|
Abstract INTRODUCTION:
Mycobacterial infections represent a global health challenge, requiring precise identification for effective treatment. Further, non-tuberculous mycobacteria (NTM) infections caused by common clinical isolates (e.g., M. avium (Mav), M. intracellulare (Min), M. kansasii (Mka), and M. abscessus (Mab)) produce symptoms similar to tuberculosis (TB) but can require distinct drug regimens, and accurate species or subspecies identifications are thus crucial for successful management.
METHODS:
To address the limitation of diagnosis of mycobacteria by long sub-culture methods, we developed a streamlined method to process culture filtrate protein (CFP) samples from MGIT growth cultures for LC-MS/MS analysis and an automated Peptide Taxonomy/Organism Checking (PEP-TORCH) pipeline approach to identify species/subspecies-specific mycobacterial peptide signatures. Through the weighted scores provided by our PEP-TORCH, we can identify and give the proportion of the co-infection cases.
RESULTS:
PEP-TORCH demonstrated 100% accuracy in identifying mycobacterial species, subspecies, and co-infections in 81 individuals suspected of mycobacterial infections, eliminating the need for a sub-solid culture procedure, the gold standard in clinical practice. A notable strength of PEP-TORCH is its ability to provide information on species and subspecies simultaneously, a process conventionally achieved sequentially. This capability significantly expedites pathogen identification. Furthermore, a targeted proteomics method was validated in 63 clinical samples using the taxa-specific peptides selected by PEP-TORCH, making them suitable as biomarkers in more clinically-friendly settings.
CONCLUSION:
Our approach, capable of simultaneous species, subspecies, and co-infection identification, surpasses clinical methods in efficiency, and saves days-weeks on culture. |
= Discovery stage. (53.14%, 2025)
= Translation stage. (22.33%, 2025)
= Clinically available. (24.53%, 2025)
