Genomic analysis of a clinical Mycolicibacterium houstonense isolate reveals dual escalation in adaptability and virulence

Mycolicibacterium houstonense is prone to being misidentified as other mycobacteria, particularly M. fortuitum. This study characterized the genome of a clinical M. houstonense isolate and delineated its phylogenetic relationship with M. fortuitum to provide a basis for accurate diagnosis and management of infections caused by this species. Genome sequencing was used to determine the taxonomic status, virulence profile, and resistance traits of the clinical isolate, while comparative genomics was employed to delineate its evolutionary relationship with M. fortuitum. The clinical isolate was definitively identified as M. houstonense. Genomic analysis revealed a unique repertoire of virulence and resistance genes. Its genome harbors 590 virulence genes, many of which encode T7SS effectors. In addition to resistance genes commonly found in nontuberculous mycobacteria, it also carries M. tuberculosis-related resistance determinants, enhancing its resilience to disinfectants, antiseptics, and antimicrobials commonly used in clinical settings. Phylogenomic analysis indicates that M. houstonense and M. fortuitum drive reciprocal divergence, reinforcing their environmental adaptability. Genomic analysis is poised to serve as a robust tool for the identification of M. houstonense. The clinical isolate in our study suggests a potential dual escalation of M. houstonense in adaptability and virulence, underscoring the need for stricter clinical monitoring and environmental surveillance.

Authors

Institutions

Publication Details

Journal
BMC Microbiology
Published
2025-12-20
DOI
https://doi.org/10.1186/s12866-025-04637-6
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genomic analysis of a clinical Mycolicibacterium houstonense isolate reveals dual escalation in adaptability and virulence

Zhenghao Wu, Ying Sheng, Ning Pan, Yimai Deng et al.
BMC Microbiology
Mycobacterium research and diagnosis
article

Genomic analysis of a clinical Mycolicibacterium houstonense isolate reveals dual escalation in adaptability and virulence

Zhenghao Wu, Ying Sheng, Ning Pan, Yimai Deng, Bibo Zhang, Ailing Xu, Shuyan Wu, Xuan Liu
article en

Abstract

Mycolicibacterium houstonense is prone to being misidentified as other mycobacteria, particularly M. fortuitum. This study characterized the genome of a clinical M. houstonense isolate and delineated its phylogenetic relationship with M. fortuitum to provide a basis for accurate diagnosis and management of infections caused by this species. Genome sequencing was used to determine the taxonomic status, virulence profile, and resistance traits of the clinical isolate, while comparative genomics was employed to delineate its evolutionary relationship with M. fortuitum. The clinical isolate was definitively identified as M. houstonense. Genomic analysis revealed a unique repertoire of virulence and resistance genes. Its genome harbors 590 virulence genes, many of which encode T7SS effectors. In addition to resistance genes commonly found in nontuberculous mycobacteria, it also carries M. tuberculosis-related resistance determinants, enhancing its resilience to disinfectants, antiseptics, and antimicrobials commonly used in clinical settings. Phylogenomic analysis indicates that M. houstonense and M. fortuitum drive reciprocal divergence, reinforcing their environmental adaptability. Genomic analysis is poised to serve as a robust tool for the identification of M. houstonense. The clinical isolate in our study suggests a potential dual escalation of M. houstonense in adaptability and virulence, underscoring the need for stricter clinical monitoring and environmental surveillance.

BMC MicrobiologyVol. 26(1)
Suzhou University of Technology (CN), Soochow University (CN), Changshu No.1 People's Hospital (CN)
Openalex Percentile: Top 47%
Mycobacterium research and diagnosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.