Peer Review History

Original SubmissionJuly 22, 2019
Decision Letter - Lauren A Richardson, Editor

Dear Dr Sabeti,

Thank you for submitting your manuscript entitled "Combining genomics and epidemiology to track mumps virus transmission in the United States" for consideration as a Research Article by PLOS Biology.

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Revision 1
Decision Letter - Lauren A Richardson, Editor

Dear Dr Sabeti,

Thank you very much for submitting your manuscript "Combining genomics and epidemiology to track mumps virus transmission in the United States" for consideration as a Research Article at PLOS Biology. Your manuscript has been evaluated by the PLOS Biology editors, an Academic Editor with relevant expertise, and by several independent reviewers.

As you will read, the reviewers appreciate many aspects of your study. However, they also raise some concerns that will need to be addressed in a revision. Of particular note, Reviewers #2 and #3 both believe that further evidence that vaccine escape is not contributing to the outbreak is needed. Reviewer #2 and the Academic Editor also believe that the scope of the results and title should be tempered to reflect the region where samples were obtained.

In light of the reviews (below), we will not be able to accept the current version of the manuscript, but we would welcome resubmission of a much-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 for further evaluation by the reviewers.

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Reviewer #1: Nathan D. Grubaugh, signed review

Wohl et al. provide an excellent investigation of the 2016-17 mumps virus outbreak in Massachusetts using genomic epidemiology. While I didn't have access to previous reviews and author responses, this version reads very well and tells a very interesting and complete story. The analyses all seem appropriate and the figures look nice and are mostly clear. I highly recommend this for publication and provide only a couple minor comments about the figures.

1. It wasn't until I read the main text did I really understand figure 2 (and I typically look at all of the figures before reading). There is a lot of important info buried in the legend, especially to explain B and C. Could the authors add a label to show that the left panels are estimates made from epi data and the right panels include genomic data? If this is clear from the start, the figure would be much clearer and more powerful.

2. Given the space in the main text, I would recommend brining some of the very nice and informative supplemental figures to the main text. The authors can choose, but I would recommend S1, S4 (but update the title to make it clear that this was used to investigate vaccine escape, then perhaps simplify it to showcase the main points), and S9.


Reviewer #2:

Wohl et al. present a molecular epidemiological analysis of recent mumps outbreaks in Massachusetts during 2016-17. Using whole genome viral data, they are able to reconstruct the spread of mumps between neighboring communities including several universities in the region and connect these local outbreaks to larger-scale transmission patterns in the United States. They also explore whether mumps has undergone antigenic evolution to escape vaccine-based immunity, but do not find any genetic changes that can be correlated with vaccination patterns.

While this paper reports a perfectly valid molecular epidemiological analysis, the viral sequence dataset they analyze is limited to only ~200 samples collected mainly in MA from 2016-17. Thus authors conclusions about mumps circulation in the larger U.S. are therefore somewhat suspect, and I believe the authors over interpret what such sparsely collected data can tell them (see main criticism below) about larger circulation patterns.

Main criticism:

1) Results Lines 102-103: The authors find that a single mumps lineage has dominated in the US since 2006 and then argue that this “implies that continuous and extensive geographic movement of mumps virus, rather than isolated outbreaks, underlies mumps in the US” —> I don’t actually see evidence for this claim in the phylogeny shown in Figure 1. If anything there is a fair amount of clustering in the phylogeny by region and lineages sampled in MA and NE one year are most closely related to lineages sampled in the those regions the previous year. It’s therefore possible that the G genotype spread slowly throughout the US and the virus is now persisting locally in each region.

2) The possibility that mutations may have allowed for vaccine escape is of major interest, but no mutations were found to strongly correlate with vaccination status or show signs of positive selection (dN/dS > 1). But classic dN/dS ratios would be very underpowered to detect selection here (Kryazhimskiy et al, PLoS Genetics, 2008) since there has presumably not been enough time for the multiple mutations needed to produce a signal of positive selection under these tests to accumulate. In light of this, maybe it would be better to plot the frequency of each mutation among sampled viruses over time and look if any mutations in antigenic regions have dramatically increased in frequency?

Minor remarks:

Line 544: ‘e-i(t)’ —> I’m guessing this should be e^{-lambda_i(t}?


Reviewer #3: Christophe Fraser, signed review

The authors generate approximately 200 new genomes of mumps virus circulating during an unusually large epidemic in and around Boston universities. They show that the virus consists of multiple widely circulating lineages. They highlight the increased resolution into transmission. Using the SH gene, they compare their sample to viruses circulating globally, and make the case for a persistent US-European lineage causing most cases. They demonstrate that the virus has an effective reproductive number RE well above one, and that control measures need to focus on blocking local transmission. A lot of work went into this impressively comprehensive analysis.

This study is well executed. The case that there is a lot of local transmission is convincing, and the finding of multiple closely related lineages circulating is surprising.

The authors also address the question of whether the virus has mutated to escape vaccine, and conclude that waning immunity is a more likely explanation for persistent transmission. I was less convinced by the robustness of this section of the paper. I was not convinced about the power of the dN dS analysis to detect escape from the vaccine selection pressure. At least, it was not clearly motivated what assumptions or hypotheses were being tested.

Perhaps more could be made of the data on time since vaccination, comparing negative and positive samples, and also formally testing whether subtitutions are associated with time since vaccination.

The data sharing statement should refer both to the sequences and to the associated metadata; currently the authors only propose to share sequences.

