Metabolic profiles of multidrug resistant and extensively drug resistant Mycobacterium tuberculosis unveiled by metabolomics. (January 2021)

• Record Type: Journal Article
• Authors: Rêgo, Amanda Mendes; Alves da Silva, Duanne; Ferreira, Nicole Victor; de Pina, Lucindo Cardoso; Evaristo, Joseph A.M.; Caprini Evaristo, Geisa P.; Nogueira, Fabio Cesar S.; Ochs, Soraya M.; Amaral, Julio J.; Ferreira, Rosana B.R.; Antunes, L. Caetano M.
• Is Part Of: Tuberculosis. Volume 126(2020)
• Publication Date: 2021-01
• Subjects: Drug resistance -- Mycobacterium tuberculosis -- Metabolic profile -- Metabolomics; 616.995
• DOI: 10.1016/j.tube.2020.102043
• Languages: English
• ISSNs: 1472-9792

Abstract

Abstract: Although treatable with antibiotics, tuberculosis is a leading cause of death. Mycobacterium tuberculosis antibiotic resistance is becoming increasingly common and disease control is challenging. Conventional drug susceptibility testing takes weeks to produce results, and treatment is often initiated empirically. Therefore, new methods to determine drug susceptibility profiles are urgent. Here, we used mass-spectrometry-based metabolomics to characterize the metabolic landscape of drug-susceptible (DS), multidrug-resistant (MDR) and extensively drug-resistant (XDR) M. tuberculosis . Direct infusion mass spectrometry data showed that DS, MDR, and XDR strains have distinct metabolic profiles, which can be used to predict drug susceptibility and resistance. This was later confirmed by Ultra-High-Performance Liquid Chromatography and High-Resolution Mass Spectrometry, where we found that levels of ions presumptively identified as isoleucine, proline, hercynine, betaine, and pantothenic acid varied significantly between strains with different drug susceptibility profiles. We then confirmed the identification of proline and isoleucine and determined their absolute concentrations in bacterial extracts, and found significantly higher levels of these amino acids in DS strains, as compared to drug-resistant strains (combined MDR and XDR strains). Our results advance the current understanding of the effect of drug resistance on bacterial metabolism and open avenues for the detection of drug resistance biomarkers.