Transfer Alert

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Dear Professor Inoue,

Thank you very much for submitting your manuscript "De novo virus inference and host prediction from metagenome using CRISPR spacers" 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 have raised substantial and significant concerns related to the novelty, accuracy, robustness, and validation of the described method and these concerns (as well as others noted in the reports below) should be fully addressed. 

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.

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Sincerely,

Elhanan Borenstein

Associate Editor

PLOS Computational Biology

Alice McHardy

Deputy 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: Sugimoto et al present a census of viruses from the human gut by matching CRISPR spacers to sequences carrying protospacers. The approach is straightforward and timely, and the findings are, on the whole, credible and interesting. The multitude of identified small ssDNA viruses, the majority of these previously unknown, is notable.

There are some concerns, though.

1. The cut-off used for protospacer detection, 93% identity, is not as stringent as the authors claim.

This means 2 mismatches for the typical spacer length are allowed, which is not error-proof, so an assessment of the false positive rate is necessary.

2. The authors claim "may entirely novel genomes of unknown taxa", but this claim is misleading because novelty here means failing an extremely stringent threshold, 85% nucleotide identity. It is disingenuous to claim "entire" novelty and actually any novelty as such based on this threshold. Roughly, this result means that a number of viruses could not be included in already know genera. All novelty statements have to be revised to this effect.

3. The "novel" genomes were then searched with capsid protein profiles to determine the fraction of the "novel" sequences that were likely to come from viruses. However, neither the selection of the capsid genes nor the matching criteria are adequately described. Only the cut-off score is indicated which in itself tell nothing about the specificity and sensitivity of the search.

4. There is effectively no attempt to analyze the genomes of "novel" viruses and place them within or outside the current virus classification. To this reviewer, this is a major deficiency. We want to know whether the approach implemented in this paper actually allows one to discover truly novel viruses, those without close evolutionary connections to known families. The current version of the manuscript does not answer this question.

Language: editing by a native English speaker is desirable - the manuscript is not written particularly poorly, overall, but nevertheless, there are quite a few obscure or ungrammatical sentences.

Reviewer #2: The authors present a methodology to detect viral sequences and their microbial hosts based on CRISPR spacers retrieved from assembled contigs, as well as from unassembled read data. They used the suggested approach to perform an analysis of phage-host interactions in gut-associated microbiomes. The authors conclude by performing a phylogenetic analysis of diversity generating retroelement (DGRs) present in crAssphage, an abundant phage in gut microbial communities.

Despite the extensive bioinformatic analyses, I found fundamental flaws and little conceptual novelty in the presented research.

The methodology is based on using assemblies to associate microbial host cell with CRISPR directed repeats (DRs) and then seeking these DRs in raw read data to recruit large spacer databases associated with each host. The last step is using these spacers to detect protospacers, presumably in viruses, that match the spacers, thus linking hosts to viruses. The problem with this linkage of host-DR-spacer-virus approach is that it does not provide a unique mapping from host to virus. Specifically, the host-DR link is problematic, as it has been demonstrated that evolutionary distant bacteria can contain perfectly identical DRs. This occurs due to the high rates of HGT these systems undergo. The consequence of identical DRs in a completely different host is that, unless there is evidence connecting relevant spacer-containing reads to a specific contig, the genuine microbial host cannot be inferred by the suggested process. This is evident even from the results presented by the authors themselves, who state they observe high rates of phages that are reportedly targeted by bacteria from different phyla (“1,418 TR sequences (12.5%) were predicted to be targeted by multiple phyla”). Without evidence to the contrary, the most likely explanation is that these 12.5% of the targets are not infecting bacteria from different phyla (including viruses allegedly infecting both Gram-positive and Gram-negative bacteria), but rather the CRISPR-Cas systems in these hosts cells have identical DRs. This phenomenon is expected to be even more severe in lower taxonomic levels, which more readily exchange genetic material, rendering the host-virus association not informative.

Further, in the title and along the manuscript, the authors suggest that viral sequences can be detected based on CRISPR-matching protospacers. This is misleading, as it is known (and indicated by the authors at some point) that CRISPR spacers do not target viruses exclusively. Retrieved sequences can include plasmid, transposable elements, and even microbial chromosomes. While not abundant, self-targeting spacers have been found and are explained by silencing of CRISPR-Cas systems using different mechanisms, such as anti-CRISPRs or mutations in the flanking repeats.

The target analysis is based on retrieved terminally redundant sequences. The authors state that they have “successfully extracted 11,391 terminally redundant (TR) CRISPR-targeted sequences ranging from 894 to 292,414 bases. These sequences are expected to be complete or near-complete circular genomes”. I find this assumption to be very problematic. The authors do try to substantiate their assumption by searching for phage signature genes in TR sequences and report finding them mostly in large (>20kb) contigs. For short TRs, they mention that they “are unable to strongly conclude whether the remaining small TR sequences are viruses or not at this point.” Still, throughout the manuscript, they treat those TRs as complete genomes or plasmids. Terminally redundant sequences, especially ones as short as 894 bp, could have other origins, which the authors should have considered. Transposons, for example, can be difficult for assembly algorithms to include within contigs and can have terminal repeats, appearing as TR sequences.

A key component in the suggested approach is the detection of spacers in read data. Yet, the authors failed to mention numerous previous studies applying this approach, including tools designed specifically to perform this task, such as CRASS (Skennerton et al., NAR 2013) and MetaCRAST (Moller et al., PeerJ 2017).

