Dear Dr Hancock,

Thank you for submitting your manuscript entitled "MAPPING TRENDS IN INSECTICIDE RESISTANCE PHENOTYPES IN AFRICAN MALARIA VECTORS" for consideration as a Research Article by PLOS Biology.

Your manuscript has now been evaluated by the PLOS Biology editorial staff as well as by an academic editor with relevant expertise and I am writing to let you know that we would like to send your submission out for external peer review.

However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.

Please re-submit your manuscript by Jan 07 2020 11:59PM.

Login to Editorial Manager here: https://www.editorialmanager.com/pbiology

During resubmission, you will be invited to opt-in to posting your pre-review manuscript as a bioRxiv preprint. Visit http://journals.plos.org/plosbiology/s/preprints for full details. If you consent to posting your current manuscript as a preprint, please upload a single Preprint PDF when you re-submit.

Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. Once your manuscript has passed all checks it will be sent out for review.

***Please be aware that, due to the voluntary nature of our reviewers and academic editors, manuscripts may be subject to delays due to their limited availability during the holiday season. Please also note that the journal office will be closed entirely 21st- 29th December inclusive, and 1st January 2020. Thank you for your patience.***

Feel free to email us at plosbiology@plos.org if you have any queries relating to your submission.

Kind regards,

Lauren A Richardson, Ph.D

Senior Editor

PLOS Biology

Dear Dr Hancock,

Thank you very much for submitting your manuscript "Mapping Trends In Insecticide Resistance Phenotypes In African Malaria Vectors" for consideration as a Research Article at PLOS Biology. Your manuscript has been evaluated by the PLOS Biology editors, an Academic Editor with relevant expertise, and by several independent reviewers.

As you will read, the reviewers appreciated many aspects of your work and the importance of these maps. They also raise a number of points that will need to be addressed in a revision. Of particular note, we like the suggestion of Rev #2 to add the data of An.funestus resistance, if it is available. Rev #3 also raises a number of excellent points. We agree that these type of additional analyses would improve the manuscript, but do not consider them to be absolutely essential for a revision. We would like you to consider them and address them as best you can, providing clear explanation for those analyses you do not choose to include in the revision.

In light of the reviews (below), we will not be able to accept the current version of the manuscript, but we would welcome re-submission of a much-revised version that takes into account the reviewers' comments. 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 for further evaluation by the reviewers.

We expect to receive your revised manuscript within 2 months.

Please email us (plosbiology@plos.org) if you have any questions or concerns, or would like to request an extension. At this stage, your manuscript remains formally under active consideration at our journal; please notify us by email if you do not intend to submit a revision so that we may end consideration of the manuscript at PLOS Biology.

**IMPORTANT - SUBMITTING YOUR REVISION**

Your revisions should address the specific points made by each reviewer. Please submit the following files along with your revised manuscript:

1. A 'Response to Reviewers' file - this should detail your responses to the editorial requests, present a point-by-point response to all of the reviewers' comments, and indicate the changes made to the manuscript.

*NOTE: In your point by point response to the reviewers, please provide the full context of each review. Do not selectively quote paragraphs or sentences to reply to. The entire set of reviewer comments should be present in full and each specific point should be responded to individually, point by point.

You should also cite any additional relevant literature that has been published since the original submission and mention any additional citations in your response.

2. In addition to a clean copy of the manuscript, please also upload a 'track-changes' version of your manuscript that specifies the edits made. This should be uploaded as a "Related" file type.

*Re-submission Checklist*

When you are ready to resubmit your revised manuscript, please refer to this re-submission checklist: https://plos.io/Biology_Checklist

To submit a revised version of your manuscript, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' where you will find your submission record.

