Metabolome analysis for investigating host-gut microbiota interactions

• Published in: Journal of the Formosan Medical Association Vol. 118; pp. S10 - S22
• Main Authors: Chen, Michael X., Wang, San-Yuan, Kuo, Ching-Hua, Tsai, I-Lin
• Format: Journal Article
• Language: English
• Published: Singapore Elsevier B.V 01.03.2019; Elsevier
• Subjects: Data processing; Gut microbiota; Mass spectrometry; Metabolomics; Sample collection; Gut microbiota; Metabolomics; Sample collection; Data processing; Mass spectrometry
• ISSN: 0929-6646; 1876-0821
• DOI: 10.1016/j.jfma.2018.09.007

Dysbiosis of the gut microbiome is associated with host health conditions. Many diseases have shown to have correlations with imbalanced microbiota, including obesity, inflammatory bowel disease, cancer, and even neurodegeneration disorders. Metabolomics studies targeting small molecule metabolites that impact the host metabolome and their biochemical functions have shown promise for studying host-gut microbiota interactions. Metabolome analysis determines the metabolites being discussed for their biological implications in host-gut microbiota interactions. To facilitate understanding the critical aspects of metabolome analysis, this article reviewed (1) the sample types used in host-gut microbiome studies; (2) mass spectrometry (MS)-based analytical methods and (3) useful tools for MS-based data processing/analysis. In addition to the most frequently used sample type, feces, we also discussed others biosamples, such as urine, plasma/serum, saliva, cerebrospinal fluid, exhaled breaths, and tissues, to better understand gut metabolite systemic effects on the whole organism. Gas chromatography-mass spectrometry (GC–MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), three powerful tools that can be utilized to study host-gut microbiota interactions, are included with examples of their applications. After obtaining big data from MS-based instruments, noise removal, peak detection, missing value imputation, and data analysis are all important steps for acquiring valid results in host-gut microbiome research. The information provided in this review will help new researchers aiming to join this field by providing a global view of the analytical aspects involved in gut microbiota-related metabolomics studies.