Headspace Gas Monitoring of Gut Microbiota Using Targeted and Globally Optimized Targeted Secondary Electrospray Ionization Mass Spectrometry

• Published in: Analytical chemistry (Washington) Vol. 91; no. 1; pp. 854 - 863
• Main Authors: Li, Haorong, Xu, Mengyang, Zhu, Jiangjiang
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 02.01.2019
• Subjects: Analytical chemistry; Chemistry; Coefficient of variation; Culture; Discriminant analysis; Electrospraying; Gas monitoring; Green tea; Headspace; Intestinal microflora; Ionization; Mass spectrometry; Mass spectroscopy; Mathematical analysis; Metabolism; Metabolites; Metabolomics; Microbiology; Microbiota; Microorganisms; Monitoring; Reproducibility; Spectroscopy; Variance analysis
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.8b03517

This study aimed to develop and incorporate a secondary electrospray ionization (SESI) setup in combination with both targeted tandem mass spectrometry (MS/MS) and a hybrid metabolomics technique, globally optimized targeted mass spectrometry (GOT-MS), to sensitively detect volatile metabolites from the headspace of in vitro gut microbial culture in a human colonic model (HCM). Two SESI-tandem mass spectrometry panels with a comparable number of targeted metabolites/features (77 compounds in the targeted SESI-MS/MS panel and 75 features in the SESI-GOT-MS/MS panel) were established. The analytical performance of the SESI-GOT-MS/MS method, as well as its biological capability, were examined and compared with the targeted SESI-MS/MS method. As a result, the SESI-GOT-MS/MS method detected a similar number of metabolic features with good reproducibility (coefficient of variation <10%) compared to the targeted SESI-MS/MS method. Both methods showed a comparable ability to differentiate the gut microbial culture with or without the addition of green tea extract (GTE) to a HCM. The results from analysis of variance (ANOVA) showed that similar numbers of compounds from targeted SESI-MS/MS and metabolic features from SESI-GOT-MS/MS have significant differences when comparing samples collected from different HCM treatment stages. Partial least-squares discriminant analysis (PLS-DA) indicated that both methods could clearly differentiate the stages of GTE treatment. In summary, we demonstrated that SESI-MS/MS in combination with either targeted or GOT approaches can be a useful tool for monitoring gut microbial metabolism and their response to perturbations.