**If you are interested in this studentship, it is vital to contact Professor Mark Viant prior to application with a copy of your CV: [email protected]
The overall aim of this PhD proposal is to implement a method that we intend to have immediate use in chemical safety in the UK. The proposed method will use a combination of in vitro toxicity tests, metabolic biomarker assays, and computational modelling to derive informative molecular measurements of toxicity thresholds. Breaking this down further, the metabolic biomarker assays will include untargeted and targeted metabolomics assays – which is a research speciality of the Birmingham team – and the computational modelling will focus on physiologically based pharmacokinetic (PBPK) modelling – a research speciality of the HSE team. Importantly, the weighting between different aspects of the PhD can be changed significantly in response to the interests of the student.
The objectives of the PhD are:
1. Implement and optimise metabolomics approaches to measure the in vitro molecular responses of cells to chemicals. There is scope to conduct cell toxicity studies at Birmingham, or via collaboration with external partners. These studies will be designed with the central purpose of deriving ‘benchmark doses’, i.e. to determine the exposure concentrations that cause small but measurable metabolic perturbations that precede higher order cellular damage. The student will have access to world-class mass spectrometry metabolomics facilities at Birmingham. There is scope to develop new mass spectrometry assays if this is of interest to the student.
2. Investigate and optimise the computational strategies for extracting information from the metabolomics dose-response datasets to derive robust ‘points of departure’ for each chemical. This builds upon related work recently published using transcriptomics data. We will explore data and information derived at a range of levels, from individual metabolites to metabolic pathways. There is scope to delve more deeply into the metabolic pathway analyses, or alternatively just to apply the available bioinformatics tools, dependent on the student’s capabilities.
3. The next stage of the project is to apply biologically-based mathematical models, such as PBPK models, that can be used to extrapolate from the quantitative in vitro data derived from the earlier objectives to in vivo, for the purposes of human risk assessment for selected chemicals. Specifically, we will seek to incorporate mechanistic biology into the PBPK models to provide quantitative, biologically-based chemical risk assessment.
This PhD is a collaboration between the Metabolomics & Systems Toxicology Lab at the University of Birmingham (Prof. Mark Viant https://more.bham.ac.uk/viant/
) and Computational Modelling in the Health & Biohazards Team at the HSE’s Science and Research Centre (Dr. George Loizou https://www.linkedin.com/in/georgeloizou/?originalSubdomain=uk
). Further international collaborations, for example with the European Food Safety Authority, are anticipated.
We seek an excellent, highly motivated candidate with a high quality undergraduate or Masters degree (can be pending) in fields such as toxicology, pharmacology, mechanistic biology or bioanalytical chemistry, who has a passion to apply and then translate state-of-the-art laboratory and/or computational approaches to 21st century challenges in human toxicology.
The PhD has a fixed start date of 23 September 2019, and is part of the MIBTP doctoral training programme, enabling the student to acquire a range of quantitative training in the first six months (https://warwick.ac.uk/fac/cross_fac/mibtp/pgstudy/trainingprogramme/
Bartels, M., Rick, D., Lowe, E., Loizou, G., Price, P., Spendiff, M., et al. (2012). Development of PK- and PBPK-based modeling tools for derivation of biomonitoring guidance values. Comput Methods Programs Biomed 108(2), 773-88.
Davidson, R.L., R. J. M. Weber, H. Liu, A. Sharma-Oates, M. R Viant, Galaxy-M: A galaxy workflow for processing and analysing direct infusion and liquid chromatography mass spectrometry-based metabolomics data. GigaScience 5:10 (2016).
Loizou, G. D. (2016). Animal-Free Chemical Safety Assessment. Frontiers in Pharmacology 7, 10.3389/fphar.2016.00218.
Loizou, G. D. and Hogg, A. (2011). MEGen: A Physiologically Based Pharmacokinetic Model Generator. Frontiers in Pharmacology: Predictive Toxicity 2 Article 56, 1-14, 10.3389/fphar.2011.00056.
McNally, K., Cotton, R., Hogg, A., and Loizou, G. (2014). PopGen: A virtual human population generator. Toxicology 315, 70-85.
Southam, A.D., R. J. M. Weber, J. Engel, M. R. Jones, M. R. Viant, A complete workflow for high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry-based metabolomics and lipidomics. Nature Protocols 12, 310-328 (2017).
Zhang, J., M. A. Abdallah. T. D. Williams. S. Harrad. J. K. Chipman. M. R. Viant, Gene expression and metabolic responses of HepG2/C3A cells exposed to flame retardants and dust extracts at concentrations relevant to indoor environmental exposures. Chemosphere 144, 1996-2003 (2016).