Genotype–Phenotype Links Between Aminoglycoside-Modifying Enzymes and Aminoglycoside MICs in Aminoglycoside-Resistant Klebsiella pneumoniae in a Southern Vietnam Tertiary Hospital

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

In the present research article entitled " High Prevalence of Aminoglycoside Modifying Enzyme Genes in Klebsiella pneumoniae from a Southern Vietnamese Tertiary Hospital”, the authors explore drug resistance. A study analyzed aminoglycoside-resistant Klebsiella pneumoniae isolates from a South Vietnamese hospital to link genetic profiles and phenotypic resistance. Researchers used broth microdilution and targeted qPCR for 14 Aminoglycoside-Modifying Enzyme (AME) genes and observed a high prevalence of ant (2″)-Ia (97.3%), aac(6′)-Ir (91.9%), and aac(6′)-Ib (89.8%). More details are available in the full study.
Authors should improve the manuscript accordingly. Major comments are as follows:
1.    Your results demonstrate a significant link between the specific gene aac(6′)-Ib and higher minimum inhibitory concentrations (MICs) as well as multidrug resistance. The findings should be revised to emphasize the importance of this correlation more effectively.
2.    Your results demonstrate that a Southern Vietnamese Tertiary Hospital" provides context, but ensure this geographical focus is central to your findings (e.g., if the prevalence is unique to this region).
3.    The author employed broth microdilution and qPCR techniques to analyze 14 genes. While it's not always essential to include this level of detail in the title, noting that these genetic profiles correlate with phenotypic resistance (MICs) enhances the scientific robustness of the work. Associations between antimicrobial resistance gene (AME) profiles, aminoglycoside MICs or susceptibility categories, and co-resistance to major antibiotic classes were evaluated using non-parametric tests and exact tests, applying the Benjamini–Hochberg correction. Additional details on the parameters, correlation curves, and the nature of the relationships (positive, negative, or neutral) should be included, along with a description of the statistical analysis methodology and the specific software used.
4.    The author should add the MIC value of all samples with the correction of your lead genes in value, but not in percentage
5.    The introduction is informative; however, it would greatly benefit from revisions aimed at enhancing clarity, logical flow, and focus. A more concise and structured presentation of the background, significance, research gap, and study objectives will strengthen the manuscript and help readers grasp the importance of this work more effectively.
6.    Consider breaking long, complex sentences into shorter, more digestible ones. Eliminate unnecessary repetition to make your point clearer. Additionally, aim for concise discussions that capture the essence without overwhelming the reader with unnecessary detail.
7.    The author needs to include more relevant references. The results should be clearly justified with supporting citations.
8.    The final paragraph clarifies the study design and goal but needs a clearer articulation of the novelty of the work. Specifically, what is new or unique about the significant link between the specific gene aac(6′)-Ib and higher minimum inhibitory concentrations (MICs) as well as multidrug resistance? How does this study advance beyond the existing literature?
9.    Please provide a comprehensive list of all reagents and drugs used, including their catalogue numbers and the corresponding company names.
10.    In the materials and methods section, you should add the statistical analysis at the end, as different experiments may have varying sample sizes and statistics.
11.    By addressing the minor suggestions, the authors can further enhance the quality and reproducibility of their work. While the methods are generally detailed, some specific details could be added for better reproducibility

Author Response

Reviewer 1

Comment 1

Reviewer comment:

Results show a significant link between aac(6′)-Ib and higher MICs/MDR; revise to emphasize importance more effectively.

Author response:

We thank the reviewer for this important suggestion and fully agree. In the revised manuscript, we have elevated the association between aac(6′)-Ib and increased MICs/MDR from a secondary statistical observation to a central finding of the study. Specifically, we now emphasize both the direction and magnitude of effects, including shifts in MIC distributions and associations with multidrug and co-resistance patterns. All results are presented with appropriate multiple-testing adjustments. In addition, we incorporated clinically interpretable diagnostic-performance metrics to contextualize the utility of aac(6′)-Ib for predicting amikacin resistance and high MIC thresholds.

