Dear Professor Papin,

Thank you very much for submitting your manuscript "Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses" for consideration at PLOS Computational Biology.

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Sincerely,

Kiran Raosaheb Patil, Ph.D.

Section Editor

PLOS Computational Biology

Kiran Patil

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: In this study, the authors utilize GEM to analyze sex-dependent differences between female and male with regard to metabolic alteration in toxicological responses mostly in liver, but also in kidney and brain. The authors identified several metabolic pathways (subsystems) that are dysregulated in liver between male and female. In general, the manuscript is well written; methods and results are clearly presented and sufficiently discussed. This study provides insight into how sex affects drug response in the treatment of liver diseases, which is an important step toward precision medicine. I have number of minor comments.

1. Line 149 – 150. It is unclear if the author is saying that the two metabolic pathways were upregulated in males in both liver and kidney, or either in liver or in kidney (when using the term “between the liver and kidney”).

2. Line 145. The authors reported that 11 metabolic subsystems were dysregulated in liver. However, in the following text the authors only mentioned two (acylglyceride and steroid) and the other eight metabolic subsystems in Figure 2C.

3. Line 154 – 171. Most of the content seems like discussions rather than results. I suggest the structuring of the results and discussions carefully.

4. Line 175 – 176. As this is the first sentence, it is better to indicate what cells/materials were used in addition to the words “treatment and non-treatment conditions”.

5. Line 155. I guess here it should be Figure 2C not Figure 3A.

Reviewer #2: Please see attachment

Reviewer #3: Summary

The authors Integrate gene expression data to contextualize the previously published Human1 human cell metabolic network model to characterize the impact of transcriptional changes of metabolic genes in the context of sex differences and drug treatment.

They used Tasks Inferred from Differential Expression (TIDEs) to discover that androgen, ether lipid, glucocorticoid, tryptophan, and xenobiotic metabolism have more activity in the male liver, and serotonin, melatonin, pentose, glucuronate, and vitamin A metabolism have more activity in the female liver. On drug treatment in hepatocytes the largest differences berween the sexes are in subsystems related to lipid metabolism. sex-specific transcriptomic data was used to create individual and averaged male and female liver models. The results indicate that the sexually dimorphic behavior of the liver may be caused by differences in enterohepatic recirculation. The authors suggest an investigation into sex-specific microbiome composition for further understanding. Moreover, the authors point out the male-bias in clinical testing of drugs that has unfortunately led to a disproportionate number of hepatotoxic events in women and reiterate the lack of focus on the systematic interactions of these differences.

Comments:

There are no major issues with this study as detailed below. Based on the technical and scientific soundness of the study, I recommend publication.

(1) The question the authors are trying to answer is very relevant and the need of the hour

(2) Overall, the findings reported here can help shape sex-specific research to represent the entire human population and potentially guide future drug design and toxicological testing.

(3) There are some minor typographical errors and I recommend correcting them before publication

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

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Reviewer #1: Yes

Reviewer #2: No: A GitHub repository is available, but does not allow the reproduction of the analyses because the datasets are not available. Please see the review file for more detail.

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Attachments

Attachment

Submitted filename: Review of PCOMPBIOL-D-23-00166.pdf

Dear Professor Papin,

We are pleased to inform you that your manuscript 'Metabolic modeling of sex-specific liver tissue suggests mechanism of differences in toxicological responses' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Mark Alber, Ph.D.

Section Editor

PLOS Computational Biology

Kiran Patil

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors revised the paper based on the reviewer comments and I am satisfied with the latest version of the paper.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

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If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Adil Mardinoglu