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Abstract
Microbiotas are a malleable part of ecosystems, including the human ecosystem. Microorganisms affect not only the chemistry of their specific niche, such as the human gut, but also the chemistry of distant environments, such as other parts of the body. Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota, and to understand the functional role of these microbial metabolites. This Review provides a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis. Data analysis remains an obstacle; therefore, the emphasis is placed on data analysis approaches and integrative analysis, including the integration of microbiome sequencing data.
Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota and to understand the functional role of these microbial metabolites. In this Review, Dorrestein and colleagues review common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis.
Details
; Mannochio-Russo Helena 2
; Costa-Lotufo, Letícia V 3
; Jarmusch, Alan K 4 ; Dorrestein, Pieter C 5 1 Universidade de São Paulo, Institute of Biomedical Science, São Paulo, Brazil (GRID:grid.11899.38) (ISNI:0000 0004 1937 0722); University of California, San Diego, Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)
2 University of California, San Diego, Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); São Paulo State University, Department of Biochemistry and Organic Chemistry, Institute of Chemistry, Araraquara, Brazil (GRID:grid.410543.7) (ISNI:0000 0001 2188 478X)
3 Universidade de São Paulo, Institute of Biomedical Science, São Paulo, Brazil (GRID:grid.11899.38) (ISNI:0000 0004 1937 0722)
4 University of California, San Diego, Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)
5 University of California, San Diego, Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California, San Diego, Department of Pediatrics, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242); University of California, San Diego, Center for Microbiome Innovation, San Diego, USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)