Changes made in the manuscript:

• Abstract: Added a concise statement highlighting the association of aac(6′)-Ib (and aac(6′)-Ih_v) with higher MICs and MDR (lines 38–40, page 2).
• Results: Added a dedicated “Key genotype–phenotype signals” paragraph prioritizing aac(6′)-Ib, with explicit reporting of effect direction and effect size (lines 254–264, page 15; lines 277–287, page 18).
• Discussion: Strengthened the interpretation of aac(6′)-Ib and linked the findings to potential clinical and antimicrobial stewardship implications (lines 336–351, page 21; line 445, page 24).

 

Comment 2

Reviewer comment:

Ensure “Southern Vietnamese tertiary hospital” geographic focus is central (and clarify whether prevalence is unique to region).

Author response:

We thank the reviewer for highlighting the importance of geographic framing and fully agree. In the revised manuscript, we have strengthened the emphasis on the study setting by clearly identifying the cohort as originating from a southern Vietnamese tertiary-care hospital in both the Title and Abstract. In addition, we expanded the regional contextualization in the Discussion by comparing our prevalence estimates and genotype–phenotype associations with those reported in other geographic and healthcare settings. Importantly, we have interpreted these comparisons cautiously and avoided over-claiming regional uniqueness beyond our cohort, while discussing plausible contributors to observed differences, such as antimicrobial exposure patterns and plasmid backgrounds.

Changes made in the manuscript:

• Title/Abstract: The geographic location and tertiary-care setting are now stated prominently.

• Discussion: Added a focused paragraph comparing our findings with published reports from other regions and providing a cautious interpretation of similarities and differences (e.g., antimicrobial use practices, plasmid backgrounds).

 

Comment 3

Reviewer comment:

Add more details on parameters, correlation curves, nature of relationships, statistical methodology, and software used.

Author response:

We thank the reviewer for this helpful suggestion and agree that additional methodological detail improves transparency and reproducibility. Accordingly, we have expanded the Statistical Analysis section to more fully specify the analytic procedures, parameter settings, and software used. We now clarify that, in addition to reporting statistical significance, we emphasize effect sizes and effect direction, including median MIC differences and/or effect contrasts with corresponding 95% confidence intervals where appropriate, and that results are adjusted for multiple comparisons. We also improved the presentation of results by concisely summarizing key effects in the main text, while directing readers to the existing tables and figures for detailed distributions, correlation patterns, and

relationship curves.

Changes made in the manuscript:

• Methods (Statistical analysis): Expanded details of statistical tests, two-sided significance thresholds, multiple-testing adjustment approach, and software used (lines 174–178, page 7).
• Results: Added explicit statements on effect direction and effect size where feasible.
• Results: Streamlined the narrative and increased cross-referencing to existing tables and figures to reduce dense, table-like prose.

Comment 4

Reviewer comment:

Add MIC value of all samples with correction of lead genes in value, not percentage.

Author response:

We thank the reviewer for this constructive comment and agree that presenting MIC values, rather than percentages alone, improves interpretability. In the revised manuscript, we refocused the Results on MIC values and distributions. Specifically, we present MIC distributions for the full cohort in Figure 3 and summarize MIC values stratified by key AME markers using medians and interquartile ranges (IQRs) in Table 3. We also clarified the analytical handling of censored values (e.g., “>64”) to ensure transparency and consistency. This approach allows us to communicate MIC information for the entire cohort while avoiding an isolate-by-isolate listing in the main manuscript.

Changes made in the manuscript:

• Results/Tables: Emphasized MIC distributions in Figure 3 and medians/IQRs by gene presence in Table 3; clarified the handling of “>64” MIC values for analysis.
• Main Results/Tables: Shifted the focus from percent-only reporting to MIC-based summaries and streamlined redundant percentage descriptions.

 

Comment 5

Reviewer comment:

Introduction needs clearer structure: background → significance → gap → objectives.

