Dear Dr Pienaar,

Thank you very much for submitting your manuscript "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma" for consideration at PLOS Computational Biology.

As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

Overall, the reviewers indicate a need for clarification of the modeling approach, the justifications for this approach, and the results. In particular, although the full model is explained in a separate preprint and the parameter ranges are tabled in the supplement, the reviews indicate that it would benefit this manuscript to include a brief description of the parameterization process and of the parameter distributions/constraints in the main text. Further, it should be made very clear early in the manuscript that this model is hypothesis generating, and the results should be presented more explicitly in that context.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Nic Vega, Ph.D.

Academic Editor

PLOS Computational Biology

Amber Smith

Section Editor

PLOS Computational Biology

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Overall, the reviewers indicate a need for clarification of the modeling approach, the justifications for this approach, and the results. In particular, although the full model is explained in a separate preprint and the parameter ranges are tabled in the supplement, the reviews indicate that it would benefit this manuscript to include a brief description of the parameterization process and of the parameter distributions/constraints in the main text. Further, it should be made very clear early in the manuscript that this model is hypothesis generating, and the results should be presented more explicitly in that context.

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The manuscript 'Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma' by Petrucciani et al. aims at using two different topologies of an agent based model of tuberculosis granuloma. One topology corresponds to a 3D in-vitro model where cells can move freely in three directions and that is initialized with a core of macrophages and a shell of T cells, whereas the other corresponds to a 2D layer in-vitro model. The simulations contain macrophages, CD4 and CD8 T cells and bacteria.

Cells can secrete cytokines and move along chemokine gradients. Direct and cytokine mediated cell-cell contacts can change the activation status of cells.

The authors find different types of behavior in 3D and 2D simulations and discuss possible reasons.

The authors refer to the mechanisms described in their model by describing them as 'established' rules that have been previously published. 'This hybrid model was

parameterized in Petrucciani et al. with experimental data for bacterial fold change, cell count, and cell viability at day 6 from both the spheroid and the traditional cultures.' Since the cited publication has not been peer reviewed, it is unclear in what sense it represents an 'established' model.

Even though the manuscript does not describe the parameter variation process explicitly, Table 1 and its caption and some discussions in the manuscript suggest that parameters ranges are varied and values are drawn from certain distributions, with the structure of the latter remaining unclear.

In fact, many mechanisms and parameters remain unclear. For instance, what determines chemokine secretion? How are chemotactic gradients established? How do they depend on cellular states?

The aim of the manuscript is very laudable. Computational models offer the opportunity to analyze which mechanisms are responsible for certain features in experimental data. However, care must be taken to constrain model parameter values as tightly as possible based on experimental data. Here, the constraint is just one time point with cell and bacteria counts. For the amount of parameters that are varied, this is clearly insufficient, rendering the detailed discussion of the reasons behind the observed differential behavior of the model topologies rather moot, in my view.

Reviewer #2: This paper presents and explores the dynamics of an agent-based in silico TB infection model. The paper was well-organised and clearly written. Experimental data was incorporated to parameterise the model and used to compare against model behaviour. Results were clearly presented using appropriate statistics and the discussions of results were well-reasoned. The results and conclusion reached by the paper could have significant impact on furthering our understand of TB.

The references section needs careful proof reading and editing as it contains numerous errors: incomplete references (e.g. (5), (24)) and formatting errors (e.g. (10); (13); (22,23) - journal name inconsistent; (12) - full journal name).

Figure 1 p.9 - The caption of this figure needs more detail. In (B) the desciption doesn't describe the figure (e.g. CD3/PBMC are not mentioned in the text). Also, there's a mismatch between "B" and "b" (inconsistent use of upper/lower case).

There were a number of minor typographic errors which did not affect understanding but need correction:

* p.6 "An additional 10.6 people fell ill" - 10.6 people?

* throughout, remove contractions e.g. p.6 "hasn't"; p.25 "don't", p.41 "don't".

