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A metabolomic and multivariate statistical process to assess the effects of genotoxins in Saccharomyces cerevisiae
journal contribution
posted on 2023-06-08, 00:30 authored by Christopher M Titman, Jessica A Downs, Stephen G Oliver, Paul L Carmichael, Andrew D Scott, Julian L GriffinThere is an increased need to develop robust cellular model systems which could replace or reduce the need for animals in toxicological testing. Current in vitro strategies for genotoxicity testing suffer from a high irrelevant positive rate, requiring the need for the development of new in vitro tools. Saccharomyces cerevisiae is used widely to study DNA damage and repair, and a high-throughput green fluorescent protein based assay has been developed to detect genotoxic-induced DNA damage. In this study a combined high resolution H-1 NMR spectroscopy and gas chromatography mass spectrometry based metabolomic approach has been used to monitor and distinguish different genotoxic compounds from other types of toxic lesion using the multivariate classification tool partial least squares-discriminate analysis (PLS-DA). The metabolic profiles of extracts of yeast (W303 alpha strain) readily distinguished the individual toxins from control cells across 22 different treatments. In addition, these metabolic profiles also demonstrated dose and time responses for selected compounds (methyl methane sulfonate and nocodazole). Finally, predictive models were built for distinguishing the genotoxic carcinogens from the control group according to the metabolic profile of the cell culture media.
History
Publication status
- Published
Journal
Molecular BioSystemsISSN
1742-206XPublisher
Royal Society of ChemistryExternal DOI
Issue
12Volume
5Page range
1913-1924Department affiliated with
- Sussex Centre for Genome Damage Stability Publications
Full text available
- No
Peer reviewed?
- Yes