Author response:

We thank the reviewer for this helpful suggestion and agree that a clearer structure strengthens the framing of the study. Accordingly, we reorganized the Introduction to follow a more explicit and logical progression: (i) the clinical problem and continued relevance of aminoglycosides, (ii) aminoglycoside-modifying enzyme (AME) mechanisms and their heterogeneity, (iii) the Vietnam-specific knowledge gap, and (iv) the study objectives and hypotheses. This restructuring reduces redundancy and clarifies the study’s significance and novelty.

Changes made in the manuscript:

• Introduction: Rewritten to follow a structured background–significance–gap–objectives sequence, with reduced redundancy and a clearer statement of novelty.

 

Comment 6

Reviewer comment:

Break long sentences; remove repetition; concise Discussion.

Author response:

We thank the reviewer for this suggestion and agree that improved readability strengthens the manuscript. Accordingly, we conducted a comprehensive readability edit across the manuscript. Long or complex sentences were shortened or split, repetitive statements were removed, and the Discussion was tightened to focus more clearly on interpretation and implications rather than restating results.

Changes made in the manuscript:

• Results: Reduced repetition of numeric summaries already presented in tables and figures.
• Discussion: Consolidated interpretive points and removed repetitive or purely definitional content.

Comment 7

Reviewer comment:

Include more relevant references; justify results with citations.

Author response:

We thank the reviewer for this comment and agree that stronger citation support improves the rigor of the manuscript. In the revised version, we have systematically expanded the Introduction and Discussion to anchor our findings more firmly in the existing literature. Specifically, we added references that (i) document reported variation in AME prevalence across geographic regions and healthcare settings, (ii) support previously described genotype–phenotype associations for major AMEs, including links to elevated MICs, and (iii) contextualize our observed co-resistance and MDR patterns within broader antimicrobial resistance frameworks. To maintain clarity, we preserved a descriptive Results section and concentrated interpretive citations in the Discussion, where comparisons and biological or clinical implications are addressed.

Changes made in the manuscript:

• Introduction/Discussion: Added targeted references to support key background statements, cross-study comparisons, and interpretation of genotype–phenotype and co-resistance patterns.
• Discussion: Reviewed all major interpretive claims to ensure they are explicitly supported by appropriate literature.

 

Comment 8

Reviewer comment:

Clarify novelty: what is new/unique about aac(6′)-Ib ↔ MIC/MDR in your study?

Author response:

We thank the reviewer for raising this important point and agree that the novelty required clearer articulation. In the revised manuscript, we clarify that the novelty of our study does not lie in identifying aac(6′)-Ib per se, but in the integrated genotype–phenotype framework applied. Specifically, we uniquely combine multi-gene AME profiling with broth microdilution–derived MIC distributions and clinically relevant MDR/co-resistance patterns within a southern Vietnamese tertiary-care cohort. These associations are analyzed using prespecified statistical approaches with multiple-testing correction and are further translated into clinically interpretable performance metrics for key signatures, thereby extending prior descriptive or binary resistance reports into a framework with practical diagnostic and stewardship relevance.

Changes made in the manuscript:

• End of Introduction: Added an explicit statement of novelty and refined study objectives to highlight the genotype–phenotype integration and clinical relevance.
• Start of Discussion: Added a dedicated paragraph clarifying the novel analytical framework and the value of establishing a robust local baseline for AME–MIC–MDR relationships

 

Comment 9

Reviewer comment:

Provide comprehensive list of reagents and drugs with catalogue numbers and company names.

Author response:

We thank the reviewer for this important suggestion and agree that a detailed listing of reagents is essential for reproducibility. In response, we added a comprehensive table detailing all key reagents, consumables, antimicrobials, and instruments used in the study. The table includes manufacturer names and catalogue numbers for antimicrobial agents, culture media, susceptibility testing plates, DNA extraction reagents, qPCR reagents, and major laboratory instrumentation.

