Leveraging open cheminformatics tools for non-targeted metabolomics analysis of C. elegans: a workflow comparison and application to strains related to xenobiotic metabolism and neurodegeneration.

Abstract

Caenorhabditis elegans (C. elegans) is a well-established nematode model for studying metabolism and neurodegenerative disorders, such as Alzheimer's (AD) and Parkinson's disease (PD). Non-targeted metabolomics via liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has proven useful for uncovering metabolic changes in biological systems. Here, we present workflows for C. elegans metabolomics, leveraging advanced open science tools. We compared two metabolite extraction methods: a monophasic extraction, which provided broader metabolite coverage in analyses conducted in hydrophilic interaction with positive polarity (HILIC POS), and a biphasic extraction, which yielded more features in reverse-phase C18 chromatography with negative polarity (RPLC NEG) analyses. Data were processed using patRoon, integrating IPO, XCMS, CAMERA, and MetFrag, which incorporated PubChemLite compounds and C. elegans-specific metabolites from an expanded WormJam database enhanced with PubChem and literature sources. MS-DIAL was also employed for data processing, allowing for expanded annotations with predicted spectra for the expanded WormJam metabolites calculated using CFM-ID. Significant metabolite differences were identified when comparing the Bristol (N2) wild-type strain with two knockout strains of xenobiotic-metabolizing enzymes and two transgenic strains related to neurodegenerative pathways. Pooled quality control (QC) samples for each strain ensured robust data quality and the detection of strain-related metabolites. Our study demonstrates the potential of non-targeted metabolomics for metabolite discovery employing open science tools in model organisms.