The Global Antimicrobial Resistance Trends of Staphylococcus aureus and Influencing Factors

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors wrote an article on trends in antimicrobial resistance in Staphylococcus aureus. While the premise of the study is very interesting and important, its execution raises several questions.

It is not clear why the authors used such a small sample of 1710 isolates.

There are 40000 isolates in the pathogenwatch database: https://pathogen.watch/genomes/all?genusId=1279&speciesId=1280.
Next. line 20 “The spearman correlation results indicated that human development index (HDI), antibiotic  consumption, and MGEs as positive selection pressure for S. aureus AMR could promote  the accumulation of ARGs in the genomes.”  This raises questions and perplexing issues. The correlation coefficients calculated by the authors r = 0.087, 0.159, -0.295 are not such.

Another statistical “paradox” is the use of the Mann-Whitney U test to compare ARGs across four time periods is statistically inappropriate. Replace with the Kruskal-Wallis test followed by post-hoc pairwise comparisons.

Line 44-45. Write explicitly that the data are from the USA, otherwise it is not clear what scale we are talking about. i.e. are you talking about the whole world or a single country, and if one country, which one?

Line 45-49 add reference to source.

Line 98 what is PM2.5?

Line 106 why is the sample so small?

Line 109 of the PATRICK database does not exist in 2025, now it is the part of the BV-BRC database.

Line 135 it's not the virus, it's virulence

148 the use of the Mann-Whitney U test to compare ARGs across four time periods is statistically inappropriate. Replace with the Kruskal-Wallis test followed by post-hoc pairwise comparisons.

Figure 2. The tree is hard to read. The colours merge. Fix it.  ST it's not the Unknow, it's Unknown

Line 213 it's not the virus, it's virulence

Line 287-288 You talk about what was dominant in terms of occurrence and do not explain the nature of the observed phenomena. Explain in detail what is tnpA and delta

 

Line 318 what is  AAC(6')-Ie-APH(2'')-Ia?

Line 351-390 Section 3.6. The authors build models of the influence of geography without taking into account that within large countries such as China, USA, Australia, Brazil there are significant differences in conditions from region to region. The value of this section is therefore questionable.

Line 415 it's not the Pythoy, it's Python

Please, add to supplementary files dataset with all of your genomes metadata (town, city, year isolated etc) to clarify the research

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript presents a significant contribution to our understanding of the factors influencing global trends in AMR in Staphylococcus aureus. The integration of diverse data sources and advanced analytical approaches is particularly commendable. To further strengthen the manuscript, I encourage the authors to revise the sections related to the explanation of the statistical methodology and to enhance the visualization of complex data for greater clarity. Additionally, making a more explicit connection to the clinical relevance of the findings would further highlight the study’s broader significance.
Overall, this is a highly promising and important study with substantial potential impact. With the suggested refinements, I am confident it will make an even stronger contribution to the field. Excellent work!

Comments for author File: Comments.pdf

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors The topic is highly original and relevant to the field. The integration of genomic, socio-economic, and environmental data makes this study novel and valuable. It addresses a significant gap in our understanding of how the Human Development Index (HDI), antibiotic consumption, mobile genetic elements (MGEs), and climate change may correlate with antimicrobial resistance (AMR) trends in Staphylococcus aureus. The study also offers new insights into the open pan-genome characteristics of S. aureus and the accumulation of antibiotic resistance genes (ARGs). Regarding methodology, the authors should clarify the selection of databases and filtering criteria used for identifying ARGs and MGEs. The description of climate variables should be more detailed, and the normalization of data across countries and years (especially regarding variations in sequence numbers and reporting) needs further explanation. The conclusions are generally consistent with the evidence presented; however, the authors should exercise greater caution when interpreting potential causal relationships, as the data are primarily observational. The references, tables, and figures are appropriate and support the findings effectively.

Author Response

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Reviewer 4 Report

Comments and Suggestions for Authors

This article presents a comprehensive and timely study of global trends in AMR in Staphylococcus aureus and the factors influencing it. The authors used a large genomic dataset and integrated it with epidemiological, socioeconomic, Human Development Index, and climate data to examine the drivers of AMR. The methodology is sound, and the results contribute to the understanding of this important public health issue.

Strengths:

- A large number of genomes (1710) from different countries around the world were used, ensuring broad representativeness.

- Comprehensive approach: Many potential drivers of AMR were investigated, including time trends, antibiotic consumption, Human Development Index, mobile genetic elements, and environmental factors (climate, PM2.5).

- Clear presentation: Results are well visualized with figures and tables, although some figures (e.g., phylogenetic tree) are quite complex.

Weaknesses: Data limitations. Genome sampling bias. The analysis is based on publicly available genomes, which may have geographical (e.g., US, Australia) and temporal biases.

Author Response

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Author Response File: Author Response.docx