Please make sure to read the following important policies and guidelines while preparing your revision:

*Published Peer Review*

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. Please see here for more details:

https://blogs.plos.org/plos/2019/05/plos-journals-now-open-for-published-peer-review/

*PLOS Data Policy*

Please note that as a condition of publication PLOS' data policy (http://journals.plos.org/plosbiology/s/data-availability) requires that you make available all data used to draw the conclusions arrived at in your manuscript. If you have not already done so, you must include any data used in your manuscript either in appropriate repositories, within the body of the manuscript, or as supporting information (N.B. this includes any numerical values that were used to generate graphs, histograms etc.). For an example see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5

*Blot and Gel Data Policy*

We require the original, uncropped and minimally adjusted images supporting all blot and gel results reported in an article's figures or Supporting Information files. We will require these files before a manuscript can be accepted so please prepare them now, if you have not already uploaded them. Please carefully read our guidelines for how to prepare and upload this data: https://journals.plos.org/plosbiology/s/figures#loc-blot-and-gel-reporting-requirements

*Protocols deposition*

To enhance the reproducibility of your results, we recommend that if applicable 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. For instructions see: https://journals.plos.org/plosbiology/s/submission-guidelines#loc-materials-and-methods

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

Sincerely,

Lauren A Richardson, Ph.D

Senior Editor

PLOS Biology

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

REVIEWS:

Reviewer #1:

I really enjoyed reading the manuscript MAPPING TRENDS IN INSECTICIDE RESISTANCE PHENOTYPES IN AFRICAN MALARIA VECTORS from Hancock and colleagues. It is well written (although I would spell out all the acronyms, since some reader may not be familiar with this topic) and the methods scientifically sound. The algorithm development and properties are coherent with the aim of the project, i.e. maximize the predictive capacity of the model (an ensemble). I congratulate the authors for the effort and for providing detailed information about the model behavior and predictions.

The paper is in line with PLOS Biology scope and aims and I suggest acceptance after the authors revise it in accordance to my corrections/questions.

Raised points:

Abstract.

Is it possible to quantify the "alarming increase", e.g. "since 2005 we have shown a X fold increase in malaria resistance across…"

Introduction

Line 74 should be "after the introduction of these interventions".

The passage from the paragraph in lines 63-83 to the paragraph in lines 85-98 is a bit abrupt. Is it possible to add a paragraph on how this problem (mapping insecticide resistance) has been dealt before? Also how current models fails in achieving what you have achieved.

Results

If I was a general reader, I would found very difficult the interpretation of the RMSE for the comparison of the 4 models. First of all, in table S2 and S3 keep consistency with names (GAMB or BGAM). In terms of values it is not clear to me why you use different units between the main text and the supplementary. If necessary, please add a sentence in the main text.

If I compare figure 1 and 5, it seems to me that lines F,G,H,I and relative areas (figure 1) may not conclusive since uncertainty is close to 1 or very high (Figure 5). Please comment in the discussions or provide a bit more information. In addition, looking at table S7 and S8 I speculate that uncertainty increases although samples are increasing too. Is this the effect of interventions that by fragmenting the "continuous" resistance, reduces the capacity of the spatio-temporal dependence to explain part of the variation?

I found very interesting the importance of rainfall in your models, especially for East Africa which was affected by two important droughts during your study period. Please can you add a comment on this?

Methods

Variable importance. Instead of using different functions (and packages) to evaluate variable importance for each model, it would not be easier to just remove a variable at time and look at the RMSE?

----------------

Reviewer #2:

Review PBIOLOGY-D-19-03626R1

The paper describes the spatial and temporal trend of insecticide resistance phenotypes in West and East African region using a large database (Moyes CL et al, Scientific dada, 2019) available in open access. Report of insecticide resistance increase in Africa is not new and several others authors have reported this trend in Africa. What is novel in the paper is the visualisation of this increase in resistance over time and space and differences between the West and East block of countries. The paper also explores and ranks factors that predicts the prevalence of insecticide resistance. This is a clear, concise and a well written manuscript of great importance.

I have however some major comments

* The results for East Africa is not as convincing than the West Africa one, as the authors omit An.funestus resistance that has a major roles in the Southern part of the continent but is also in the past few years increasingly present in East Africa countries (Burundi, Tanzania, Uganda, Kenya). The An.funestus resistance data are also available and applying the model would provide important information that are missing in the actual paper especially as the models aimed to assist decision making in resistance management. The frequency of insecticide resistance in East Africa is not as widespread than in West Africa and resistance management in this area might be the most successful.