Finally, the concluding evolutionary analysis of DGRs in crAssphage seems unrelated to the rest of the manuscript.

Reviewer #3: Sugimoto and colleagues present a de novo virus detection pipeline based on using CRISPR spacers, and apply this approach to over 11,000 human gut metagenomes to detect viral genomes and infer a surprising 70% with a putative host prediction. The authors additionally focus analyses on diversity-generating retroelement (DGR) loci from the widely distributed crAssphage and surmise that there is a common ancestor with human- and baboon-derived sequences. Overall, for a new virus detection pipeline, I would have expected a thorough benchmarking of the methods compared to existing methods (eg, VirSorter or VirFinder) and detailed quality assessment based on the recent MIUViGs standards (Roux et al, Nature Biotech 2019). As written, the pipeline and resultant data are very descriptive and lack a statistically robust assessment of false/true positive recovery rates. Further, it is unclear the level of novelty of this work compared to other approaches to detect uncultivated viruses from metagenomic data. For example, the authors compare the recovery rate of TR sequences >20Kb and nearly all are recovered in existing databases (IMG/VR, RefSeq Plasmid, GVD), with the remaining <20Kb not well represented in databases, but also questionable as to whether they even represent viral sequences. Below the authors should consider several major concerns with the current manuscript, and seek to address these to better validate their pipeline.

Major Comments

In general, the pipeline is fairly well described, but lacks necessary benchmarking. There are a number of unexplained decisions that also need clarification. For example, the 93% sequence identity threshold for masked CRISPR hits is a very permissive threshold to select, and I question what that rationale was. Typically, identical matches or 1-mismatch are allowed given the short sequence length of spacers and to avoid spurious hits. Additional details for why this threshold was selected and a benchmarking of true vs. false positives is needed to ensure the underlying quality of the data is robust.

The crAssphage DGR analysis and inference is poorly described and questionable. In particular, the link between the human gut crAssphage DGRs and the single (?) baboon sequence to infer function/activity is not grounded in much evidence. A more thorough analysis is warranted. Further, any inference of activity should be based on more than a single time point/sequence, and would ideally have longitudinal data for analysis of dynamics/function.

In general, the manuscript would benefit from significant revision to better organize the development/benchmarking of the pipeline and the subsequence analysis of the 11,000 gut metagenomes. For both, the authors should consider focusing on the lines of evidence to support their findings, instead of drawing conclusions based on little evidence. The authors should also thoroughly check for grammar/spelling.

Minor comments:

L. 54: Using the term “parasitic nature” does not accurately describe viral modes of activities, so I would suggest removing this phrase.

L. 59: Metagenomics encompasses more than sequencing host-associated samples, so I encourage the authors to ensure an accurate definition. Further, the authors should also describe that beyond bulk metagenome sequencing from a given environment, laboratory-based approaches to target viral particles and subsequent sequencing (eg, viromics) is another widely used approach to sequence uncultivated viruses.

L.75: A definition of “totally different” is warranted in this context. While reference-based virus detection tools do have limitations, many available tools rely on HMM-based searches which does enable recovery of divergent virus genomic sequences.

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Dear Professor Inoue,

Thank you very much for submitting your manuscript "De novo virus inference and host prediction from metagenome using CRISPR spacers" 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.

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,

Elhanan Borenstein

Associate Editor

PLOS Computational Biology

Alice McHardy

Deputy 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 #1: The authors have addressed three of my major comments adequately. However, the most important issue, namely, comment #4, on the lack of an appropriate characterization of the identified virus genomes, remains unresolved. I think this type of analysis is a must in a paper on virus discovery.

Reviewer #2: I appreciate the authors’ genuine efforts to address the issues raised in my review, but I still find fundamental problems with the host taxonomy inference, which is key to the study. The authors attempted to address the concern I raised and added an ad-hoc (the results of which support the issues I’ve brought up). However, I find the host inference analysis *conceptually* problematic. The high rates of HGT, acknowledged by the authors, render the host inference ineffective when relying on an assembled reference database such as RefSeq. Due to the frequent HGT events, observing a directed repeat (DR) in a given organism within the reference database does not mean that the DR resides in the same host in the analyzed sample. Thus the host of a virus targeted by a spacer flanked with DRs cannot be reliably determined based on the presence of the DR in a specific host in RefSeq.

The authors try to deal with this to a certain extent by disregarding DRs that appear in RefSeq in multiple hosts. But this assumes that the representation of CRISPRs in various hosts in RefSeq is comprehensive and static. However, in actuality, it is partial and very much dynamic. Thus, the host inference analysis, which is a major part of this manuscript, is highly problematic in its current form.

Following my comment on the matter, the authors referred to plasmids and transposons in different parts of the manuscript. However, the title of the manuscript, as well as the abstract and major parts of the main text, still refer solely to viruses. This is misleading, as more than 59% of the small TR seqeunces and more than 15% of the large TR sequences detected in this study seem to originate from plasmids or similar elements.

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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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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.

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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 Professor Inoue,

We are pleased to inform you that your manuscript 'Comprehensive discovery of CRISPR-targeted terminally redundant sequences in the human gut metagenome: viruses, plasmids, and more' 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,

Elhanan Borenstein

Associate Editor

PLOS Computational Biology

Alice McHardy

Deputy 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 additional analyses and clarifications the authors added to the manuscript text addressed all my concerns.

I appreciate the authors' thorough and elaborate reply.

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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.

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Reviewer #2: No