Heuristic algorithms in evolutionary computation and modular organization of biological macromolecules: Applications to in vitro evolution

Alexander V. Spirov; Ekaterina M. Myasnikova

doi:10.1371/journal.pone.0260497

Peer Review History

Original SubmissionJuly 1, 2021
11 Aug 2021 Decision Letter - Josh Bongard, Editor PONE-D-21-21266 Heuristic algorithms in Evolutionary Computations and modular organization of biological macromolecules: applications to in vitro evolution PLOS ONE Dear Dr. Spirov, 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 ensure that your decision is justified on PLOS ONE’s publication criteria and not, for example, on novelty or perceived impact. For Lab, Study and Registered Report Protocols: These article types are not expected to include results but may include pilot data. Please submit your revised manuscript by Sep 25 2021 11:59PM. 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Thank you for stating the following in the Acknowledgments Section of your manuscript: [This work is supported by the Russian Foundation for Basic Research (grant no. 20-04-01015) and Federal Agency for Scientific Organizations of the Russian Federation (grant no. 01201351572).] We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: [The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.] Please include your amended statements within your cover letter; we will change the online submission form on your behalf. 4. Please amend either the abstract on the online submission form (via Edit Submission) or the abstract in the manuscript so that they are identical. [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: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No ****** 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: No ****** 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: It is difficult to determine if the work is technically sound as the authors need to explain more clearly and specically what their motivations and goals were for this research, or what questions they were looking to answer. How their methods were implemented in silico was not explained clearly, and they do not summarize what specic conclusions they have drawn from their results. For example the authors reference the SELEX method, an existing in vitro method for evolution DNA aptamers. What are they specically hoping to contribute to methods such as SELEX? In the methods section they summarize various evolutionary algorithms, but they do not explain how the authors themselves explicitly applied them in their experiments. It is also not clear from the methods section how these various algorithms which they discuss related to their research questions or goals. The authors should dene clearly in their introduction what questions they are seeking to answer with this research, what their novel contributions were, and what their utility is. The results section is very verbose and contains a signiant discussion of related work, so it is difficult to determine what questions the various experiments or case studies were seeking to answer and whether they did so successfully. The authors do not clearly dene what success means in their various experiments, and they need to explain more clearly what the exact tness function was, how it was evaluated, and how it was implemented in silico. It is therefore difficult to identify what conclusions can be drawn from the paper. It was only evident after reading the entire results section that the point of the in silico experiments was to identify the optimal algorithm features and hyperparameters for in vitro implementation through in silico simulation. This should be made clear in the introduction. The discussion also contains a large discussion of related work rather than a discussion of their experimental results, and so after reading it, it is still unclear what conclusions the authors have drawn from the research, or whether their conclusions are novel, and what their utility is. The authors need a separate section where they summarize their conclusions, to discuss how their results lead to those conclusions, and connect their conclusions back to the goals or questions which they were hoping to answer with this research. The experiments conducted in the paper were all in silico simulations. These simulations were composed of an analysis of their proposed evolutionary algorithm from different perspectives. Therefore, the expected statistical analysis would involve typical metrics often reported when analysing the performance of evolutionary algorithms. When analysing the performance of evolutionary algorithms one generally needs to report: -Some variation of average success rate, that is, the fraction of algorithm runs where a solution of satisfactory quality was obtained. -The mean best tness, which is the optimal tness obtained from each run averaged over the number of runs. -The effectiveness, or the average solution quality obtainable within a given computational limit. -Or the efficiency, which is the average amount of time needed to achieve a solution of satisfactory quality. Given that computational time depends on the available hardware, efficiency is often reported as the average number of evaluations to a solution. These are also usually accompanied by progress curves for the various metrics. The authors reported success rate, effectiveness and efficiency in various gures throughout the results section. These reported metrics are sufficient for the nature of their in silico experiments, however, it is not always made clear how success was dened, that is, how the authors dened a solution to be of acceptable quality. There are many grammatical problems with the text, potentially because the author's rst language is not English. So much so that it makes it difficult to understand what the authors are trying to communicate in many places. Further, some concepts were not sufficiently claried. The following concepts need to be explained more clearly: -Directed evolution / articial