene_137776

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: (RRID:CVCL_0553)

Curator: @scibot

SciCrunch record: RRID:CVCL_0553

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_52962

Curator: @scibot

SciCrunch record: RRID:Addgene_52962

What is this?

DOI: 10.1158/2159-8290.CD-24-1904

Resource: RRID:Addgene_74171

Curator: @scibot

SciCrunch record: RRID:Addgene_74171

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: OncoKB (RRID:SCR_014782)

Curator: @scibot

SciCrunch record: RRID:SCR_014782

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: (Roche Cat# 705-4793, RRID:AB_2833232)

Curator: @scibot

SciCrunch record: RRID:AB_2833232

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: (Leica Biosystems Cat# PA0554, RRID:AB_10554454)

Curator: @scibot

SciCrunch record: RRID:AB_10554454

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: (Abcam Cat# ab32420, RRID:AB_725574)

Curator: @scibot

SciCrunch record: RRID:AB_725574

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: (Thermo Fisher Scientific Cat# ICN56967, RRID:AB_2334775)

Curator: @scibot

SciCrunch record: RRID:AB_2334775

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: (Agilent Cat# GA623 (also GA62361-2), RRID:AB_3073940)

Curator: @scibot

SciCrunch record: RRID:AB_3073940

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: Gene Set Enrichment Analysis (RRID:SCR_003199)

Curator: @scibot

SciCrunch record: RRID:SCR_003199

What is this?

DOI: 10.1158/1078-0432.CCR-24-4120

Resource: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260)

Curator: @scibot

SciCrunch record: RRID:SCR_002260

What is this?