Pratchakan Chaiyachat: Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Benjawan Kaewseekhao: Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Angkana Chaiprasert: Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Phalin Kamolwat: Bureau of Tuberculosis, Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand.
Ditthawat Nonghanphithak: Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Jutarop Phetcharaburanin: Department of Systems Biosciences and Computational Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Auttawit Sirichoat: Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Rick Twee-Hee Ong: Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
Kiatichai Faksri: Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand. kiatichai@kku.ac.th.
The detection of pre-extensively (pre-XDR) and extensively drug-resistant tuberculosis (XDR-TB) is challenging. Drug-susceptibility tests for some anti-TB drugs, especially ethambutol (ETH) and ethionamide (ETO), are problematic due to overlapping thresholds to differentiate between susceptible and resistant phenotypes. We aimed to identify possible metabolomic markers to detect Mycobacterium tuberculosis (Mtb) strains causing pre-XDR and XDR-TB. The metabolic patterns of ETH- and ETO-resistant Mtb isolates were also investigated. Metabolomics of 150 Mtb isolates (54 pre-XDR, 63 XDR-TB and 33 pan-susceptible; pan-S) were investigated. Metabolomics of ETH and ETO phenotypically resistant subgroups were analyzed using UHPLC-ESI-QTOF-MS/MS. Orthogonal partial least-squares discriminant analysis revealed distinct separation in all pairwise comparisons among groups. Two metabolites (meso-hydroxyheme and itaconic anhydride) were able to differentiate the pre-XDR and XDR-TB groups from the pan-S group with 100% sensitivity and 100% specificity. In comparisons of the ETH and ETO phenotypically resistant subsets, sets of increased (ETH = 15, ETO = 7) and decreased (ETH = 1, ETO = 6) metabolites specific for the resistance phenotype of each drug were found. We demonstrated the potential for metabolomics of Mtb to differentiate among types of DR-TB as well as between isolates that were phenotypically resistant to ETO and ETH. Thus, metabolomics might be further applied for DR-TB diagnosis and patient management.
