Professor of Metabolomics
Professor Mark Viant’s expertise lies predominantly in the field of metabolomics. His research interests span from method development in analytical chemistry and bioinformatics through to the application of metabolomics to both human and environmental toxicology, focusing extensively on finding novel solutions for industry and regulators in chemical safety science.
2017 – 2021 NERC iCASE with Thermo Fisher Scientific
Ultrahigh sensitivity metabolomics: using mass spectrometry to open a window into discovering novel molecular responses to chemical toxicants
1. Develop low-flow LC-MS methods for untargeted metabolomics analyses of low biomass cell samples using in vitro toxicology.
2. Utilise these analytical methods to evaluate the effectiveness of metabolomics for biologically-driven chemical grouping and read-across (a variation on the widely used method in chemical risk assessment).
3. Evaluate the potential of metabolomics to simultaneously generate toxicokinetic information (alongside the toxicodynamics) from in vitro toxicology studies in order to further support read-across case studies.
2017 – 2021 BBSRC iCASE with Waters
Mass spectrometry imaging of the model organism Daphnia: a tool for localising molecular stress responses
1. Optimise Desorption Electrospray Ionisation (DESI) imaging mass spectrometry to study the spatial distribution of polar metabolites and lipids in small model organisms.
2. Apply DESI to build a spatial atlas of the metabolome of a model organism, focusing on Daphnia, benefitting from this species’ Deep Metabolome Annotation project in our Metabolomics & Systems Toxicology Laboratory.
3. Apply DESI in the context of Daphnia toxicology to localise the uptake, distribution and metabolism of chemical pollutants alongside measurements of changes in endogenous metabolism (spatial metabolomics).
2018 – 2022 BBSRC iCASE with AstraZeneca
Novel metabolomics strategies to understand drug-induced perturbations in cardiac microtissues
1. Optimise microtissue sample preparation for DIMS-based untargeted metabolomics analysis.
2. Characterise the metabolome of cardiac microtissues following drug (cardiotoxicant) perturbation.
3. Use data from metabolomics, and complementary techniques, to generate hypotheses on the molecular mechanisms of drug-induced cardiotoxicity.
4. Validate hypothesised modes of action using appropriate techniques.
2018 – 2022 NERC iCASE with Thermo Fisher Scientific
Developing and implementing metabolomics approaches for environmental risk assessment of chemicals
1. Establish and optimise novel high-throughput sampling and non-targeted direct infusion mass spectrometry (DIMS) metabolomics for low biomass samples.
2. Evaluate the capabilities of multi-omics and computational approaches for biologically-based chemical grouping and read-across in single and multiple OECD test species, Daphnia magna and potentially fish, studying ‘dirty’ and specific-acting chemicals.
3. Assess the potential of metabolomics to generate untargeted toxicokinetics data to further enhance robust grouping and read-across of ‘dirty’ and specific-acting chemicals.
4. Disseminate and translate findings into regulatory practice through strategic partnership and international engagement with regulatory and government bodies, including the European Chemicals Agency (ECHA), the US Environmental Protection Agency (EPA) and Health Canada.
2020-2024 BBSRC iCASE with Unilever
Integrating Mass Spectrometry and Bioinformatics to Develop Physiology-Based Kinetic Models for Chemical Safety Science
1. Build a one-compartment toxicokinetic model using available literature data for the model species Daphnia magna (water flea).
2. Evaluate the uptake of chemicals within Daphnia magna over time, using mass spectrometry approaches and microdissection.
3. Conduct toxicokinetic studies to discover the biotransformation products of chemicals within Daphnia magna.
4. Develop a deployable physiologically based kinetic model for Daphnia magna parameterised and validated using data and knowledge derived from objectives 1-3.