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Abstract Introduction
In recent years, microbiome research has dramatically reshaped our understanding of how symbiotic microbes impact on a multitude of (patho-)physiological processes in the host. However, causal links are still lacking to a large extent. Metabolomics allows the investigation of microbial metabolic activities, and is thus the ideal technology to assess functional nutrition-microbiota-host crosstalk. Here, we discuss the application of a newly developed standardized targeted assay for the quantification of endogenous and microbiota-derived metabolites covering central metabolic pathways.
Methods
Human EDTA plasma and fecal homogenate were analyzed by using a standardized, quantitative assay in kit format allowing for the multiplexed analysis of 630 metabolites by mass spectrometry. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was employed for the analysis of 106 small molecules from 13 compound classes, whereas flow-injection analysis tandem mass spectrometry (FIA-MS/MS) was employed for the analysis of hexoses and 523 lipids from 12 lipid classes. A sample volume of 10 µL were used per well on a 96-well plate, preloaded with internal standards. After derivatization and extraction, LC-MS/MS and FIA-MS/MS analyses were performed (Agilent 1290 Infinity UHPLC – SCIEX QTRAP® 5500). MetIDQ™ software was used for the entire automated workflow, from sample registration to quality-controlled, quantitative results.
Results
In plasma, more than 455 metabolites were quantified above LOD with high precision, and more than 120 metabolites in fecal samples. To a large extent, the small molecules and lipids quantified in feces overlap with those in plasma. A higher number of lipids, especially phosphatidylcholines and triglycerides, were quantified in plasma compared to fecal samples. In addition to endogenous metabolites, a multitude of microbiota-derived metabolites were quantified.
Conclusion
The capability to quantify microbiota-derived metabolites in blood and fecal samples allows for correlation studies also with data from other omics technologies to investigate functional nutrition-microbiome-host interplay for uncovering causal links to pathophysiological processes, disease development, and response to drug treatment. |
= Discovery stage.
= Translation stage.
= Clinically available.
