Mark ViantProfessor 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.
Project: MetaboFlow - the development of standardised workflows for processing metabolomics data to aid reproducible data sharing and big data initiatives
Funder: Wellcome Trust (grant no. 202952/C/16/Z)
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.
Project: Phenome and Metabolome aNalysis (PhenoMeNal)
Funder: European Commission's Horizon 2020 programme (grant no. 654241)
Co-I Dr Ralf Weber: firstname.lastname@example.org
PhenoMeNal is a new, comprehensive, standardised, secure and scalable e-infrastructure that supports small and large-scale data processing and analysis pipelines for metabolic phenotype data. Based in a cloud research environment, PhenoMeNal provides a range of services in data analysis, ultimately to improve the understanding of the causes and mechanisms underlying health and disease.
1. We are leading the training and outreach work package to facilitate the dissemination and uptake of this exciting new resource.
Project: Towards an integrated approach in defining the MoA / KE of chemicals
The principal aim of our research collaboration with Unilever is to optimise and apply multi-omics and computational approaches to discover and subsequently characterise metabolic and transcriptional key events that are predictive of apical (toxicological) endpoints, focusing on Daphnia magna.
1. Determine optimal experimental designs for multi-omics and phenotyping time-course studies to provide us the ability to discover putative molecular key events in organisms exposed to baseline narcotic and specific acting chemicals.
2. Subsequently develop optimal experimental designs to characterise the quantitative relationships between these putative key events including the adverse outcome.
3. To explore how to integrate such findings with existing in vitro and in silico approaches to inform on a chemical’s Mode-of-Action as part of a weight of evidence approach for risk assessment.
Jelena Sostare2014-2018 NERC iCASE with Thermo Fisher Scientific
Project: Novel analytical approaches for the safety assessment of engineered nanomaterials
1. Optimise solvent systems for the reproducible and efficient extraction of polar metabolites and lipids from a range of sample matrices.
2. Develop novel high throughput analytical methods, comprising automated sample preparation and metabolomics analysis, for assessing the toxicity of nanomaterials to low biomass samples.
3. Utilise the knowledge discovered from integrated metabolomics and transcriptomics studies of the sentinel organism, Daphnia magna, to build an Adverse Outcome Pathway (AOP) describing the toxicity of ZnO nanomaterials.
Tom Lawson2014 - 2018 NERC iCASE with GigaScience
Project: Computational tools for the annotation of model organism metabolomes: with application to the ecotoxicological model Daphnia magna
1. Create computational methods and workflows for the optimised acquisition of mass spectrometry gas-phase fragmentation data.
2. Develop a web-framework and database for managing, analysing and curating large scale annotation studies, specifically from the Daphnia magna Deep Metabolome Annotation (DMA) project that is central to our Metabolomics & Systems Toxicology Laboratory.
3. Data and metadata analysis for model organism metabolome annotations.
Stefan Schade2015 - 2019 BBSRC iCASE with Unilever
Project: An integrative approach for understanding the adverse outcome pathways in algae
1. Optimise methods for the culturing, sampling, extraction and measurement of metabolites and lipids from Chlamydomonas reinhardtii (a single-cell green algae used in toxicity testing).
2. Develop and conduct time-course gene expression, metabolomics and lipidomics studies to deeply probe the molecular responses of C. reinhardtii to chemical exposures.
3. Construct gene regulatory networks and metabolic networks, encapsulating both the temporal changes and dose-response surface, to help to identify and characterise molecular key events in toxicity pathways, as well as the “tipping points” to adverse (apical) endpoints within an AOP framework
Judith Ngere2016 - 2020 NERC iCASE with Thermo Fisher Scientific
Project : Novel approaches to characterise the toxicokinetics and toxicodynamics of chemicals using metabolomics approaches
1. Evaluate the applicability of mass spectrometry based metabolomics methods to measure the exposome.
2. Optimise and apply direct infusion mass spectrometry (DIMS) and LC-MS metabolomics to simultaneously characterise the internal dose of a chemical, its potential biotransformation products, and the effects of the chemical on the metabolome.
3. Utilising these analytical methods, to evaluate the effectiveness of metabolomics for toxicokinetic and toxicodynamic studies in chemical exposed environmental organisms, including bee and Daphnia.
Julia Malinowska2017 - 2021 NERC iCASE with Thermo Fisher Scientific
Project: 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 Smith2017 - 2021 BBSRC iCASE with Waters
Project: 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).