evolution of biological macromolecules. -How evolution of biological macromolecules is directed in vitro. -In the case studies, how were the molecules which were being evolved, represented and evaluated in silico. -Implementation details of the selection, mutation and crossover / recombination methods. Regarding the layout of the paper, the research questions or goals of the research need to be clearly stated in the introduction. The introduction should also clearly describe what this research contributes to the field. Discussions of related work should be separated from the results and discussion sections and moved to a separate related work section. The results section should clearly explain what experiments were run and what results were ob- tained from each experiment. The discussion section should discuss these results, not related work, and extract conclusions from them. The conclu- sions section should summarize everything which can be extracted from the results and connect the conclusions back to the goals and questions of the research. ****** 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. 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Revision 1
2 Nov 2021 Author Response Dear Dr Bongard, Thank you for the letter, regarding manuscript, ‘Heuristic algorithms in Evolutionary Computations and modular organization of biological macromolecules: applications to in vitro evolution ' by Spirov & Myasnikova. We hereby resubmit the manuscript. Above all we would like to extend our thanks and appreciation to the editors and reviewer for making very important and helpful comments. We modified the manuscript according to the reviewer’s recommendations. The major corrections are highlighted in red. Our point-by-point response to the reviewer’s comments follows. For the sake of convenience, the comments are enumerated. The page numbers are referred to according to the revised manuscript. The manuscript was strongly revised, structured, more illustrations (two new figures), and references were added. Several figures were revised. In response to the Reviewer’s comments, Introduction and Discussion were restructured, Results section was shortened. The conclusions from our numerical tests were explicitly formulated. The goal and major tasks of our study are now explicitly formulated in Introduction. The most significant insertions have been introduced into Discussion. The reviewer drew our attention to the fact that the prospects for our research were not sufficiently elucidated`. In response to this comment, we have added extended paragraphs discussing the prospects for experimental implementation of the algorithms we have proposed and tested. We hope to have given the full responses to all the comments. Thank you for your consideration, Sincerely, Alexander Spirov Ekaterina Myasnikova PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. Done. 2. Thank you for stating the following financial disclosure: [The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript]. At this time, please address the following queries: a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. The research was supported by the Russian Science Foundation (grant 17-18-01536). b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. c) If any authors received a salary from any of your funders, please state which authors and which funders. d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.” Please include your amended statements within your cover letter; we will change the online submission form on your behalf. 3. Thank you for stating the following in the Acknowledgments Section of your manuscript: [This work is supported by the Russian Foundation for Basic Research (grant no. 20-04-01015) and Federal Agency for Scientific Organizations of the Russian Federation (grant no. 01201351572).] We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: [The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.] Done. Please include your amended statements within your cover letter; we will change the online submission form on your behalf. Done. 4. Please amend either the abstract on the online submission form (via Edit Submission) or the abstract in the manuscript so that they are identical. Done. Reviewers' comments: Reviewer #1: 1. It is difficult to determine if the work is technically sound as the authors need to explain more clearly and specically what their motivations and goals were for this research, or what questions they were looking to answer. Our motivation: we, like some other researchers, are inspired by the similarity of ideas in the field of evolutionary computation and in vitro evolution, in general, and SELEX, in particular. We emphasis this in Introduction (1.1 Biological in vitro evolution and genetic algorithms; 1.2 Building Blocks in biology and genetic algorithms) and Discussion. Moreover, we are inspired by our observation that well-known in GA foundations Royal Roads problem is very similar to the problem of evolutionary search from scratch for multidomain (and multifunctional) synthetic macromolecules. This remarkable similarity inspired us for this study. In Discussion we also discuss the ways and prospects of implementation of more effective algorithms into biological experiment that can be also regarded as our motivation. In order to convey our motives to potential readers, we have added a new first figure (Fig. 1) to Introduction. This figure illustrates our expectation that "Heuristic algorithms from evolutionary computation hold remarkable promise for transfer to synthetic biology and biotechnology." We have clearly formulated the goal and two major tasks of the article (last para in Introduction, p. 7). 