This exciting 4-year BBSRC iCASE PhD opportunity bridges the University of Birmingham’s (*) metabolomics team and Unilever’s Safety and Environmental Assurance Centre (SEAC), both having state-of-the-art facilities and renowned research programmes, thereby creating an excellent environment for this challenging yet impactful research project.
* Winner of ‘University of the Year for Graduate Employment’, The Times and The Sunday Times Good University Guide 2015-16; 91% of our postgraduate researchers from the School of Biosciences were in work and/or further study six months after graduation.
A revolution is now occurring in bioscience, driven by the availability of highly sensitive molecular technologies that can generate ‘big data’ to drive new understandings of molecular function. These technologies can help to create quantitative models of organism function. Of major importance, and often overlooked, is modelling the effect that organisms can have on the stressor (to complement the more-often studied effect the stressor can have on the organism) – representing a critical element of exposure science. Understanding how species deal with increasing chemical stressors (both from natural sources and/or anthropogenic-activities) will deeply influence the way we manage the potential risk of these stressors.
In a rapidly changing world with ecosystems under unprecedented pressures, leading to biodiversity loss at a rate never observed before, bio-analytical approaches used in tandem with computational modelling are key to deal with the problem. In an attempt to mitigate this pressure, there is an impelling need to understand the most sensitive physiological properties of organisms (and their underlying molecular mechanisms). To achieve this prognostically within a safety assessment framework, i.e. to characterize the stressor before it’s allowed to enter the environment, the decision-making requires quantitative exposure and effect models, as highlighted by the recent publication of an “opinion on the state-of-the-art of Toxicokinetic/Toxicodynamic effect models for regulatory risk assessment” by EFSA. This is where new, advanced, bio-analytical and molecular technologies can have a key role in the way we face this challenge, which we will explore within this PhD.
The overall aim of this PhD project is to understand the physiological properties involved in chemical absorption, distribution, metabolism and excretion (ADME) processes of an invertebrate model species, using state-of-the-art molecular and imaging tools, and to develop relevant physiology-based kinetic (PBK) models that can then be used to predict how chemicals are processed by this model species. It is intended that these models would immediately translate into Unilever’s risk assessment toolkit, highlighting the real-world impact of this PhD.
This project will use cutting-edge advanced technologies, including untargeted mass spectrometry (MS) and respective data analyses workflows, mass spectrometry imaging (MSI), genomics and mathematical modelling to address four tasks:
1. Define the physiological properties which influence the absorption of chemicals using the model invertebrate species Daphnia magna.
2. Understand the relationships between external and internal concentrations of a suite of chemicals over time and determine the properties (chemical and biological) influencing these relationships (a so-called one compartment mathematical model).
3. Understand the internal distribution of chemicals within the model organism over time to describe detoxification processes, underpinning this knowledge with genomic information on Daphnia’s ability to metabolise chemicals.
4. Develop a PBK model for Daphnia magna, based on existing literature and knowledge derived from the novel data generated above.
This project will use cutting-edge approaches, including untargeted mass spectrometry analysis (based on metabolomics) and mass spectrometry imaging, as well as genomics and modelling. The student training and research will take place both at the University of Birmingham and Unilever (Colworth). The Safety and Environmental Assurance Centre at Unilever houses state of the art research laboratories and ca. 180 scientists. The metabolomics team at the University of Birmingham comprises of ca. 25 PhD students and postdoctoral researchers. The School of Biosciences was ranked in 6th in the UK Russell Group in REF2014, with >90% of research rated as world leading.
Are you the right person for this PhD? We seek an excellent, highly motivated candidate with a high quality undergraduate and preferably Masters degree (can be pending) in fields such as biochemistry, bioanalytical chemistry or (eco)toxicology. A strong interest in data analysis and modelling is required.
Please note: any interested candidates should email Mark Viant ([email protected]
) to confirm their interest, in addition to applying through the website below.
• Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms.
EFSA Panel on Plant Protection Products and their Residues (PPR),
EFSA Journal, 2018, 16(8), p.e05377.
• Depressing antidepressant: fluoxetine affects serotonin neurons causing adverse reproductive responses in Daphnia magna.
Campos B, Rivetti C, Kress T, Barata C, Dircksen H
Environmental Science & Technology. 2016 May 11;50(11):6000-7.
• Combined mathematical modelling and experimentation to predict polymersome uptake by oral cancer cells.
Sorrell I, Shipley RJ, Hearnden V, Colley HE, Thornhill MH, Murdoch C, Webb SD. Nanomedicine: Nanotechnology, Biology and Medicine. 2014 Feb 1;10(2):339-48.
• Toxicokinetic models and related tools in environmental risk assessment of chemicals.
Grech A, Brochot C, Dorne JL, Quignot N, Bois FY, Beaudouin R.
Science of the Total Environment. 2017 Feb 1;578:1-5.
• Metabolomics Discovers Early-Response Metabolic Biomarkers that Can Predict Chronic Reproductive Fitness in Individual Daphnia magna
Nadine S. Taylor, Alex Gavin and Mark R. Viant
Metabolites. 2018 Sep; 8(3): 42-61.
• Distinguishing between the metabolome and xenobiotic exposome in environmental field samples analysed by direct-infusion mass spectrometry based metabolomics and lipidomics
Andrew D. Southam, Anke Lange, Raghad Al-Salhi, Elizabeth M. Hill, Charles R. Tyler and Mark R. Viant
Metabolomics. 2014; 10(6): 1050–1058.