* The contribution of public health vs agriculture insecticides to selection of resistance is essential to device appropriate resistance management. One of the main limitation concerning the predictors is the lack of information on the insecticide/pesticide use for agriculture. The authors used different variables as a proxy, land use of crops and other land cover, fate of insecticides in the environment, etc. These variables correspond to more than half of the variables included in the model. Variables that cover the widest area modelled (ITN, Rainfall, temperature etc..) seems to be the highest contributors. I am therefore wondering if the apparent lower contribution of agriculture pesticide in An. gambiae insecticide resistance is due to the number of variables that have been included. Could the land use variables representing crops using pesticides the most, be pulled together as a single variable in the model? While I understand the difficulty to get the data on agriculture pesticide and find appropriate proxies, the authors should discuss, more in details, some of their findings and differences observed between West and East Africa. The model seems to suggest that agriculture pesticide use is a more important contributor in West than East Africa. Please comments.

* The authors have discussed the difference in insecticide resistance between An.gambiae and An.arabiensis. I have 4 points, I wanted to raise on this.

o The prediction model gives a good idea of the trends in West Africa as well as predicting factors. The resistance trend in the vectors in West Africa (gamiae/coluzzi) is more homogenous than in the other sibling species in East Africa Arabiensis/gambiae. Could it explain the wider credible interval in the prediction they found in East compare to West Africa?

o The authors include a variable on relative abundance of Arabiensis vs gambiae/coluzzi. which do not seem to contribute to the overall model in East Africa. Please would you be able to explain.

o There are reports showing a shift toward An.arabiensis that seems to be associated with IRS and ITN. Would this and lower insecticide resistance prevalence in An.arabiensis explained why ITN coverage is not as strongly predictive for resistance in East Africa compared to West Africa?

o Contribution of Rainfall variables, please could you explain why do you think there is a difference in importance between West and East Africa. Could rainfall be a proxy for increase in An.gambiae abundance and therefore insecticide resistance? Or?

* Overall, I would suggest the authors to expand on their discussions especially on the contribution factors and possible explanation of differences between West and East Africa.

Minor comments,

* Why was the variable "Proportional abundance of An. arabiensis to An.coluzzii/gambiae" considered as static? The authors indicated this variable was based on collection from1985 -2015. Would the variable not be able to predict better the resistance if it was included as a yearly or bi-annual variable?

* The authors mentioned that insecticide use for agriculture was not available therefore different crops and livestock production were used. How were these 30 crops selected? Is it based on known insecticide use?

* The authors indicate that "Our predictive maps of mean prevalence of resistance are available to visualise alongside the latest susceptibility test data on the IR mapper website (http://www.irmapper.com), and can guide decisions about resistance management at regional and local levels. In making recommendations, our results will need to be considered in combination with (i) data from resistance monitoring of field samples, including other malaria vector species such as An. funestus; (ii) data on the presence of underlying mechanisms of resistance, and (iii) analyses of the expected impacts of resistance management strategies on malaria prevalence".

Would the maps and predictors be available for each country? Otherwise I am not convinced that the overall maps and results as presented in the paper would be enough to help decision making at national level.

----------------

Reviewer #3: Tovi Lehmann, signed review

Mapping Trends in Insecticide resistance Phenotypes in Africa malaria vectors

By: Hancock et al.