2. How their methods were implemented in silico was not explained clearly, and they do not summarize what specific conclusions they have drawn from their results. We expanded the description of the methods and their specific implementation in the Methods section. Specifically, we added the details of our implementation of mutations and crossover. The detailed description of standard selection methods ((µ, λ) and Sigma scaling selection) and specific versions of BioRS (biologically substantiated versions of BioRS fitness function) was previously included into Methods. To bring the BioRS function notations into correspondence with the rest of the text, the last subsection is now entitled “Competitive BioRS function (with domain interference)” and the explanation: “This version of the BioRS function is a further extension of “BioRS function with alternative domain structures” in which the domain interference is additionally taken into account” is introduced. To make the application of these methods clearer for readers, we have introduced several relevant links to this section from those places where the corresponding method is used. We have formulated the main conclusions summarizing the results of our numerical tests in the end of the Results section (pp. 28-29). We have also significantly expanded and restructured the Discussion section where these conclusions are analyzed and discussed (see also our responses below). 3. For example the authors reference the SELEX method, an existing in vitro method for evolution DNA aptamers. What are they specifically hoping to contribute to methods such as SELEX? We have added extended paragraphs to Discussion, where we formulate the prospects of experimental implementation of the algorithms we have tested. Specifically, we discuss modern experimental approaches of in vitro evolution using nucleic acid synthesizers, as it was done by prof. Kell’s group [Knight et al., 2009] (3.3 “In in vitro evolution small populations are preferable”, final paragraph (p.31)), and microfluidic techniques (3.4 “Prospects of hill-climbing-based methods” final paragraphs (pp.32-33)). 4. In the methods section they summarize various evolutionary algorithms, but they do not explain how the authors themselves explicitly applied them in their experiments. It is also not clear from the methods section how these various algorithms which they discuss related to their research questions or goals. The Methods section only encompasses those algorithms that are tested in our study. Now we specify these algorithms explicitly: “Our tests were implemented for two versions of BioRS: simple consensus-based and competitive.” To avoid the confusion the notation of the BioRS function with domain interference is corrected to “Competitive BioRS with domain interference”. See also the response to the previous comment. Our initial selection of (new) heuristic algorithms for in silico testing was inspired and dictated by the RR research area in GA. It was there that the standard (mu, lambda)-GA was tested in comparison with Sigma scaling selection, and in comparison with RMHC. We emphasize this in the text (See, for example, 2.2, 2nd last para, p.22). To develop this issue, we have also proposed and tested a parallel RMHC. A more complete list of promising algorithms that we have not tested yet, but which have shown their effectiveness in GA for RR problems, is given in Discussion. We expect that algorithms that are effective for RR problems in GA may turn out to be promising for in vitro evolution problems (which we repeatedly emphasize in the text). We have restructured the Results section to make it clearer for the reader. We have also paid attention to this issue in Discussion (final subsection). 5. The authors should define clearly in their introduction what questions they are seeking to answer with this research, what their novel contributions were, and what their utility is. The Introduction section has been substantially modified and structured to clearly outline our motives, our goal and the tasks we solve, as well as our most important result. As the most significant new result, we interpret our conclusion about the prospects of implementing the RMHC & parallel RMHC algorithms in new experimental approaches. 6. The results section is very verbose and contains a signiant discussion of related work, so it is difficult to determine what questions the various experiments or case studies were seeking to answer and whether they did so successfully. The authors do not clearly dene what success means in their various experiments, and they need to explain more clearly what the exact tness function was, how it was evaluated, and how it was implemented in silico. It is therefore difficult to identify what conclusions can be drawn from the paper. We have somewhat shortened or completely removed to Discussion the introductory paragraphs in Results subsections to present our work and its results more clearly. We explicitly presented our fitness function in Methods and explained how it was evaluated, and how it was implemented in silico. We have added key conclusions at the end of the Results (pp. 28-29) and discussed them in detail in the new Discussion subsections (see below). 7. It was only evident after reading the entire results section that the point of the in silico experiments was to identify the optimal algorithm features and hyperparameters for in vitro implementation through in silico simulation. This should be made clear in the introduction. Our intentions, goals and objectives are now clearly and explicitly formulated in the end of Introduction, p.7 (as noted above). 8. The discussion also contains a large discussion of related work rather than a discussion of their experimental results, and so after reading it, it is still unclear what conclusions the authors have drawn from the research, or whether their conclusions are novel, and what their utility is. The authors need a separate section where they summarize their conclusions, to discuss how their results lead to those conclusions, and connect their conclusions back to the goals or questions which they were hoping to answer with this research. As already mentioned above, we substantially supplemented and structured Discussion to discuss the results of our numerical tests and conclusions from them. The novelty of our research is determined by the novel idea of introducing the biologically substantiated extensions of RS-type fitness function that have prospects in experimental applications. This is explained in Introduction. 