PREreview of Global diversity and evolution ofSalmonellaPanama, an understudied serovar causing gastrointestinal and invasive disease worldwide: a genomic epidemiology study

We, the students of MICI5029/5049, a Graduate Level Molecular Pathogenesis Journal Club at Dalhousie University in Halifax, NS, Canada, hereby submit a review of the following BioRxiv preprint:  

Global diversity and evolution of Salmonella Panama, an understudied serovar causing gastrointestinal and invasive disease worldwide: a genomic epidemiology study 

Caisey V. Pulford, Blanca M. Perez-Sepulveda, Danielle J. Ingle, Rebecca J. Bengtsson, Rebecca J. Bennett, Ella V. Rodwell, Maria Pardos de la Gandara, Charlotte Chong, P. Malaka De Silva, Magali Ravel, Véronique Guibert, Elisabeth Njamkepo, Neil Hall, Marie A. Chattaway, Benjamin P. Howden, Deborah A Williamson, Jay C. D. Hinton, François-Xavier Weill, Kate S. Baker 

bioRxiv 2024.02.09.579599; doi: https://doi.org/10.1101/2024.02.09.579599  

We will adhere to the Universal Principled (UP) Review guidelines proposed in:  

Universal Principled Review: A Community-Driven Method to Improve Peer Review. Krummel M, Blish C, Kuhns M, Cadwell K, Oberst A, Goldrath A, Ansel KM, Chi H, O'Connell R, Wherry EJ, Pepper M; Future Immunology Consortium. Cell. 2019 Dec 12;179(7):1441-1445. doi: 10.1016/j.cell.2019.11.029  

SUMMARY: Nontyphoidal Salmonella (NTS) disease caused by Salmonella enterica serovars represents a global health burden associated with gastrointestinal disease. Most research is focused on serovars Typhimurium and Enteritidis that cause NTS in sub-Saharan Africa; however, the relatively understudied S. enterica serovar Panama (S. Panama) causes NTS cases globally. Pulford, et al. (2024), present a genomic epidemiology study investigating antimicrobial resistance (AMR) trends across defined population groups (clades) of S. Panama. Through this work they also speculated on the evolution of the serovar and proposed assessing genetic markers for invasiveness found within the clades of S. Panama. To complete this research, they complied a robust dataset of 836 sequenced genomes of S. Panama isolates collected over 88 years from 45 countries across 6 continents. Four population groupings or clades of the isolates were defined using phylogenetic relationships and Bayesian Analysis of population structure. This analysis revealed regional clustering in the phylogenetic tree, as demonstrated by the high number of isolates in each clade from the same geographic area (Latin America & Caribbean, Martinique, Europe or Asia & Oceania). Next, the genomes were scanned for genes and mutations known to result in reduced antimicrobial susceptibility to determine AMR trends across the clades. Only 14.5% of isolates were identified as having resistance, and the majority of those fell within either the European or Asia/Oceania clades (C2 & C4). It was found that AMR genes clustered on plasmids within the genomes suggesting plasmid mediated resistance within S. Panama. To address the evolutionary history of the serovar, they determined the most recent common ancestor (MRCA) of all the clades and each clade individually to show when the serovar emerged (1500s) and when it was more recently introduced to various regions (1870-1890s). Finally, they used an ‘invasiveness index’ (based upon the assumption mutations in certain genes correspond to increased invasiveness) to demonstrate that the European clade (C2) had a significantly higher invasiveness index than the other clades.   

OVERALL ASSESSMENT:  This study provides an excellent example of the application of genomic epidemiology techniques to an understudied serovar of S. enterica. The authors generated and thoroughly investigated a large dataset to provide meaningful insights into AMR within the S.Panama serovar. The data presented will be very helpful in public health monitoring of this serovar in the future. Here, we provide the authors with feedback to shift how some data is presented/discussed to strengthen the paper for both a public health audience and researchers looking to build upon this study. 

STRENGTHS:  The authors have completed a solid genomic epidemiology study into S. Panama using the standard bioinformatic methodologies in the field. The phylogenic grouping into clades corresponding to geographic groups is well done. The prevalence of AMR in the serovar (specifically located on plasmids) and certain clades is convincing. Overall, the paper is well written, sufficient background information and rationale is provided, and the results are easily understood, all of which make the study more accessible to a generalist audience.

WEAKNESSES:  There seems to be an assumption that S. Panama originated in Panama made throughout this paper; providing evidence of this specific origin would lend credence to their phylodynamic analysis. The main take away points regarding plasmid-mediated AMR are underemphasized compared to the less convincing invasiveness index findings.

DETAILED U.P. ASSESSMENT:  

OBJECTIVE CRITERIA (QUALITY)

1.   Quality: Experiments (1–3 scale; note: 1 is best on this scale) SCORE = 1.5

Figure by figure, do experiments, as performed, have the proper controls? [note: we use this ‘figure-by-figure' section for broader detailed critiques, rather than only focusing on controls]. 

· Fig 2: Overall, the figure is very informative, but the use of different scales for each clade makes it more challenging to compare between clades. Potentially, making a condensed version of the figure using stacked bar chart for main text and moving the original to supplemental could aid comprehension.

· Fig S2: This figure was well done and effectively demonstrates how AMR spread through the European clade. Perhaps this figure could be moved from supplementals to main text. 

· Fig 3: It appears that the tool used for data visualization for this figure is not properly cited. Any other tools used for data visualization should also be cited.

· Fig S3: When discussing this figure within the text, including the distinction between significance difference and meaningful difference would be beneficial. Also, including the machine learning model (cited in this results section) features/criteria used to make choices would be helpful (further mentioned in a comment below).   

Are specific analyses performed using methods that are consistent with answering the specific question?  