Summary:

This is a well written, interesting paper that I enjoyed reading. It is based an analytic modeling to describe the change of resistance to pyrethroids in the African malaria mosquito, A. gambiae s.l.. Using ~6500 test of mosquito resistance assays performed between 2005 and 2017 and incorporating >100 explanatory variables including application of the pesticides, cross-resistance between insecticide types (including DDT), climate, hydrology, vegetation cover, mosquito species composition, etc., the model generated predictive dynamic (time stamped) maps that describe the level of resistance across large parts of West and East Sub-Saharan Africa. Consistent with other studies, the results confirmed that resistance to Pyrethroids dramaticall increased (from 15% to 98%) over that time in W Africa, but from 9 to 45% in E Africa. Resistance to DDT also increased following similar pattern but to a lesser extent, given the higher starting rates of resistance to DDT in the area. The authors also assess the factors that explain the model and thus likely to affect the evolution of resistance. This analysis highlights the complexity of the factors and difficulty in narrowing the number of key factors down. Among the many effects, coverage of ITNs was highest in W Africa although it was modestly important (and ranked 8th) in E Africa. Yet, it appears that the success of the model depends on small effects of >100 factors or nearly so. The main strength of the study is the production of regional maps that can guide decisions about the management of resistance in areas where few or no tests of resistance were done. However, the authors caution that their predictions are no replacement for such tests and mostly call attention to low confidence indicator for areas where more tests are needed.

I applaud the authors for a valuable advance in the management of insecticide resistance and their application of state-of-the-art computing to generate these impressive maps. The careful interpretation of the results is also a strength of this paper. Yet, I feel that this paper better fits a journal with more specialized readership in a narrower field of malaria epidemiology than PlosBiology. I note below that if the authors extend their analyses to address additional new questions, then their work could well fit with PlosBiology's broad readership. I hope my comments below will help the authors decide about the best course for their paper.

General Comments:

1. Given the exceptional analytic skills and unique data, I wonder if the authors would focus on some additional questions (using regions/time sections that are suitable to address them as applicable) that will "elevate the interest" in their work. For example (a) Are true "reversals of resistance" evident? How to discern true reversals? If observed, how common are they? What factors may account for them? Are they more common during early evolution phase (when mutations are presumably more costly) and how they can be exploited in management of resistance?

b) are there islands of susceptibility and resistance that are stable. If so where, how long, and what could account for them (see above).

c) is there a way to infer the "lower rate of spatial spread of resistance" (assuming arriving from nearest area) over distance and possibly certain barriers?

d) how unstable are resistance profiles at a location, so if we have several resistance tests in a region that had indicated 51-67% 2,3,4, or up to 7 years ago, how important is to do that test this year if there is no dramatic change in insecticide use and if there was. How such answers change based on availability of a complete time series 10, 50, 100, or 500 km away. So, can we refine the guidance when and where we need new tests.

2. The term "spread of resistance" is complex and may better replaced here or be explained in the outset. Intuitively, it conveys the notion of (1) spread from point A to B, which is not the case here. The authors include (2) the rise in frequency of resistance in the same region, and (3) the spread from unknown multiple sources so that no point A to B can be given. A clarification would be helpful.

3. Maps are very good to convey "big picture" of changes in resistance level over time but seem a little too perfect and convey a false notion that all is known. I cannot tell which parts of a map are close to "observed", which show gaps between observed and predicted (how big the gap), and which are "predicted" with no observed to compare with.

These are a few examples for questions that once being addressed may provide new insights that will merit publication in a broad audience journal such as PlosBiology.

Specific comments

Introduction

- why the range of data used/selected was 2005-17? Given that there is much widespread resistance in 2005, it would be interesting to start earlier, even if it would address smaller areas.

-. It is mentioned that pyrethroids have been extensively used and given the analysis by different types of pyrethroids, it will help knowing about the difference in sensitivity for each type, mechanism of resistance to each type, and historical use of these types in different areas. Some of this info can form a basis for expectations to judge the maps against.

- The introduction led me to assume that there were no previous papers on the origin and spread of mechanisms of resistance which were depicted by maps. If this is incorrect, it'd be helpful to refer to their maps and underlying basis.

Results

I believe if date-stamp is 2005, data were taken only during this year (not from a range, e.g., 2004-2006). Correct?

L 198 -214. -

- I assume 'out-of-sample' means removing an observation and using the rest of the data to predict it. Is 10-fold means that it was repeated 10 times across all observation, one at a time or 90% of the data were used? It needs to be explained.

