Journal Article Ppublish
PubMed: 42219816 DOI: 10.1155/pm/5535650
Untargeted and Targeted Liquid Chromatography-Mass Spectrometry-Based Lipidomic Profiling Revealed a Potential Biomarker Panel to Distinguish Clinical Isolates of M. tuberculosis From Nontuberculous M. kansasii.
Pulm Med 2026(1):e5535650
Authors: Meenakshi Chugh, Saif Hameed, Jitendra Singh, Zeeshan Fatima
Affiliations
- Amity Institute of Biotechnology, Amity University Haryana, Manesar, Gurugram, India, amity.edu. Amity Medical School, Amity University Haryana, Manesar, Gurugram, India, amity.edu.
- Amity Institute of Biotechnology, Amity University Haryana, Manesar, Gurugram, India, amity.edu.
- Department of Translational Medicine, All India Institute of Medical Sciences, Bhopal, India, aiims.edu.
Abstract
The rising incidence of nontuberculous mycobacteria (NTM) infections, particularly Mycobacterium kansasii (M. kansasii), and their overlapping clinical features with Mycobacterium tuberculosis (MTB) are leading to diagnostic ambiguity in tuberculosis-endemic regions. Accurate differentiation remains limited by conventional diagnostic methods, emphasizing the need for molecular- and lipid-based biomarkers. In the present era of "OMICS" sciences, herein we attempted a comprehensive analysis of MTB and M. kansasii lipid profiles to elucidate species-specific lipidomic features as potential biomarkers. Three clinical isolates each of MTB and M. kansasii were obtained from treatment-naïve patients with microbiologically confirmed pulmonary infections. Lipid profiling was performed by integrating untargeted and targeted profiling through ultraperformance liquid chromatography coupled with tandem mass spectrometry from bacilli total lipid and mycobacterial cell wall lipid extracts. Untargeted profiling exhibited a higher abundance of fatty acyls, GLs, selected GPLs (PE, PG, PI, and PA), and saccharolipids (SLs) specifically Ac2SGL in MTB, whereas M. kansasii isolates were characterized by elevated levels of GPLs like PC and LPC, polyketides, and specific SLs such as diacylated trehalose species. Targeted quantification confirmed differential expression of GL (TG and DG) and GPL (PC, PE, LPC, PI, and PS) species, supporting their diagnostic relevance. Additionally, biomarker analysis further identified five lipid species with strong discriminative potential. Collectively, these findings support the development of a robust lipidomic biomarker panel for the accurate differentiation of MTB and M. kansasii, with potential implications for improved diagnostics and targeted therapeutic strategies after further confirmation.
MeSH
Mycobacterium, Biomarkers, Tuberculosis, Therapeutics, Lung Diseases, Lipidomics, Infections, Nontuberculous Mycobacteria