* throughout, references needs to be before full stops. e.g. p.6 "decades.(1)" -> "decades (1)."; The same comment applies to Figure and Appendix references.

* throughout, inconsistent use of bold font in Figure/Section references e.g. p.10 "Figure 1a" ("Figure 1" is in bold, "a" is not).

Reviewer #3: uploaded as attachment

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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: No: code access is not described in the manuscript.

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: Yes: Jamie Twycross

Reviewer #3: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Attachments

Attachment

Submitted filename: Elsjefinal.docx

Dear Dr Pienaar,

Thank you very much for submitting your manuscript "Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

The reviewers indicate that all substantial concerns have been addressed, but that there are a few minor points of clarity that should be addressed prior to publication. These points are entirely about presentation of the data and results and should be trivial to address.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email.

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Nic Vega, Ph.D.

Academic Editor

PLOS Computational Biology

Amber Smith

Section Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

The reviewers indicate that all substantial concerns have been addressed, but that there are a few minor points of clarity that should be addressed prior to publication. These points are entirely about presentation of the data and results and should be trivial to address.

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #3: Excellent job addressing concerns. nice job!

Reviewer #4: This revised manuscript by Petrucciani et al. report a series of studies using their recently-described in vitro 3D spheroid granuloma model in order to better understand how specific permutations affect bacterial control. Tuberculous granulomas are complex structures with a network of interactions between multiple immune cell types and they are a key determinant of TB control or progression. Naturally formed granulomas from human or NHP are difficult to isolate and manipulate experimentally. In vitro models offer a tractable platform by which to test specific hypotheses. Here the authors describe a series of elegant simulations using their computational model recently described in PMID 38517920 to test hypotheses about the role of CD4+, CD8+, and macrophages in controlling Mtb within in vitro granulomas. The studies are well conceived and executed and the revised manuscript is very well written. Their in silico approach is hypothesis-generating and will guide the development of more complex in vitro models, inform in vitro and in vivo studies, and advance our understanding of the immune responses needed to protect from Mtb.

Reviewer #5: I agree with other reviewers in that this manuscript can be a nice contribution to the field. Although I agree with Reviewer 1 in that a very large list of parameters is being `calibrated' based on relatively few data points, the hypotheses and dynamics generated in this study (in silico) have the potential to be tested in the future in vitro/ex vivo/in vivo experiments. In the revised version of the manuscript, the main model hypotheses and used parameter calibration methods have been better explained.

Overall, I believe the authors have successfully addressed all comments from reviewers.

A few relatively minor points:

- I would recommend the authors to refer to Figure 2 in (15) where a nice overall description of the model is given.

- I believe that Table 1 is currently very much a reproduction of Table 1 in (15). I imagine there is no issue since the copyright of (15) is with the authors, and I can see the benefit of including this table in this manuscript. However, I would recommend making this clear and citing such table. Moreover, a list of parameters with values without a clear description of what each parameter represents is not necessarily useful, and makes the interpretation of results (corresponding to specific parameter values) difficult for the reader. Can the authors refer to a clear comprehensive glossary of parameter definitions from somewhere? Either from the Supplementary, the Github repository or Ref (15).

- Please make sure that resolution of all images is good enough.

- I would strongly recommend that key data is provided numerically, rather than just as figures (e.g. boxplots), for reproducibility purposes. Similarly, key summary statistics of calibrated parameters would facilitate reproducibility.

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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 #3: Yes

Reviewer #4: Yes

Reviewer #5: No: I couldn't see numerical data provided (just figures). I might have missed it though.

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PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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 #3: No

Reviewer #4: No

Reviewer #5: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

References:

Review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Dear Dr Pienaar,

We are pleased to inform you that your manuscript 'Agent-based model predicts that layered structure and 3D movement work synergistically to reduce bacterial load in 3D in vitro models of tuberculosis granuloma' 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,

Nic Vega, Ph.D.

Academic Editor

PLOS Computational Biology

Amber Smith

Section Editor

PLOS Computational Biology

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