Specific comments:

Introductory paragraph, lines 46-56. How sure are the authors that temporally changing patterns of reporting might not affect these observations?

Line 60. ‘academic institutions and other close contact settings.’ Please use more specific language. What is a ‘close contact setting’? Does this include a household?

Line 60, and repeated several times later. Where possible, avoid open ended ranges such as ‘at least 18’, and instead use ranges and estimates.

Line 65. I am not convinced that ‘phylogenomic analysis’ is a thing and think ‘phylogenetic analysis’ would be clearer.

Line 76. The number of genomes is variously 201 (here), 200 (line 96), and 203 (Line 220 and Figure S1). Please check to make this consistent, or specify if slightly different samples were used for different analyses.

Line 81. ‘Median sequencing depth’. Also specify 95% range.

Line 81. ‘All genomes were at least 82% complete.’ This is not a fair description of the sequencing success rate, if I understand correctly the information provided in Fig S1. The authors generated 203 genomes from 259 samples. So 56 samples (22%) were excluded, because of low viral loads associated with late collection of the samples. This is relevant information for readers interested in assessing the sequencing method used here. It is also possibly relevant as a sampling bias to consider in the discussion.

Lines 91-95. Whilst I am convinced that this conclusion is likely correct from the paper, I don’t see how you can conclude this from the analysis of the genomes (Figure 1). It rather seems to be a conclusion of the partial genes (Figure 3). To conclude this, you need to place the diversity in your sample in the context of the full global diversity, which you can only do with the SH gene. If you agree, then it seems you may need to present Figure 3 before Figure 1. I can see this is awkward since you want to showcase the genome trees & data, but you could make a case for the broad level information from a conventional SH analysis, and then zooming into the much higher resolution whole genome data.

Lines 129-139. To me, this was the most opaque section of the paper. First on dN/dS: Why is a dN/dS analysis appropriate for addressing the question of vaccine escape? Why would vaccine selection produce higher dN than non-vaccine immunological selection? Is the study powered for this comparison? It is not clear to me that a codon-by-codon analysis, as shown in Fig S4A or B is valid without correcting for multiple testing, and I don’t understand what conclusion, if any, the authors are drawing from this analysis. In terms of the substitutions, the authors conclude that most mutations fixed here were already present in an ancestral sample (Iowa 2006), and thus that immune escape is unlikely (lines 991-998). The authors should make explicit the assumption of some kind of additive model here: why is not plausible that one of the two mutations identified, 336 and 474, could alone be responsible for vaccine escape? Without further wet-lab neutralisation assays, it must be hard to tell. Overall, I can see why the authors did the analyses, the question is interesting. But the conclusions seem vague at this stage.

Lines 158-181. This is a convincing analysis, and really highlights the power of the whole genome data.

Methods. The authors use well-established in-house viral genomics methods and publicly available phylogenetic software.

BEAST analysis: could you show the estimated skygrid plots for effective population size (Ne.tau)?

PCA analysis (lines 478-481). Does this add anything to the paper?

Stochastic model. The branching process approach looks sensible. The model estimates for lines 581-586 seem interesting, but I can’t see any estimates in the paper?

Table S1. Please include the time since vaccination for both the positive and negative samples. Could more not be made of a comparison between the two?

Lines 1005-1010. This seems an orphan paragraph. Could you add a sentence to place these findings in context?

Lines 1013-1045. These are interesting findings on lack of diversity in host, though paragraph 1035-1045 seems very speculative given the data.

Revision 2

Submitted filename: mumps-plosbio-response.docx
Decision Letter - Lauren A Richardson, Editor

Dear Dr Sabeti,

Thank you for submitting your revised Research Article entitled "Combining genomics and epidemiology to track mumps virus transmission in the United States" for publication in PLOS Biology. I have now obtained advice from two of the original reviewers and have discussed their comments with the Academic Editor.

Based on the reviews, we will probably accept this manuscript for publication, assuming that you will modify the manuscript to address the remaining points raised by the reviewers. Congratulations!

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Reviewer #2:

The authors' revision has improved an already good paper. But I still disagree with their major conclusion that widespread geographic dispersal must be common.

Specifically, the authors say that: "Given the modest sampling in this dataset from outside the Northeast, finding such wide geographic dispersal suggests that long-distance migration of the virus is common in the US"

I hate to be difficult, but I really don't think this is the most parsimonious conclusion to be drawn from the phylogeny in Figure 1. Rather I would say there is strong evidence for regional circulation (e.g. in MA and the NE) with occasional long-distance disperal to more distance regions of the U.S. After all, there is relatively strong clustering even from regions like the Midwest that were very under-sampled. Of course, more sampling from different regions may in fact reveal long-distance dispersal is common, I just don't feel that this should be assumed without evidence.


Reviewer #3: Christophe Fraser, signed review

The authors have done a great job responding the comments. They have strengthened their conclusions on waning immunity. They have clarified both the motivations for the different linked analyses, and highlighted limitations where appropriate. This is an impressively comprehensive study with several interesting and (to me, at least) unexpected conclusions.

Revision 3

Submitted filename: mumps-plosbio-response2.docx
Decision Letter - Lauren A Richardson, Editor

Dear Dr Sabeti,

On behalf of my colleagues and the Academic Editor, Sara Y Del Valle, I am pleased to inform you that we will be delighted to publish your Research Article in PLOS Biology.

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