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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 Griffin
There 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 BioSystems

ISSN

1742-206X

Publisher

Royal Society of Chemistry

Issue

12

Volume

5

Page range

1913-1924

Department affiliated with

  • Sussex Centre for Genome Damage Stability Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

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