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Metabolomics and lipidomics in Caenorhabditis elegans using a single-sample preparation

Authors :
Michel van Weeghel
Frédéric M. Vaz
Mia L. Pras-Raves
Martin A. T. Vervaart
Jan E. Kammenga
Angela C. M. Luyf
Reuben L. Smith
Bauke V. Schomakers
Arwen W. Gao
Mark G. Sterken
Antoine H C van Kampen
Riekelt H. Houtkooper
Marte Molenaars
Hyung L. Elfrink
Georges E. Janssens
Laboratory Genetic Metabolic Diseases
Amsterdam Gastroenterology Endocrinology Metabolism
APH - Methodology
Epidemiology and Data Science
APH - Personalized Medicine
Laboratory for General Clinical Chemistry
ACS - Diabetes & metabolism
ACS - Heart failure & arrhythmias
Source :
Disease models & mechanisms, 14(4):dmm.047746. Company of Biologists Ltd, Disease Models & Mechanisms, article-version (VoR) Version of Record, Disease Models & Mechanisms 14 (2021) 4, Disease Models & Mechanisms, 14(4)
Publication Year :
2021

Abstract

Comprehensive metabolomic and lipidomic mass spectrometry methods are in increasing demand; for instance, in research related to nutrition and aging. The nematode Caenorhabditis elegans is a key model organism in these fields, owing to the large repository of available C. elegans mutants and their convenient natural lifespan. Here, we describe a robust and sensitive analytical method for the semi-quantitative analysis of >100 polar (metabolomics) and >1000 apolar (lipidomics) metabolites in C. elegans, using a single-sample preparation. Our method is capable of reliably detecting a wide variety of biologically relevant metabolic aberrations in, for example, glycolysis and the tricarboxylic acid cycle, pyrimidine metabolism and complex lipid biosynthesis. In conclusion, we provide a powerful analytical tool that maximizes metabolic data yield from a single sample. This article has an associated First Person interview with the joint first authors of the paper.<br />Summary: We describe an integrated metabolomics and lipidomics method for analyzing metabolites in C. elegans using a single-sample preparation, which provides a robust way of obtaining comprehensive, high-quality metabolic data from biological samples.

Details

Language :
English
ISSN :
17548403 and 17548411
Database :
OpenAIRE
Journal :
Disease models & mechanisms, 14(4):dmm.047746. Company of Biologists Ltd, Disease Models & Mechanisms, article-version (VoR) Version of Record, Disease Models & Mechanisms 14 (2021) 4, Disease Models & Mechanisms, 14(4)
Accession number :
edsair.doi.dedup.....be939dab8bd914eaeca1e4a5e09203b6