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Bacterial Genome Wide Association Studies (bGWAS) and Transcriptomics Identifies Cryptic Antimicrobial Resistance Mechanisms in Acinetobacter baumannii

Bibliographic Data

ID22076642
AuthorsChandler Roe, Chandler C Roe (0000-0002-5762-7846, Northern Arizona University), Charles H D Williamson (Northern Arizona University), Adam J Vazquez (0000-0001-8625-3436, Northern Arizona University), Kristen Kyger (Northern Arizona University), Michael Valentine (Translational Genomics Research Institute), Jolene R Bowers (0000-0003-0538-6160, Translational Genomics Research Institute), Paul D Phillips (Northern Arizona University), Veronica Harrison (Translational Genomics Research Institute), Elizabeth Driebe, Elizabeth M Driebe (Translational Genomics Research Institute), David M Engelthaler (0000-0001-5945-059X, Translational Genomics Research Institute), Jason W Sahl (Northern Arizona University, corresponding author)
Year2020
Volume8
Pages451-451
Publication date2020-09-02
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2020.00451
PMID33014966
OpenAlexW3081622250
LanguageEN
Citations received1
References cited115

Antimicrobial resistance (AMR) in the nosocomial pathogen, Acinetobacter baumannii, is becoming a serious public health threat. While some mechanisms of AMR have been reported, understanding novel mechanisms of resistance is critical for identifying emerging resistance. One of the first steps in identifying novel AMR mechanisms is performing genotype/phenotype association studies. However, performing genotype/phenotype association studies is complicated by the plastic nature of the A. baumannii pan-genome. In this study, we compared the antibiograms of 12 antimicrobials associated with multiple drug families for 84 A. baumannii isolates, many isolated in Arizona, USA. in silico screening of these genomes for known AMR mechanisms failed to identify clear correlations for most drugs. We then performed a bacterial genome wide association study (bGWAS) looking for associations between all possible 21-mers; this approach generally failed to identify mechanisms that explained the resistance phenotype. In order to decrease the genomic noise associated with population stratification, we compared four phylogenetically-related pairs of isolates with differing susceptibility profiles. RNA-Sequencing (RNA-Seq) was performed on paired isolates and differentially expressed genes were identified. In these isolate pairs, we identified five different potential mechanisms, highlighting the difficulty of broad AMR surveillance in this species. To verify and validate differential expression, amplicon sequencing was performed. These results suggest that a diagnostic platform based on gene expression rather than genomics alone may be beneficial in certain surveillance efforts. The implementation of such advanced diagnostics coupled with increased AMR surveillance will potentially improve A. baumannii infection treatment and patient outcomes

Acinetobacter baumannii · Antibiotic resistance · Antibiotics · Bacteria · Biology · Computational biology · Drug resistance · Gene · Genome · Genomics · Genotype · Phenotype · Population · Pseudomonas aeruginosa · Antibiotic Resistance in Bacteria · Bacterial Identification and Susceptibility Testing · Medicine · Mycobacterium research and diagnosis · Genetics

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    Open Access•Chandler Roe, Chandler C Roe et al.•Frontiers in Public Health•2020

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  • Bacterial Genome Wide Association Studies (bGWAS) and Transcriptomics Identifies Cryptic Antimicrobial Resistance Mechanisms in Acinetobacter baumannii

    Open Access•Chandler Roe, Chandler C Roe et al.•Frontiers in Public Health•2020

Citations per year0.17
Citation span2020 - 2020 (1)
Highly citedNo

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