Identifying nontuberculous mycobacteria from a mycobacteria growth indicator tube with nuclear magnetic resonance spectroscopy: A laboratory metabolomics analysis case report

Abstract

Background: Nuclear magnetic resonance (NMR) spectroscopy-based metabolomics profiling has emerged as a promising approach for identifying tuberculosis (TB) biomarkers in urine. This method offers potential in discriminating between samples with varied biological compositions, aiding in the identification of diagnostic markers for respiratory tract infections. However, direct identification of nontuberculous mycobacteria (NTM) from liquid cultures without subculturing on solid media faces challenges, particularly with existing proteomic diagnostics like matrix-assisted laser desorption ionization–time-of-flight mass spectrometry. Common techniques such as DNA-DNA reverse hybridization (line probe assays) also struggle to discriminate between NTM mixture patterns and have a limited spectrum of NTM that can be identified. Thus, there is a need to characterize NTM metabolic fingerprints in complex liquid broths to facilitate rapid identification without subculturing. Description: Mycobacterium gordonae was cultured at the National Health Laboratory Services Greenpoint TB-laboratory in South Africa, using Löwenstein–Jensen (LJ) media slants. After confirming the species through Sanger sequencing, NTM bacilli were collected, homogenized, and inoculated into Mycobacteria Growth Indicator Tubes (MGIT) containing BD MGIT™ PANTA™ antimicrobial mixture. NMR spectroscopy was conducted at the Department of Chemistry, University of Cape Town, Cape Town, South Africa. Supernatant samples underwent NMR data acquisition using standard Bruker pulse sequences on a Bruker Avance III 600 MHz NMR spectrometer. Discussion: NMR offers low sensitivity initially, but this can be enhanced with higher field strength, cryo- and microprobes, and dynamic nuclear polarization. It provides minimal sample preparation, allows for nondestructive analysis, and exhibits very high reproducibility. NMR can detect all metabolites with an NMR concentration level in one measurement and is suitable for in vivo studies, especially for 1H magnetic resonance spectroscopy. In this regard, NMR could potentially be used to detect the metabolomics profiles of a wide NTM spectrum, including NTM mixtures. To the authors' knowledge, this is the first report that attempts to utilize NMR to identify NTM. The laboratory analysis revealed no significant differences in metabolite quantities between NTM-inoculated and control MGITs. The spectra only displayed broth components, suggesting low analyte concentrations or overshadowing by larger media signals. However, to overcome this, future studies could explore pellet lysate components or vary bacterial concentrations to assess their impact on observed metabolic profiles. Differential precipitation and column chromatography may aid in isolating metabolites from media components. Conclusion: NMR emerges as a compelling choice for NTM identification, offering nondestructive analysis, high reproducibility, and minimal sample preparation, capable of measuring multiple metabolites in a single sample. However, the complexity of MGIT broth media presents challenges for NMR-based NTM identification, necessitating optimization of sample preparation methods. Therefore, in light of the growing demand for improved NTM diagnostic tools, this laboratory case accentuates the need to contemplate innovative approaches with cutting-edge technology for NTM identification.