Exploring drug resistance genes in Acinetobacter baumannii using metagenomic next-generation sequencing
Year: 2025
Type: article
Abstract: Introduction: With the rising incidence of infectious diseases, the overuse of antibiotics has become a serious problem in clinical practice. In recent years, metagenomic next-generation sequencing (mNGS) has emerged as a promising alternative, offering advantages such as rapid turnaround, broad-spectrum detection, and comprehensive coverage. However, its clinical utility for antimicrobial resistance testing remains to be fully established. Methods: In this study, we evaluated the effectiveness of mNGS in detecting antimicrobial resistance in Acinetobacter baumannii using 53 clinical samples. The performance of mNGS was compared with conventional culture-based methods. In addition, clinical judgment of drug resistance was used as a reference to assess concordance between sequencing results and patient treatment. Results: Metagenomic sequencing produced an average of 8.4 × 10⁷ reads per sample and identified 61 resistance loci-20 of which appeared in at least five isolates. Among the A. baumannii-positive samples, class-specific accuracy of mNGS exceeded 80% for β-lactams, aminoglycosides, quinolones, and minocycline, underscoring its strong performance in comprehensive resistome profiling. We further investigated resistance-associated genes in A. baumannii that appeared with high frequency, including enzymatic inactivation mechanisms (ADC-type cephalosporinases and OXA-type oxacillinases), efflux systems (AbaQ, AbeM), and RND-type efflux pumps (adeIJK/adeN and adeFGH/adeL). Discussion: Our findings demonstrate a high concordance between mNGS results, culture-based methods, and clinical evaluations, highlighting the potential of mNGS as a reliable tool for assessing antimicrobial resistance in
Source: Frontiers in Microbiology
Authors: Guiqiu Li, Jianxing Lao, Yixiong Jiang, Pei Tang, Hui Huang, Lijuan He, Ke Yuan, Xiulan Lai
Institutions: Shenzhen University, BGI Group (China)
Language: English
Subfield: Molecular Medicine
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4414972474
