Dear Dr Dunlop,

Thank you very much for submitting your manuscript "Generating information-dense promoter sequences with optimal string packing" 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.

The reviewers appreciate the goal to computationally generate promoters with densely packed binding sites. They raise several points to discuss, which will enhance the paper. Furthermore, both reviewers suggest that experimental validation would significantly strengthen the manuscript, so please consider whether this is possible.

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,

Stefan Klumpp

Academic Editor

PLOS Computational Biology

Stacey Finley

Section Editor

PLOS Computational Biology

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

Both reviewers suggest that experimental validation would significantly strengthen the manuscript, so please consider whether this is possible.

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Summary of manuscript:

In the manuscript entitled “Generating information-dense promoter sequences with optimal string packing,” the authors described solution methods to create promoter sequences that contain many transcription factor binding sites in a specified (typically short) length of DNA. The final solver developed for this task is available online, and the ability to generate promoters with densely packed binding sites could be of general interest to the synthetic biology or cell engineering communities. However, the functionality of at least one promoter library must be shown to demonstrate the expected value of this novel solution method. Demonstration of bacterial promoter library function would suffice.

Other comment:

(1) It is often unclear what the library size is for each generated library, referring to the number of sequences that would need to be screened to test for function (number of sequences generated), instead of the author’s definition of library size [R] = number of binding sites. This information is necessary to gauge the usefulness of each generated library, as screening 10^6 promoters for function might be possible in one system, while testing 10^1 might be more feasible in another. As the manuscript sells the SSP method for promoter library generation, discussion of the feasibility of testing the generated libraries is warranted.

(2) Promoter library sequences, the full sequences in addition to the inputted binding sites, should be included in the supplement or extended data, primarily for libraries that are expected to have function like the bacterial promoter libraries.

Reviewer #2: Natural promoter regions may contain many overlapping binding sites of transcriptional factors, affecting transcription initiation rates. Despite the common occurrence of overlapping binding sites in nature, the rapid artificial design of nucleotide sequences with many overlapping sites remains a challenge. In this paper, the authors propose a computational approach for designing nucleotide sequences with densely packed DNA-protein binding sites, termed the Nucleotide String Packing Problem (SPP). They first demonstrate that the SPP problem is NP-hard, and thus simplify the problem into Orienteering Problem with integer distances, which can then be efficiently solved using various open-source and commercial solvers. The authors subsequently explore many possibilities of the method in the design of bacterial promoters.

Suggestions provided are as follows:

1.Regarding the issue of bias in solutions, the authors attempt to explore the effects of binding site size and sequence on bias, while briefly mentioning the potential impact of different solvers due to their different internal algorithms. However, the explanation for the effects of binding site sequences and different solvers is not sufficiently clear. For the effect of sequences, one approach could be to investigate the influence of bias from the perspective of sequence overlap. Additionally, exploring different solvers and observing their specific effects on bias, if any, could also be attempted here.

2.The article mentions that "Meanwhile, generative AI techniques are starting to show promise in emulating the complexity of context-dependent promoters (31–37). However, these models often struggle with interpretability, and fine-tuning them to include or exclude specific binding sites still requires specialized expertise (38)." However, in practice, the method designed in this article may rely more heavily on specialized expertise, as understanding different binding sites may involve complex processes. Additionally, whether existing expert knowledge is sufficient to generate binding site libraries consistent with natural promoters is worth discussing. It is recommended that the authors provide a clearer explanation in this regard.

3.Furthermore, due to the ambiguity in determining binding sites in biology and the variation in protein-motif binding across different biological states, whether more densely distributed binding sites correspond to a more suitable promoter is still worth considering. It is hoped that more discussion on this aspect will be provided in the Discussion section.

4.If experimental conditions permit, synthesizing designed promoter sequences and subsequently measuring the strength of artificially designed promoters using methods such as fluorescence protein assays would enhance the persuasiveness of the article.

5. The introduction part lacks a comprehensive overview of the categories of computational methods related to promoter design, and there are additional types of computational methods relevant to promoter design that should be introduced. For example, some promoter strength predictive models (classification/regression), which may play a crucial role in in silico directed evolution.

6.Minor issue: The title of Figure 4 is not bold, inconsistent with other figures.

**********

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

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

Reviewer #1: No: I don't think the data generated is available

Reviewer #2: Yes

**********

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

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.

Data Requirements:

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

Reproducibility:

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

Dear Dr Dunlop,

We are pleased to inform you that your manuscript 'Generating information-dense promoter sequences with optimal string packing' 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,

Stefan Klumpp

Academic Editor

PLOS Computational Biology

Stacey Finley

Section Editor

PLOS Computational Biology

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

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 addressed my concerns, therefore I think this article can be accepted.

**********

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: None

**********

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