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.

Dear Dr Krogh Jensen,

Thank you very much for submitting your manuscript "Literate programming for iterative design-build-test-learn cycles in bioengineering" for consideration at PLOS Computational Biology.

As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments. In particular, please take care to address the detailed and constructive comments of Reviewer 2 in full.

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

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

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

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

Important additional instructions are given below your reviewer comments.

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

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

Sincerely,

Ruth E Baker

Section Editor

PLOS Computational Biology

Ruth Baker

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The manuscript describes computational and experimental work which has been executed to a high standard, is novel, interesting and makes a significant contribution to the biotechnology field. As a structural biologist, I am not expert enough in bioinformatics to make an authoritative judgement, but the paper is well-written, technically sound and the standard of presentation is very high. I thought that the introduction was rather brief and would possibly benefit from citing related work of others in this field. Apart from that I am happy to recommend publication of the manuscript in its present form.

Reviewer #2: The article introduces the Python Software teemi, designed to assist in the organization and guidance for strain construction. It supports various steps in the DBTL cycle while adhering to FAIR principles. The authors provide a case study that involves simulating guided and iterative laboratory workflows to optimize strictosidine production in yeast.

While this work may be of interest to the community, its current form appears to be more a collection of scripts or a Python package than a comprehensive platform for DBTL. As a result, it's unclear from the paper if the contribution is substantial enough for publication in PLOS Computational Biology. A relevant extra effort would be needed to design such a comprehensive platform. Here are some issues that would in anycase need to be addressed before publication.

Major Comments:

1. A workflow of the tool is missing. This omission makes it difficult to gauge the tool's generalizability. To be considered a platform, it should be evident what inputs are required from the user and what outputs the platform provides at each step of the DBTL. Does the user need to modify internal code to use the tool? If so, it resembles a collection of files that could serve as templates or inspiration rather than a platform.

2. The title suggests that the use of literate programming is a significant contribution to DBTL cycles in synthetic biology. However, literate programming is widely used by the synthetic biology community for iterative DBTL, especially through Jupyter notebooks. This creates confusion. The title is misleading (the actual name of the package in Github is "a python package designed to make high-throughput strain construction reproducible and FAIR). It is crucial for the authors to clarify the primary contributions of their work.

3. Table 1 is notably incomplete. Please update it with platforms that have already been released and published, addressing the DBTL cycle. For example, the Galaxy project is cited, but what about GalaxySynbioCad, which is a Galaxy-based platform specifically tailored to the DBTL pipeline? (https://www.nature.com/articles/s41467-022-32661-x)

4. The main assumptions, decisions, and methods adopted at each stage of the DBTL should be clearly explained (in connection with comment 1). For instance, in the BUILD module, the authors adopted CasEMBLR for CRISPR/Cas9-mediated assembly, and in the TEST stage, they used DMA Sequence and LC-MS...

5. In the LEARN stage, the authors claim that the library for the next iteration is based on the top-performing predicted models. However, it seems that no combinatorial experimental design is applied to enhance the exploration of solutions. This could introduce bias into the results, and this aspect is not adequately clarified in the text.

6. The tool's features and functionalities need to be specified. The term "engineering of complex biosystems" is too abstract. The features supported are clearly specified in the documentation of the Python package, but not in the paper.

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

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

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes: Jonathan B Cooper, UCL.

Reviewer #2: No

Figure Files:

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

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Reproducibility:

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

Dear Dr Krogh Jensen,

We are pleased to inform you that your manuscript 'teemi: An open-source literate programming approach for iterative design-build-test-learn cycles in bioengineering' has been provisionally accepted for publication in PLOS Computational Biology.

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

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

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

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

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

Best regards,

Ruth E Baker

Section Editor

PLOS Computational Biology

Ruth Baker

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #2: The authors have satisfactorily addressed all the points raised. The rationale for the methods and approaches

adopted in the study are now much clearer for the reader, and the work as it is presented is a relevant contribution to the community.

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

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

Reviewer #2: Yes

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

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

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

Reviewer #2: No