Limits to detecting epistasis in the fitness landscape of HIV

Avik Biswas; Allan Haldane; Ronald M. Levy

doi:10.1371/journal.pone.0262314

Peer Review History

Original SubmissionOctober 15, 2021
15 Oct 2021 Author Response Transfer Alert This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present. Attachments Attachment Submitted filename: PlosOne_response.pdf https://doi.org/10.1371/journal.pone.0262314.r001
29 Nov 2021 Decision Letter - Emilio Gallicchio, Editor PONE-D-21-33103Limits to detecting epistasis in the fitness landscape of HIVPLOS ONE Dear Dr. Levy, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit a letter and a revised manuscript that addresses the minor points raised by the third reviewer. Disregard the comment concerning the quality of the figures. The low resolution of the figures in the prepared pdf is an artifact of the editorial process. Please submit your revised manuscript by Jan 13 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. 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Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtx [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data 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 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—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The work of Biswas et al. focuses on the use of data-driven models of protein sequence composition to characterize the fitness landscape of proteins, particularly HIV proteins that are commonly targeted by antiretroviral drugs. This work deals with a common and relevant problem in the field of amino acid coevolution where both sequence data (or its diversity) is scarce, and where experimental measures of fitness are limited by experimental constraints. This extensive study has two important results: 1) higher order marginals can be recovered with a pairwise model and that such higher order marginals indeed play a role in the fitness landscape of viral proteins. 2) It sheds light on why existent experimental data trying to capture epistatic effects of mutations is hard to model due to the limited dynamic range of these experiments. Being this a revision of an initial submission, I was able to review previous reviewers comments and the accompanying responses and changes. My assessment is that the responses to the reviewer comments were appropriate and the changes did in fact improve the clarify of the presentation. My general assessment from the previous reviewers was that they did not have enough background in the recent developments in the field of amino acid coevolution and were focused on challenging the model development itself which has been already established and refined in the literature. This revision is technically sound but also does a good job presenting the biological implications of their results. In conclusion, I think this study is relevant for the field and explains several open questions concerning the application of sequence Potts models to viral proteins. I find this study relevant and of use, especially in these times where understanding the fitness landscapes of proteins related to infectious diseases in a matter of pressing public health. Given the extensive changes toward this revision, I only have a few questions and comments that if responded could make this manuscript more clear. General 1. The finding that the Capsid shows a higher correlation with he Potts model is interesting. A similar correlation has been observed for Capsids on other types of viruses (AAV) providing further evidence of the relevance of Potts models in these types of studies. I suggest citing this additional study too (https://doi.org/10.1016/j.bpj.2020.12.018). 2. Data Processing. It is stated that positions with more than 1% gaps of gaps were removed. This seems to me like a very stringent cutoff, can the authors provide an explanation of why more than 1% is too much? 3. Data processing. The statement “Sequences with insertions and deletions are removed” is not clear to me. Do you mean the positions with insertions and deletions? Or are you removing any complete sequence that has an insertion or deletion? Somehow this does not makes sense to me. 4. Alphabet reduction. I wonder if Equation 5 could be improved by including an index instead of the explicit realizations like Q=20, my understanding is that after each iteractive step, Q will be reduced with respect to the previous step right? If this is true then it should be noted that this is not only valid for a change from 21 to 20. If I misinterpretted it, then it is possible that the equation needs some further clarification. 5.Alphabet reduction. The authors compared the model with alphabet reduction with the model using full parameters. If the model with the full parameters was inferred, then what was the motivation to reduce the alphabet? 6. In the section statistical robustness of HIV Potts models, the concept of Signal-to-noise ratio is introduced and scores for the different protein systems are presented. Although it is mentioned that SNR depends on several factors, it would be good to have a more concrete definition or point out to previous work where it is defined. 7. The quality of some images is quite low, I assume this is due to the system that converts the manuscript for review. Please make sure to have high quality images. Figure 3 axes could have larger fonts for readability. Minor 1. The use of the term favorability/ disfavorability is a bit awkward, I would consider another term. 2. Conventions, should “Fig 1” be spelled “Fig. 1” ? 3. Page 5, line 149. Change “.. higher entropies in Supplementary File 1 Fig 2 A” to “.. higher entropies (Supplementary File 1 Fig 2 A).” 4. Page 5, line 157. Change “This is suggestive that strong couplings ..” to “This is suggestive of strong couplings” 5. Page 11, line 364. correct “changes in CA perhaps has a ..” to “changes in CA perhaps have a ..” 6. NRTIs is only defined in a figure caption, I suggest to define it also in the main text. 7. Data processing. The concept of “deletes” is used instead of “deletion”, I would simply use deletions. 8. Page 13, line 444. Add a period after “filtered out.” 9. Page 13, correct “drug resistance mutations is not yet” with “drug resistance mutations are not yet” 10. Mutation information section. Replace “including list of ..” with “ including a list of ..” 11. Subsection title. Use lower case across titles, e.g. Change “Statistical Robustness of HIV” with “Statistical robustness of HIV ..” 12. Change title in the SI to be compatible with the manuscript 13. What is the need of having two distinct Supplementary files? It seems to me that the two files can be combined into a single document ****** 6. 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 #1: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment 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. Registration is free. 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 PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0262314.r002
