Genomic heterogeneity and lineage-specific beta-lactamases in recurrent Achromobacter bloodstream infection patients
Genomic heterogeneity and lineage-specific beta-lactamases in recurrent Achromobacter bloodstream infection patients

Genomic heterogeneity and lineage-specific beta-lactamases in recurrent Achromobacter bloodstream infection patients

Emerg Microbes Infect. 2025 Dec;14(1):2547721. doi: 10.1080/22221751.2025.2547721. Epub 2025 Aug 26.

ABSTRACT

Recurrent Achromobacter infections pose significant clinical challenges due to antimicrobial resistance and within-host evolution. This study investigates the genetic and phenotypic changes among Achromobacter isolates using next-generation sequencing. We retrospectively analyzed 65 Achromobacter infection cases at a tertiary hospital in Taiwan from 2016 to 2023. Whole-genome sequencing of 12 isolates from patients with recurrent bloodstream infections was performed using Oxford Nanopore Technology. Resistance genes and beta-lactamases were identified, and genome similarity was assessed using average nucleotide identity (ANI) for phylogenetic analysis. Recurrent infections were significantly associated with bloodstream and urinary tract infections (p < 0.01). Whole-genome sequencing improved species identification over matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS), leading to the discovery of a novel Achromobacter species and the first identification of A. insuavis as a bacteraemia pathogen. Beta-lactamases grouped according to phylogenetic clades, indicating lineage-specific resistance patterns. Missense mutations in genes such as siaT, rapA, atzEa1, AL523_09115, and clpA correlated with changes in antimicrobial resistance profiles, suggesting in vivo evolution during recurrent infections. This study enhances understanding of Achromobacter genomic heterogeneity and underscores the importance of whole-genome sequencing for accurate species identification and resistance detection. The findings highlight the need for larger-scale studies to monitor emerging variants and assess their clinical impact.

PMID:40857070 | DOI:10.1080/22221751.2025.2547721