- I believe that RMSE should be given side by side with MAE, which is more directly applicable to the data and is less susceptible to outliers.

- I think this stat is more meaningful conditioned on distance (spatial and temporal if there were multiple observations in the time interval and only 1 was removed) from nearest data points. Further, I'd report the 'adjusted' value to reflect the mean and median distance between observed and predicted that the map shows.

- I agree that validation of model prediction is vital and fit in the results, although this section is written too technically, and most readers won't be able to interpret it. I suggest keeping the section but transfer parts to the methods and in their place, provide biological relevant predictions capturing a couple of the better and worse predictions pertaining to relevant space and time points.

Dear Dr Hancock,

Thank you for submitting your revised Research Article entitled "MAPPING TRENDS IN INSECTICIDE RESISTANCE PHENOTYPES IN AFRICAN MALARIA VECTORS" for publication in PLOS Biology. I have now obtained advice from two of the original reviewers and have discussed their comments with the Academic Editor.

Based on the reviews, we will probably accept this manuscript for publication, assuming that you will modify the manuscript to address the remaining points raised by reviewer #3. Please also make sure to address my Data Policy-related requests noted at the end of this email.

We expect to receive your revised manuscript within two weeks. Your revisions should address the specific points made by each reviewer. In addition to the remaining revisions and before we will be able to formally accept your manuscript and consider it "in press", we also need to ensure that your article conforms to our guidelines. A member of our team will be in touch shortly with a set of requests. As we can't proceed until these requirements are met, your swift response will help prevent delays to publication.

*Copyediting*

Upon acceptance of your article, your final files will be copyedited and typeset into the final PDF. While you will have an opportunity to review these files as proofs, PLOS will only permit corrections to spelling or significant scientific errors. Therefore, please take this final revision time to assess and make any remaining major changes to your manuscript.

NOTE: If Supporting Information files are included with your article, note that these are not copyedited and will be published as they are submitted. Please ensure that these files are legible and of high quality (at least 300 dpi) in an easily accessible file format. For this reason, please be aware that any references listed in an SI file will not be indexed. For more information, see our Supporting Information guidelines:

https://journals.plos.org/plosbiology/s/supporting-information

*Published Peer Review History*

Please note that 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. Please see here for more details:

https://blogs.plos.org/plos/2019/05/plos-journals-now-open-for-published-peer-review/

*Early Version*

Please note that an uncorrected proof of your manuscript will be published online ahead of the final version, unless you opted out when submitting your manuscript. If, for any reason, you do not want an earlier version of your manuscript published online, uncheck the box. 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 as soon as possible if you or your institution is planning to press release the article.

*Protocols deposition*

To enhance the reproducibility of your results, we recommend that if applicable 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. For instructions see: https://journals.plos.org/plosbiology/s/submission-guidelines#loc-materials-and-methods

*Submitting Your Revision*

To submit your revision, please go to https://www.editorialmanager.com/pbiology/ and log in as an Author. Click the link labelled 'Submissions Needing Revision' to find your submission record. Your revised submission must include a cover letter, a Response to Reviewers file that provides a detailed response to the reviewers' comments (if applicable), and a track-changes file indicating any changes that you have made to the manuscript.

Please do not hesitate to contact me should you have any questions.

Sincerely,

Roli Roberts

Roland G Roberts, PhD,

Senior Editor

PLOS Biology

------------------------------------------------------------------------

DATA POLICY:

You may be aware of the PLOS Data Policy, which requires that all data be made available without restriction: http://journals.plos.org/plosbiology/s/data-availability. For more information, please also see this editorial: http://dx.doi.org/10.1371/journal.pbio.1001797

Many thanks for depositing your data in Figshare; this is much appreciated. However, my understanding is that this largely comprises the "raw" geographical raster data; we also ask that all the numerical values summarized graphically in the figures and results of your paper be made available in one of the following forms:

1) Supplementary files (e.g., excel). Please ensure that all data files are uploaded as 'Supporting Information' and are invariably referred to (in the manuscript, figure legends, and the Description field when uploading your files) using the following format verbatim: S1 Data, S2 Data, etc. Multiple panels of a single or even several figures can be included as multiple sheets in one excel file that is saved using exactly the following convention: S1_Data.xlsx (using an underscore).