Changes made in the manuscript:

• Supplementary Materials: Added a dedicated table titled “Reagents, consumables, and instruments” providing manufacturers and catalogue numbers for all key materials used in the study.

 

Comment 10

Reviewer comment:

Put statistical analysis at end of Materials and Methods.

Author response:

We thank the reviewer for this organizational suggestion and agree. The Statistical Analysis subsection has been moved to the end of the Materials and Methods section to improve structural clarity and consistency with journal conventions.

Changes made in the manuscript:

• Methods: Reordered subsections so that Statistical Analysis appears last within the Materials and Methods section (prior to Ethics, where applicable).

 

Comment 11

Reviewer comment:

Add specific methodological details for reproducibility.

Author response:

We thank the reviewer for this important comment and agree that additional methodological detail is critical for reproducibility. In response, we expanded the Materials and Methods section to provide more explicit descriptions of both MIC testing and qPCR procedures. For MIC testing, we now specify antimicrobial concentration ranges, dilution schemes, incubation conditions, reading criteria, quality-control procedures, and the analytical handling of censored MIC values. For qPCR, we clarify assay conditions, positivity thresholds, control strategies, and the handling of discordant technical replicates. Where space constraints limited detail in the main text, we added step-by-step descriptions in the Supplementary Methods.

Changes made in the manuscript:

• Methods (MIC testing): Added dilution schemes, incubation and reading criteria, quality-control measures, and handling of censored MIC values.
  • Methods (qPCR): Clarified positivity criteria, control strategy, and handling of discordant replicates.
• Supplementary Methods: Added detailed, step-by-step methodological descriptions to ensure full reproducibility.

Reviewer 2 Report

Comments and Suggestions for Authors

This retrospective analysis of a highly selected set of clinical isolates goes overboard on data presentation without establishing the fundamental premise that the multiple analyses have any predictive power, positive or negative, to effect antibiotic treatment.  While these data could be useful from an epidemiological viewpoint, it does not provide any more useful information than a traditional antibiogram for treatment selection, and from an infection control perspective, particularly in a resource limited setting. 

Specifics:

1. most importantly, must transform your statistical significance presentation to something that provides a positive or negative predictive power.
2. provide evidence that rapid diagnostic resistant gene identification can impact treatment outcomes in an acute care setting, i.e. hospitalized patient with life threatening infection. How it can be better than usual AST testing.  Identifying carbapenem resistance genes, KPC, VIM, NDM, IMP, etc. is well established but has equivocal impact on outcomes beyond AST. You are identifying ARE genes, which are not terribly specific to drug or MIC.  Correlation yes, but hard yes or no answer?
3. Far too much data presented in text when figures will do.
4. Too much data, example figure 3, in the body of the manuscript. Could be moved to supplemental data.

Comments for author File: Comments.pdf

Author Response

Reviewer 2

Comment 1

Reviewer comment:

Transform statistical significance to positive/negative predictive power.

Author response:

We thank the reviewer for this valuable suggestion and agree that clinical interpretability requires moving beyond statistical significance alone. Accordingly, we incorporated a diagnostic-performance framework to translate statistically significant associations into decision-relevant predictive measures. For selected key AME markers—most notably aac(6′)-Ib and aac(6′)-Ih_v—we now report sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratios for classifying phenotypic resistance outcomes. These metrics are presented in Supplementary Table S4 and are summarized concisely in the Results to highlight their potential clinical relevance while avoiding overinterpretation.

Changes made in the manuscript:

• Results: Added explicit statements noting that sensitivity, specificity, PPV, NPV, and likelihood ratios were evaluated for selected AME markers (see Supplementary Table S4).
• Supplementary Materials: Added Supplementary Table S4, reporting diagnostic-performance metrics for aac(6′)-Ib and aac(6′)-Ih_v.
• Discussion: Added a brief interpretive statement emphasizing the adjunctive nature of these markers and the continued need for MIC confirmation (lines 360–363, page 21).

