Team Members & Projects

Team Leader

Mark Viant

Mark Viant

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.

Postdoctoral Fellows

Tom Lawson

Tom Lawson

Wellcome Trust (grant no. 202952/C/16/Z)

MetaboFlow – the development of standardised workflows for processing metabolomics data to aid reproducible data sharing and big data initiatives

The MetaboFlow project seeks to address an urgent need within the metabolomics research community for reproducible and scalable metabolomics data analysis workflows.

1. Working with collaborators from institutions in the UK and Europe, we aim to integrate a wide range of existing and novel metabolomics data processing algorithms, feature extraction and metabolite identification tools into this open-source and cloud-based Galaxy research platform. This will enable data analyses to be conducted within a highly structured framework, ensuring that all stages of a given workflow, including the inputs, outputs and parameters applied, are recorded. Users will also be able to easily share all, or parts, of an analysis history with chosen collaborators, making reproducible and open metabolomics research both viable and simple.

2. To provide training and outreach in MetaboFlow.

PhD Students

Julia Malinowska

Julia Malinowska

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.

Matthew Smith

Matthew Smith

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).

Tara Bowen

Tara Bowen

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.

Hanna Gruszczynska

Hanna Gruszczynska

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.