Revision 1
18 Dec 2021 Author Response In response to the specific editor comments, we have provided a rebuttal letter that responds to each point raised by the academic editor and reviewer(s), a marked-up copy of the manuscript highlighting changes made to the original version, as well as an unmarked version of the revised paper without tracked changes. In response to the specific comments raised by the reviewer, we provide a detailed response (in the rebuttal letter) as below: The work of Biswas et al. focuses on the use of data-driven models of protein sequence composition to characterize the fitness landscape of proteins, particularly HIV proteins that are commonly targeted by antiretroviral drugs. This work deals with a common and relevant problem in the field of amino acid coevolution where both sequence data (or its diversity) is scarce, and where experimental measures of fitness are limited by experimental constraints. This extensive study has two important results: 1) higher order marginals can be recovered with a pairwise model and that such higher order marginals indeed play a role in the fitness landscape of viral proteins. 2)It sheds light on why existent experimental data trying to capture epistatic effects of mutations is hard to model due to the limited dynamic range of these experiments. Being this a revision of an initial submission, I was able to review previous reviewers comments and the accompanying responses and changes. My assessment is that the responses to the reviewer comments were appropriate and the changes did in fact improve the clarify of the presentation. My general assessment from the previous reviewers was that they did not have enough background in the recent developments in the field of amino acid coevolution and were focused on challenging the model development itself which has been already established and refined in the literature. This revision is technically sound but also does a good job presenting the biological implications of their results. In conclusion, I think this study is relevant for the field and explains several open questions concerning the application of sequence Potts models to viral proteins. I find this study relevant and of use, especially in these times where understanding the fitness landscapes of proteins related to infectious diseases in a matter of pressing public health. Given the extensive changes toward this revision, I only have a few questions and comments that if responded could make this manuscript more clear. We thank the reviewer for the thoughtful commentary and for highlighting the main points of the manuscript. The reviewer finds the study "relevant and of use". Below we provide a point-by-point response to the questions and comments raised by the reviewer. We have also updated the manuscript with changes made in response to the current reviewer comments highlighted in "cyan", while changes made to the previous reviewers' comments are highlighted in "yellow". General: 1. The finding that the Capsid shows a higher correlation with the Potts model is interesting. A similar correlation has been observed for Capsids on other types of viruses (AAV) providing further evidence of the relevance of Potts models in these types of studies. I suggest citing this additional study too (https://doi.org/10.1016/j.bpj.2020.12.018). We thank the reviewer for the suggestion and have added the citation in the updated manuscript. 2. Data Processing. It is stated that positions with more than 1% gaps were removed. This seems to me like a very stringent cutoff, can the authors provide an explanation of why more than1% is too much? We had not used the correct wording, "gap"; whiIe referring to the "dot" character in HIV protein sequence alignments available from the Stanford HIV drug resistance database, which represents an unsequenced position in the sequence. Such positions (columns in the multiple sequence alignment) with more than 1% "dots" or missing amino characters were removed from the MSA, so that the subsequent Potts model built on the MSA would not have spurious correlations between missing amino acids/unsequenced positions and amino acid residues at other positions. Similarly remaining sequences (rows in the MSA) with "dots" (a small fraction of the MSA) after the first filtration step, were then removed to preserve the quality of sequences. We have made this clear by revising the previous statement in the Materials and Methods section: " MSA columns with more than 1% ``dots" ('.') which represent unsequenced positions in the sequences are removed to avoid spurious correlations in the subsequent Potts model built on the MSA. Remaining sequences with any "dots" or unsequenced positions are then removed." 