Genomic Determinants of Pathogenicity and Antimicrobial Resistance of Nosocomial Acinetobacter baumannii Clinical Isolates of Hospitalized Patients (2019–2021) from a Sentinel Hospital in Hangzhou, China

Abstract

Purpose Acinetobacter baumannii ( A. baumannii or AB) is one of the most opportunistic, nosocomial pathogens threatening public healthcare across countries. A. baumannii has become a primary growing concern due to its exceptional ability to acquire antimicrobial resistance (AMR) to multiple antimicrobial agents which is increasingly reported and more prevalent every year. Therefore, there is an urgent need to evaluate the AMR knowledge of A. baumannii for effective clinical treatment of nosocomial infections. This study aimed to investigate the clinical distribution AMR phenotypes and genotypes, and genomic characteristics of A. baumannii isolates recovered from hospitalized patients of different clinical departments of a sentinel hospital to improve clinical practices. Methods A total of 123 clinical isolates were recovered from hospitalized patients of different clinical departments during 2019–2021 to analyze AMR patterns, and further subjected to whole-genome sequencing (WGS) investigations. Multi-locus sequence typing (MLST), as well as the presence of antimicrobial-resistant genes (ARGs), virulence factor genes (VFGs) and insertion sequences (ISs) were also investigated from WGS data. Results The results highlighted that A. baumannii clinical isolates had shown a high AMR rate, particularly from the intensive care unit (ICU), towards routinely used antimicrobials, ie, β-lactams and fluoroquinolones. ST2 was the most prevalent ST in the clinical isolates, it was strongly associated to the resistance of cephalosporins and carbapenems, with bla OXA-23 and bla OXA-66 being the most frequent determinants; moreover, high carrier rate of VFGs was also observed such as all strains containing the ompA, adeF, pgaC, lpsB , and bfmR genes. Conclusion Acinetobacter baumannii clinical isolates are mostly ST2 with high rates of drug resistance and carrier of virulence factors. Therefore, it requires measurements to control its transmission and infection.

Machine learning and feature extraction for rapid antimicrobial resistance prediction of Acinetobacter baumannii from whole-genome sequencing data

“…However, ST2 was still the most abundant (84/120, 70.0%), which is in line with previous studies that show that ST2 is widely spread globally and represents the predominant clone of MDR A. baumannii ( Hamidian and Nigro, 2019 ; Li et al, 2023 ). This is especially true for China, where ST2 affects a high proportion of hospitalised patients and contributes to significant mortality rates ( Yu et al, 2021 ; Liu et al, 2022 ; Wei et al, 2023 ). Specimen collection, sampling location, accession number, and other details of all 459 isolates can be found in Supplementary Table S2 .…”

“…com. 10.3389/fmicb.2023.1320312 Frontiers in Microbiology 05 frontiersin.org hospitalised patients and contributes to significant mortality rates (Yu et al, 2021;Liu et al, 2022;Wei et al, 2023). Specimen collection, sampling location, accession number, and other details of all 459 isolates can be found in Supplementary Table S2.…”