4.6 Article

High-Throughput UHPLC-MS to Screen Metabolites in Feces for Gut Metabolic Health

Journal

METABOLITES
Volume 12, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/metabo12030211

Keywords

bile acids; fecal metabolomics; gut-liver axis; targeted metabolomics; sample preparation

Funding

  1. European Union's Horizon 2020 research and innovation programme [668031]
  2. Novo Nordisk Foundation through Challenge Grant MicrobLiver [NNF15OC0016692]
  3. H2020 Societal Challenges Programme [668031] Funding Source: H2020 Societal Challenges Programme

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Feces, the byproduct of our diet, has been linked to gut diseases and metabolic disorders. To analyze metabolites in fecal samples efficiently, we developed a novel sample preparation method that allows for the detection of both polar and non-polar metabolites. By using this method, we analyzed 475 fecal samples from patients with liver disease and healthy controls, and found reproducibility and coverage of 28 metabolites.
Feces are the product of our diets and have been linked to diseases of the gut, including Chron's disease and metabolic diseases such as diabetes. For screening metabolites in heterogeneous samples such as feces, it is necessary to use fast and reproducible analytical methods that maximize metabolite detection. As sample preparation is crucial to obtain high quality data in MS-based clinical metabolomics, we developed a novel, efficient and robust method for preparing fecal samples for analysis with a focus in reducing aliquoting and detecting both polar and non-polar metabolites. Fecal samples (n = 475) from patients with alcohol-related liver disease and healthy controls were prepared according to the proposed method and analyzed in an UHPLC-QQQ targeted platform in order to obtain a quantitative profile of compounds that impact liver-gut axis metabolism. MS analyses of the prepared fecal samples have shown reproducibility and coverage of n = 28 metabolites, mostly comprising bile acids and amino acids. We report metabolite-wise relative standard deviation (RSD) in quality control samples, inter-day repeatability, LOD (limit of detection), LOQ (limit of quantification), range of linearity and method recovery. The average concentrations for 135 healthy participants are reported here for clinical applications. Our high-throughput method provides a novel tool for investigating gut-liver axis metabolism in liver-related diseases using a noninvasive collected sample.

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