3. Data processing. The statement “Sequences with insertions and deletions are removed” is not clear to me. Do you mean the positions with insertions and deletions? Or are you removing any complete sequence that has an insertion or deletion? Somehow this does not makes sense to me. Complete sequences with insertions or deletions are removed. There are only few such sequences and removing them doesn't affect the multiple sequence alignment (MSA) statistics much; for example, less than 1% (~0.3%) of the sequences in the Reverse Transcriptase MSA contain insertions or deletions. On the other hand, keeping these sequences in the MSA would have complicated the subsequent model building, without improving the statistics. We have now made this clear in the revised text: " Complete sequences with any insertions ('#') or deletions ('~') are removed. Such sequences form a small fraction (<1%) of the MSA and removing them doesn't significantly affect the MSA statistics. " 4. Alphabet reduction. I wonder if Equation 5 could be improved by including an index instead of the explicit realizations like Q=20, my understanding is that after each iterative step, Q will be reduced with respect to the previous step right? If this is true then it should be noted that this is not only valid for a change from 21 to 20. If I misinterpreted it, then it is possible that the equation needs some further clarification. The reviewer is right. In each iterative step, the alphabet is reduced by 1 from a Q-letter alphabet in the previous step to a Q-1 letter alphabet. To make this clear, we have modified Equation 5 with an index instead of explicit realizations as below: 〖MI〗_RMSD= √(1/N ∑_ij▒(〖MI〗_Q^ij-〖MI〗_(Q-1)^ij )^2 ) 5.Alphabet reduction. The authors compared the model with alphabet reduction with the model using full parameters. If the model with the full parameters was inferred, then what was the motivation to reduce the alphabet? We apologize for the confusion. We only compared the Mutual Information (MI) of the MSA encoded in the full 21-letter (20 amino acids + 1 gap character) alphabet to the MI of the MSA in a reduced alphabet. The Potts model is only inferred based on the MSA in the reduced alphabet for computational efficiency and not inferred based on the MSA encoded in the full 21-letter alphabet. In the most recent work in our group, we are using the full alphabet. The project described in this manuscript was carried out using a reduced alphabet. We do not believe the alphabet reduction affects any of the results presented in this manuscript. 6. In the section statistical robustness of HIV Potts models, the concept of Signal-to-noise ratio is introduced and scores for the different protein systems are presented. Although it is mentioned that SNR depends on several factors, it would be good to have a more concrete definition or point out to previous work where it is defined. We have now included a reference to previous work from the group which gives a more elaborate definition of the SNR and the several factors it depends on: " The SNR for Potts models fit to protein sequences is discussed in more detail in [54]. " Minor: 1. The use of the term favorability/ disfavorability is a bit awkward, I would consider another term. We have used the terms "favorability/disfavorability" for a mutation in its specific sequence background, in keeping with previous published work (Biswas et al., eLife, 2019). The Potts model describes the prevalence landscapes of the protein sequences, and the model �Es best describe the favorability/disfavorability of mutations in a given sequence background. Alternatively, using terms like stabilizing/destabilizing (Flynn et al., MBE, 2017) can lead to further confusion as they can be interpreted to be pertaining specifically to protein stabilities. 2. Conventions, should “Fig 1” be spelled “Fig. 1” ? We have now renamed all figures in the manuscript according to the convention, for example Fig 1 as Fig. 1. 3. Page 5, line 149. Change “.. higher entropies in Supplementary File 1 Fig 2 A” to “.. higher entropies (Supplementary File 1 Fig 2 A).” We have modified the sentence in the Main text. 4. Page 5, line 157. Change “This is suggestive that strong couplings ..” to “This is suggestive of strong couplings” We thank the reviewer for pointing out the typo and have corrected it in the revised text. 5. Page 11, line 364. correct “changes in CA perhaps has a ..” to “changes in CA perhaps have a ..” We have corrected the typo in the revised text. 6. NRTIs is only defined in a figure caption, I suggest to define it also in the main text. We thank the reviewer for pointing this out and have now defined all the major drug-classes used in antiretroviral therapy including NRTIs in the Main text lines 432-436. 7. Data processing. The concept of “deletes” is used instead of “deletion”, I would simply use deletions. We have changed the word "deletes" to "deletions". 8. Page 13, line 444. Add a period after “filtered out.” Added a period. 9. Page 13, correct “drug resistance mutations is not yet” with “drug resistance mutations are not yet” Corrected. 10. Mutation information section. Replace “including list of ..” with “ including a list of ..” We have modified the main text replacing "including list of .." with "including a list of .." as pointed out by the reviewer. 11. Subsection title. Use lower case across titles, e.g. Change “Statistical Robustness of HIV” with “Statistical robustness of HIV ..” We have now modified the font for the subsection titles accordingly. 12. Change title in the SI to be compatible with the manuscript. We have now changed the title of the SI to be compatible with the manuscript. 13. What is the need of having two distinct Supplementary files? It seems to me that the two files can be combined into a single document. The supplementary files are kept separate for ease of readability. Supplementary file 1 contains the details of many methods, supplementary data, and figures. Supplementary file 2 on the other hand contains only supplementary tables and figures pertaining to double mutant cycles showing that most strongly coupled pairs of mutations predicted by the Potts model contain drug-resistance associated mutations studied in the literature. Note that there was a slight error in Figure S2A in Supplementary File 2, in marking the standard deviations, which we have now corrected and modified in the revised version. This does not affect any of the results. Attachments Attachment Submitted filename: PLOS_One_Response_to_Reviews.pdf https://doi.org/10.1371/journal.pone.0262314.r003
21 Dec 2021 Decision Letter - Emilio Gallicchio, Editor Limits to detecting epistasis in the fitness landscape of HIV PONE-D-21-33103R1 Dear Dr. Levy, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Emilio Gallicchio, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0262314.r004
Formally Accepted
6 Jan 2022 Acceptance Letter - Emilio Gallicchio, Editor PONE-D-21-33103R1 Limits to detecting epistasis in the fitness landscape of HIV Dear Dr. Levy: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr Emilio Gallicchio Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0262314.r005

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