· Is there appropriate technical expertise in the collection and analysis of data presented?

·   Yes, appropriate technical expertise is demonstrated throughout.  

· Do analyses use the best-possible (most unambiguous) available methods quantified via appropriate statistical comparisons?  

· Yes, the analyses were well done throughout the paper.  

· Are controls or experimental foundations consistent with established findings in the field? A review that raises concerns regarding inconsistency with widely reproduced observations should list at least two examples in the literature of such results. Addressing this question may occasionally require a supplemental figure that, for example, re-graphs multi-axis data from the primary figure using established axes or gating strategies to demonstrate how results in this paper line up with established understandings. It should not be necessary to defend exactly why these may be different from established truths, although doing so may increase the impact of the study and discussion of discrepancies is an important aspect of scholarship.  

· Generally strong throughout the manuscript.  

2.   Quality: Completeness (1–3 scale) SCORE = 1.5 

· Does the collection of experiments and associated analysis of data support the proposed title- and abstract-level conclusions? Typically, the major (title- or abstract-level) conclusions are expected to be supported by at least two experimental systems.  

Within the evolutionary timescales section of the results, a concluding point is that the predicted timeframes of MRCA of C3 and C4 coincide with the construction of the Panama Canal. However, it appears that the MRCA timeframes of C1 and C2 also overlap with the construction of the Panama Canal. Also, there is no additional discussion or speculation on the implications of this finding. Explanation or justification as to why the only the MRCAs of C3 and C4 but not C1 and C2 were mentioned would be helpful. Additional discussion or speculation on the significance of finding the MRCAs coinciding with the construction of the Panama Canal would strengthen the concluding the statement of this section.

The conclusions made regarding the AMR data and genes found on plasmids and the implications for how these genes are being acquired was quite convincing. In comparison, the conclusions from the invasiveness index are less convincing (see comment on Fig S3 above and comment below). As such, by putting more emphasis on the AMR data and a little less on the invasiveness index would strengthen the paper.

· Are there experiments or analyses that have not been performed but if ‘‘true’’ would disprove the conclusion (sometimes considered a fatal flaw in the study)? In some cases, a reviewer may propose an alternative conclusion and abstract that is clearly defensible with the experiments as presented, and one solution to ‘‘completeness’’ here should always be to temper an abstract or remove a conclusion and to discuss this alternative in the discussion section.   

· N/A

3. Quality: Reproducibility (1–3 scale) SCORE = 1 

· Figure by figure, were experiments repeated per a standard of 3 repeats or 5 mice per cohort, etc.?  

· NA

· Is there sufficient raw data presented to assess the rigor of the analysis?  

· Yes

· Are methods for experimentation and analysis adequately outlined to permit reproducibility?  

· Yes. However, see comment on transparency of machine learning model (below).

· If a ‘‘discovery’ dataset is used, has a ‘‘validation’ cohort been assessed and/or has the issue of false discovery been addressed?  

· Yes

4. Quality: Scholarship (1–4 scale but generally not the basis for acceptance or rejection) SCORE = 1.5 

· Has the author cited and discussed the merits of the relevant data that would argue against their conclusion? 

The invasiveness index is based upon a previously published machine learning model. The reader would benefit from more information about this model (i.e. model features, criteria to make choices) to help them weigh the evidence for the findings, perhaps in the form of a table of information in the supplemental section. Experimental evidence demonstrating that nucleotide differences correspond to increased invasiveness would strengthen the section.

· Has the author cited and/or discussed the important works that are consistent with their conclusion and that a reader should be especially familiar when considering the work?  

· Yes 

· Specific (helpful) comments on grammar, diction, paper structure, or data presentation (e.g., change a graph style or color scheme) go in this section, but scores in this area should not be significant basis for decisions. 

Consistent with previous comments, dividing the AMR trends section so a new section begins when discussing the evolution and location of genes on plasmids would help the reader better understand this data and appreciate its importance. 

MORE SUBJECTIVE CRITERIA (IMPACT):  

1.   Impact: Novelty/Fundamental and Broad Interest (1–4 scale) SCORE= 2 

A score here should be accompanied by a statement delineating the most interesting and/or important conceptual finding(s), as they stand right now with the current scope of the paper. A ‘‘1’’ would be expected to be understood for the importance by a layperson but would also be of top interest (have lasting impact) on the field.]  

How big of an advance would you consider the findings to be if fully supported but not extended?  

The paper is very informative from a public health perspective, but the AMR aspect of the study is underdeveloped considering the threat of plasmid-mediated AMR globally. A greater emphasis on this aspect of the study is certainly warranted and could come at the expense of the focus on invasiveness, which was less well supported. Such a change could strengthen the paper for public health audiences. The Discussion/Perspectives section could be strengthened by including more detail regarding how to extend these findings in future studies. Addressing potential limitations to future studies (such as if there is a mouse model) would be helpful for others.

2.   Impact: Extensibility (1–4 or N/A scale) SCORE =  N/A 

Has an initial result (e.g., of a paradigm in a cell line) been extended to be shown (or implicated) to be important in a bigger scheme (e.g., in animals or in a human cohort)?  This criterion is only valuable as a scoring parameter if it is present, indicated by the N/A option if it simply doesn’t apply. The extent to which this is necessary for a result to be considered of value is important. It should be explicitly discussed by a reviewer why it would be required. What work (scope and expected time) and/or discussion would improve this score, and what would this improvement add to the conclusions of the study? Care should be taken to avoid casually suggesting experiments of great cost (e.g., ‘‘repeat a mouse-based experiment in humans’’) and difficulty that merely confirm but do not extend (see Bad Behaviors, Box 2) 

  N/A 

Competing interests

The authors declare that they have no competing interests.