 

Comment 2

Reviewer comment:

Provide evidence that rapid diagnostic resistance gene identification impacts outcomes; compare to usual AST; note that carbapenemase detection impact may be equivocal; AME genes not specific.

Author response:

We thank the reviewer for this important and nuanced comment and agree that the clinical impact of rapid resistance-gene diagnostics requires careful and balanced discussion. In the revised manuscript, we expanded the Discussion to reflect available evidence showing that improvements in time to effective therapy and antimicrobial optimization are most consistently achieved when rapid molecular diagnostics are coupled with active antimicrobial stewardship, rather than when used in isolation, and that effects on downstream clinical outcomes can vary by setting and implementation compared with conventional phenotypic AST. We also explicitly acknowledge that, similar to carbapenemase detection, the clinical impact of resistance-gene identification may be equivocal in some contexts. Furthermore, we clarify that AME detection is neither fully drug- nor allele-specific, and that genotype-to-phenotype inference is inherently probabilistic due to co-resistance backgrounds and alternative resistance mechanisms (including 16S rRNA methyltransferases). Accordingly, we emphasize that AME-based screening should be viewed as a complementary, interim triage tool, rather than a replacement for MIC-based phenotypic susceptibility testing.

Changes made in the manuscript:

• Discussion (clinical utility of rapid diagnostics): Added a concise summary of evidence indicating that rapid molecular diagnostics can reduce time to effective therapy when paired with antimicrobial stewardship, and positioned AME screening as an adjunct pending MIC confirmation (lines 463–468, page 26).
• Discussion (limitations of gene-only inference): Strengthened discussion of allele/substrate specificity, co-existing resistance mechanisms, and the role of 16S rRNA methyltransferases, reinforcing that MIC-based phenotypic AST remains essential.

 

Comment 3

Reviewer comment:

Too much data in text; figures will do.

Author response:

We thank the reviewer for this helpful suggestion and agree that the Results section benefited from further condensation. Accordingly, we substantially streamlined the Results narrative, replacing extended numeric enumerations with concise summary statements and directing readers to the existing tables and figures for full quantitative detail. Figures were retained without modification, as they provide the most interpretable presentation of distributions and relationships while maintaining transparency without expanding the main text.

Changes made in the manuscript:

• Results: Replaced long numeric descriptions with brief summaries and explicit references to relevant tables and figures (lines 196–383, pages 8–22).
• Results: Removed repetition of values already presented in tables/figures and retained only key cohort-defining estimates in the narrative (lines 196–383, pages 8–22).

 

Comment 4

Reviewer comment:

Too much data (e.g., Figure 3) in body; move to supplemental.

Author response:

We thank the reviewer for this suggestion and agree with the intent to minimize data density in the main text. After careful consideration, we retained Figure 3 in the main manuscript because it displays core MIC distribution data that directly support the study’s primary conclusions and are difficult to convey adequately in text or summary statistics alone. To address concerns regarding readability, we reduced textual repetition of detailed values and strengthened cross-referencing, allowing the figure to carry the quantitative detail while keeping the Results narrative concise and focused on key messages.

Changes made in the manuscript:

• Results/Figure references: Retained Figure 3 in the main manuscript and reduced in-text duplication by summarizing only the main takeaways and directing readers to Figure 3 for full MIC distribution detail (lines 255–274, page 11).

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

 The author should revised tile "Genotype–phenotype links between aminoglycoside-modifying enzymes and aminoglycoside MICs in aminoglycoside-resistant Klebsiella pneumoniae in a southern Vietnam tertiary hospital".

Author Response

Comment 1:

The author should revised tile "Genotype–phenotype links between aminoglycoside-modifying enzymes and aminoglycoside MICs in aminoglycoside-resistant Klebsiella pneumoniae in a southern Vietnam tertiary hospital

Response to reviewer:

We fully agree with the reviewer’s comment and have revised the title in the revised manuscript. We thank the reviewer for this valuable suggestion