Comparative metabolomics with Metaboseek reveals functions of a conserved fat metabolism pathway in C. elegans.
Maximilian J HelfBennett W FoxAlexander B ArtyukhinYing K ZhangFrank C SchroederPublished in: Nature communications (2022)
Untargeted metabolomics via high-resolution mass spectrometry can reveal more than 100,000 molecular features in a single sample, many of which may represent unidentified metabolites, posing significant challenges to data analysis. We here introduce Metaboseek, an open-source analysis platform designed for untargeted comparative metabolomics and demonstrate its utility by uncovering biosynthetic functions of a conserved fat metabolism pathway, α-oxidation, using C. elegans as a model. Metaboseek integrates modules for molecular feature detection, statistics, molecular formula prediction, and fragmentation analysis, which uncovers more than 200 previously uncharacterized α-oxidation-dependent metabolites in an untargeted comparison of wildtype and α-oxidation-defective hacl-1 mutants. The identified metabolites support the predicted enzymatic function of HACL-1 and reveal that α-oxidation participates in metabolism of endogenous β-methyl-branched fatty acids and food-derived cyclopropane lipids. Our results showcase compound discovery and feature annotation at scale via untargeted comparative metabolomics applied to a conserved primary metabolic pathway and suggest a model for the metabolism of cyclopropane lipids.
Keyphrases
- mass spectrometry
- high resolution mass spectrometry
- liquid chromatography
- fatty acid
- hydrogen peroxide
- gas chromatography
- data analysis
- ultra high performance liquid chromatography
- ms ms
- tandem mass spectrometry
- transcription factor
- gas chromatography mass spectrometry
- machine learning
- adipose tissue
- high throughput
- deep learning
- high resolution
- single cell
- nitric oxide
- genome wide
- risk assessment
- gene expression
- solid phase extraction
- preterm birth
- quantum dots