DOI: 10.1128/spectrum.00130-26 ISSN: 2165-0497
Global integrative analysis of whole-genome-based predictions of antimicrobial resistance trends in five major nosocomial pathogens
Yen-Yi Liu, Li-Wen Huang, Mei-Fang Su, Bo-Ren Chen, Chih-Chieh Chen ABSTRACT
Global increases in antimicrobial resistance in key nosocomial pathogens, including
Acinetobacter baumannii
,
Enterococcus faecium
,
Klebsiella pneumoniae
,
Pseudomonas aeruginosa
, and
Staphylococcus aureus
, have severely compromised clinical efficacy and increased health-care expenditures. Although species-specific surveillance is common, large-scale analyses covering diverse geographic domains remain limited. To address this gap, we systematically analyzed more than 100,000 bacterial isolates from global databases. We leveraged whole-genome sequencing-based antibiotic resistance gene (ARG) identification from the curated 5NosoAE data set to characterize resistance fingerprints against 91 distinct antibiotics and disinfectants. We implemented a standardized high-specificity resistance fingerprint criterion based on strict ARG matching thresholds to generate standardized antibiotic resistance fingerprints to evaluate phenotypic distribution across the five aforementioned pathogens. Our findings revealed high-frequency resistance predominantly against frontline antibiotic classes such as aminoglycosides, folate pathway antagonists, and β-lactams. Specifically, we identified 209 resistance fingerprints that exhibited major co-occurrence patterns among the five nosocomial pathogens. This finding highlights the presence of shared resistance fingerprint patterns across species, suggesting that antimicrobial resistance surveillance may benefit from integrated multispecies comparative frameworks, in addition to isolated pathogen tracking. By establishing such a scalable, data-driven framework, this study provides a high-resolution framework for large-scale comparative surveillance of resistance fingerprint patterns. This framework can support evidence-based global antibiotic stewardship and the development of unified intervention strategies aimed at combating the expanding clinical resistome.
IMPORTANCE
In this study, we established a standardized, scalable framework for multinational antimicrobial resistance analysis to address a major gap in current surveillance, namely, fragmented monitoring of individual pathogens. We observed extensive co-occurrence of resistance fingerprint patterns among five major nosocomial pathogens based on large-scale genomic surveillance data. These findings highlight the value of comparative multispecies surveillance frameworks for understanding large-scale resistance pattern distributions beyond isolated strain-level observations. Overall, our framework provides a high-resolution approach for comparative resistance fingerprint surveillance, supporting evidence-based antibiotic stewardship and future large-scale monitoring efforts based on publicly available genomic data sets.