PWAT-D-22-00027

Advancing antimicrobial resistance monitoring in surface waters with metagenomic and quasimetagenomic methods

PLOS Water

Dear Dr. Ottesen,

Thank you for submitting your manuscript to PLOS Water. After careful consideration, we feel that it has merit but does not fully meet PLOS Water'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.

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Debora Walker

Executive Editor

PLOS Water

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Water’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

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Reviewer #1: Yes

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Reviewer #1: Yes

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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: Overview:

The work examined different methodology for detecting AMR in surface water from surface water from 1) a creek near a hospital and 2) a water reservoir used for recreation and municipal water in Maryland. The group compared culture independent data, both metagenomic and quasimetagenomic where they enriched the microbiome before sequencing. The comparison they made was whether the methodology could pick up the National Antimicrobial Resistance Monitoring System’s (NARMS) critically important resistance gene targets and found the quasimetagenomic testing to be more sensitive than metagenomic alone (30% vs 1% respectively). They also examined the genomic data using four different tools finding more data from the quasimetagenomic testing, in this pilot study the quasimetagenomic method was proven to be robust.

Overall comments:

I can see this is a huge piece of work, but I don’t fully understand the implication of the work, what are your recommendations?

Given the overview I would have expected that the manuscript would have some solid conclusions eg which genomic analysis tools are best for this type of data, which method is better for the analysis of water bodies going forward etc, I would like the authors to state clearly their conclusions.

Are there any limitations to the methods that you have used? Please describe them fully in your discussion

Was there a difference between the creek near the hospital compared to the water reservoir? One would assume there would be more resistant organisms found near the hospital, but I am unsure whether this is the conclusion from the work

What is the implication of this study? Is this likely to impact human health? What further studies might be performed to examine this?

I would like to see more statistical analysis comparing the different methodology and making comparisons between the two different waterways.

Specific comments:

Introduction:

Lines 81-83: In the introduction you describe NARMS as monitoring “a subset of WHO CIAs derived from Escherichia, Salmonella, Campylobacter and Enterococcus primarily isolated from human, food-producing animals, raw retail meats, and feed environments”, please reword this as I presume you mean that you monitor resistance to these antibiotics rather than the antibiotics themselves.

Lines 109-113: The last sentence of the introduction provides results, this needs to be reworded to describe what they are going to do instead of what they have done.

I would expect all figures to contain information about their contents without having to check the methods section and have prepared my comments as such.

Table 1:

What does the second column depict? Please provide a heading.

From a clinical point of view it would be useful to include Azithromycin under the macrolides heading in addition to Erythromycin.

I think it would be more effective if you combine tables 1 and 2 to show which resistance genes you detect in the NARMS programme.

Figure 1:

Please provide a key for the figures (eg CARB, CEPH) and whether some of these groups encompass some of the groups in c) encompass some of those that are split out in d)

What is meant by RPKM and Hits – are they equivalent? It’s difficult to make comparisons between the methods from the current figures

Figure 2:

How does this differ from figure 1? It appears to be the same to me.

Figure 3:

Please provide a key for the acronyms on the y axis

It seems to me there are differences between CI and QMGS, eg where VANYF if detected by QMGS but not CI in Sligo and VANRO is detected by CI and not QMGS.

Which analytical method was chosen for this figure? Did you focus on CARD alone here?

Figure 4:

Here you depict the CI and QMGS methodology from Sligo and only the QMGS method from Patuxent – please also provide CI from Patuxent (or remove the QMGS data)

Figure 5:

Which genes are being depicted in this figure? Are FOX (MEG_3034) and FOX (MEG_3029) the same gene? There is insufficient information provided to understand the figure.

What does a fold change mean? This seems to be a comparison between the two water bodies, I guess if the black is higher there are more resistance genes in Sligo and if the grey is more abundant there are more of the resistance genes in Patuxent, but this is not stated explicitly

Figure 6:

Lines 209-10: Please explain why you state no plasmids could be annotated from CI data, although

The figure displays the plasmids found in the two water bodies, while more plasmids were described in the Patuxent water, it would be interesting to understand what overlap there is in the water bodies.

Could tables 3 and 4 be combined?

Figure 7:

I found it difficult to understand figure 7, please provide more information (which are a, b, c and d).

Do the non-shaded areas mean no bacteria were observed using the specific methodology (CI vs QMGS)? Are these provided in order to make the comparisons between the different water bodies?

Figure 8:

It would be useful to have more of an overview of this data ie showing Campylobacter species, Enterococcus species etc as well as showing the specific species.

Please explain what 10, 50 etc are in figures a and b

I assume the figure depicts the different media used for enrichment, this needs to be explicit in the key to the diagram

Figure 10:

Why does the relative abundance of Actinobacillus increase in relative abundance between figure a) and b) for CI?

Discussion:

Lines 348-51: you conclude based on your data that 50L of water provides a significant increase in detecting capacity, I’m not sure your figures support this eg Fig 9 seems to show more information is available from 10L than 50L

Typos:

Please replace ‘surveils’ in Figures 9 and 10 for ‘surveys’

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Reviewer #1: Yes: Dr Catrin E Moore

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Advancing antimicrobial resistance monitoring in surface waters with metagenomic and quasimetagenomic methods

PWAT-D-22-00027R1

Dear Dr. Ottesen,

We are pleased to inform you that your manuscript 'Advancing antimicrobial resistance monitoring in surface waters with metagenomic and quasimetagenomic methods' has been provisionally accepted for publication in PLOS Water.

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

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

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

Best regards,

Katrina J. Charles

Academic Editor

PLOS Water

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Reviewer Comments (if any, and for reference):