2) Deposition in a publicly available repository. Please also provide the accession code or a reviewer link so that we may view your data before publication.

Regardless of the method selected, please ensure that you provide the individual numerical values that underlie the summary data displayed in the following figure panels as they are essential for readers to assess your analysis and to reproduce it: Figs 1A, 3, 5, 7, 8, 9, S4, S5, S6, S8. NOTE: the numerical data provided should include all replicates AND the way in which the plotted mean and errors were derived (it should not present only the mean/average values).

Please also ensure that figure legends in your manuscript include information on where the underlying data can be found (i.e. the Figshare deposition and the bioRxiv DOI), and ensure your supplemental data file/s has a legend.

Please ensure that your Data Statement in the submission system accurately describes where your data can be found.

------------------------------------------------------------------------

REVIEWERS' COMMENTS:

Reviewer #2:

The authors have addressed all my comments and answered my questions adequately. I am glad they included An.funestus results even if the number of data point were much lower than An.gambiae.

Reviewer #3:

[Identifies himself as Tovi Lehmann]

Overall the revisions are thorough and satisfactorily address all the key points. The sophisticated methodology is explained in less-technical terms and the new graphs help provide a more complete picture. I enjoyed reading the paper and feel it will resonate with much interest. So my recommendation is "Accept".

I understand if the authors prefer to expand on that elsewhere, but I would like to hear their comments (2-3 sentences) on the relationships between insecticide resistance and corresponding malaria decline, or lack of decline over that 13-15 years time frame. Their analysis may provide a very valuable if not a decisive answer to this important yet incompletely addressed question.

Minor points (up to authors to decide if they would like to address):

- L270-2. 'Attenuations and declines in resistance may reflect fitness costs of resistance, or they may also arise due to shifts in the composition of the sibling species that make up the An. gambiae complex (see the Discussion).'

I'd consider adding a the contribution of migration from areas with low resistance.

L 470 'in populations of Gambiae complex mosquito species' , consider revising this fragment. At least, change to ..An. gambiae complex...

Dear Dr Hancock,

On behalf of my colleagues and the Academic Editor, Andrew Fraser Read, I am pleased to inform you that we will be delighted to publish your Research Article in PLOS Biology.

The files will now enter our production system. You will receive a copyedited version of the manuscript, along with your figures for a final review. You will be given two business days to review and approve the copyedit. Then, within a week, you will receive a PDF proof of your typeset article. You will have two days to review the PDF and make any final corrections. If there is a chance that you'll be unavailable during the copy editing/proof review period, please provide us with contact details of one of the other authors whom you nominate to handle these stages on your behalf. This will ensure that any requested corrections reach the production department in time for publication.

Early Version

The version of your manuscript submitted at the copyedit stage will be posted online ahead of the final proof version, unless you have already opted out of the process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

PRESS

We frequently collaborate with press offices. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximise its impact. If the press office is planning to promote your findings, we would be grateful if they could coordinate with biologypress@plos.org. If you have not yet opted out of the early version process, we ask that you notify us immediately of any press plans so that we may do so on your behalf.

We also ask that you take this opportunity to read our Embargo Policy regarding the discussion, promotion and media coverage of work that is yet to be published by PLOS. As your manuscript is not yet published, it is bound by the conditions of our Embargo Policy. Please be aware that this policy is in place both to ensure that any press coverage of your article is fully substantiated and to provide a direct link between such coverage and the published work. For full details of our Embargo Policy, please visit http://www.plos.org/about/media-inquiries/embargo-policy/.

Thank you again for submitting your manuscript to PLOS Biology and for your support of Open Access publishing. Please do not hesitate to contact me if I can provide any assistance during the production process.

Kind regards,

Alice Musson

Publishing Editor,

PLOS Biology

on behalf of

Roland Roberts,

Senior Editor

PLOS Biology