9. The experiments conducted in the paper were all in silico simulations. These simulations were composed of an analysis of their proposed evolutionary algorithm from different perspectives. Therefore, the expected statistical analysis would involve typical metrics often reported when analysing the performance of evolutionary algorithms. When analyzing the performance of evolutionary algorithms one generally needs to report: -Some variation of average success rate, that is, the fraction of algorithm runs where a solution of satisfactory quality was obtained. -The mean best fitness, which is the optimal fitness obtained from each run averaged over the number of runs. -The effectiveness, or the average solution quality obtainable within a given computational limit. -Or the efficiency, which is the average amount of time needed to achieve a solution of satisfactory quality. Given that computational time depends on the available hardware, efficiency is often reported as the average number of evaluations to a solution. These are also usually accompanied by progress curves for the various metrics. The authors reported success rate, effectiveness and efficiency in various figures throughout the results section. These reported metrics are sufficient for the nature of their in silico experiments, however, it is not always made clear how success was defined, that is, how the authors defined a solution to be of acceptable quality. We have completed all the Tables, as well as the corresponding figures (Fig. 7; 8; 9) so that all the test criteria adopted in the GA are given explicitly. Specifically, when comparing algorithms, we give the average number of fitness evaluations, standard deviation, and success rate. Additionally, we present in Supplement and briefly analyze the graphs presenting the mean duration (# of evaluations) of each next epoch in GA tests at different parameter values. These tests (Table 1) were implemented for the specific BioRS version with eight domains to make this empirical analysis more illustrative. 10. There are many grammatical problems with the text, potentially because the author's rst language is not English. So much so that it makes it difficult to understand what the authors are trying to communicate in many places. The spell check is done, grammar is corrected. 11. Further, some concepts were not sufficiently claried. The following concepts need to be explained more clearly: -Directed evolution / artificial evolution of biological macromolecules. The definition is given by an endnote. -How evolution of biological macromolecules is directed in vitro. This same endnote also provides a response to this comment. -In the case studies, how were the molecules which were being evolved, represented and evaluated in silico. As we explained now in the Methods section, in our tests: potential solutions are represented by one-dimensional symbol strings in (A,T,G,C) four-letter alphabet; bitwise mutations, (µ, λ) selection, and single point crossover are applied. Fitness functions for simple consensus-based and competitive BioRS are defined below in this section (p.36). -Implementation details of the selection, mutation and crossover / recombination methods. Implementation details are now given in Methods (pp.36-37). 12. Regarding the layout of the paper, the research questions or goals of the research need to be clearly stated in the introduction. The introduction should also clearly describe what this research contributes to the field. Done. Please see our responses above. 13. Discussions of related work should be separated from the results and discussion sections and moved to a separate related work section. The results section should clearly explain what experiments were run and what results were ob- tained from each experiment. The discussion section should discuss these results, not related work, and extract conclusions from them. The conclu- sions section should summarize everything which can be extracted from the results and connect the conclusions back to the goals and questions of the research. As discussed above, the main sections of the article, in particular Discussion, are modified, restructured in response to the Reviewer’s comments. ________________________________________ 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. ================================================================== Attachments Attachment Submitted filename: ___Response_to_Reviewers.docx https://doi.org/10.1371/journal.pone.0260497.r002
11 Nov 2021 Decision Letter - Josh Bongard, Editor Heuristic algorithms in Evolutionary Computations and modular organization of biological macromolecules: applications to in vitro evolution PONE-D-21-21266R1 Dear Dr. Spirov, 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, Josh Bongard Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ******** 2. 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 ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 4. 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 ****** 5. 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 ****** 6. 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 authors have satisfactorily addressed all comments and concerns. ****** 7. 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 https://doi.org/10.1371/journal.pone.0260497.r003
Formally Accepted
22 Nov 2021 Acceptance Letter - Josh Bongard, Editor PONE-D-21-21266R1 Heuristic algorithms in Evolutionary Computations and modular organization of biological macromolecules: applications to in vitro evolution Dear Dr. Spirov: 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. Josh Bongard Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0260497.r004

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