The QMEE CDT Project proposal database

Welcome to the QMEE CDT Project proposal database. This is a live list of projects proposals put forward by PIs across the CDT partner institutions

PIs/Supervisors will continue to add projects to this list over the next few months, so do keep checking back! You can search the projects using the box below: simply enter some text and press Search to do a text search across all the database fields. If you want to search more finely, the search tool also allows you to search on particular details of the project descriptions: you will see these finer search options appear if you click on the search box.

Click on the view button next to a project to get the full proposal description. If you want to download project details, either for all projects, or for a subset you have searched for, then click on the 'Download details' button.

Fungal pathogen evolution in a warming world: consequences for human health and biodiversity
Novel interactions between infectious disease, climate change and habitat loss threaten the health of wildlife, humans, our crops and our livestock. Predicting, mitigating and managing these impacts will require a detailed understanding of the evolutionary dynamics underlying the rise and spread of pathogens, including the roles of phenotypic plasticity, genetic variation and trade-offs between virulence and transmission success. The most potent defence against fungal infection is a high body temperature. The paucity of fungal diseases in mammals relative to insects, amphibians and plants is the reason why parasitic fungi are believed to have played a key role in the evolution of vertebrate endothermy, homeothermy and (arguably) the extinction of the dinosaurs (Casadevall 2012). What is unclear is why fungi have not co-evolved a similarly high thermal tolerance. If there is genetic variance for the thermal optima of fungi, a low thermal tolerance may reflect adaptation to the cooler and more variable environments typically experienced by saprophytes, from which parasitic fungi derive. Phylogenetic analyses provide important insights into the origin of various virulent fungal lineages. Recent studies on Batrachochytrium dendrobatidis, a global amphibian pathogen causing amphibian chytridiomycosis (Clare et al. 2016), Aspergillus fumigatus, an opportunitistic pathogen of plants and animals including humans (Meis et al. 2016) and Fusarium oxysporum, an emerging crop disease, reveal that ‘ecotype’, specifically temperature-at-origin, is an important predictive factor of virulence. However, we still know little about the relative thermal performance of these genetic isolates nor their potential for future adaptation under climate change. An understanding of how a warmer climate may facilitate the emergence of virulent fungal strains will require an integrated modelling approach. Enzyme-kinetics theory is needed to understand and predict pleiotropy in thermal performance, mutation-selection balance theory is required to understand and predict response to selection as a function of genetic variance for underlying biophysical variables maintained in different thermal environments and computational models are necessary to integrate these theoretical predictions and simulate thermal adaptation under different scenarios of environmental variability and stochasticity (Walters et al. 2012). Main project aims 1) Relate genetic variance in thermal performance e.g. thermal optima and critical maximum temperature, to underlying thermodynamic constraints and the selective environment. 2) Validate model predictions by quantifying genetic variance for thermal performance curve biophysical variables using a novel gradient plate approach on: a. hundreds of readily available genome-sequenced isolates for B. dendrobatidis, A. fumigatus and F. oxysporum. b. strains subject to laboratory evolution under various thermal regimes 3) Identify genes associated with isolate variation and their possible relationships to biophysical variables. 4) Review and adjust the assumptions of the theoretical models given empirical evidence. References: Casadevall A (2012) PLoS Pathog. DOI:10.1371/journal.ppat.1002808 Clare F et al. (2016). Phil. Trans. R. Soc. B. DOI: 10.1098/rstb.2015.0454 Meis JF et al. (2016). Phil. Trans. R. Soc. B. DOI: 10.1098/rstb.2015.0460 Walters RJ et al. (2012). Funct. Ecol. DOI: 10.1111/j.1365-2435.2012.02045.x
Matthew Fisher
Richard Walters
Trenton W. J. Garner, IOZ, trent.garner@ioz.ac.uk; Michael Shaw, Reading, m.w.shaw@reading.ac.uk
Computing, Quantitative data analysis, Ecological observations / data collection
Richard Walters
The student will develop several skill sets identified as most wanted by NERC, including modelling, data management, numeracy and risk and uncertainty. 1) Mathematical biology and its application to population genomics, enzyme kinetics and epidemiology 2) Computer programming and its application to Individual-Based Modelling, simulations 3) Statistically robust experimental design and practice
This project will use cutting-edge techniques to measure temperature across previously unattainable levels of experimental replication. In tandem with next-generation genomics, experimental evolution and access to global culture collections, the project will bring big-data approaches to addressing fundamental question of how fungal pathogens adapt, spread and thrive in changing environments.
Temperature response curves can be used to predict changes in performance in response to climate warming. The change in performance depends not only on the extent of climate warming but also on the shape of the temperature response curve for the organism’s performance between the previous and new temperatures – a hypothesis that this study will address.
Global amphibian declines; increases in fungal disease in intensive-care settings; climatic determinants of crop epidemics.
Fungi are widely emerging as serious global pathogens. This project will focus on serious pathogens that are causing global amphibian declines but also on those that are causing increasing levels of human disease – for instance cystic fibrosis patients. Impact of this project will result in increases in our ability to model disease across different scales – from global to the individual
The project captures four major research themes: 1. Quantitative ecology; 2. Technology development and Big Data; 3. Development of new statistical and computational tools and 4. Embedding ecological models within a social context. This skillset is of relevance to the fields of evolutionary ecology, global change biology or infectious disease epidemiology
Climate and climate change, Population genetics and evolution, Ecological/Evolutionary tools, technology & methods
Offered: Working with fungal pathogens; next-generation sequencing; mathematical modelling; ecological modelling Required: Wet laboratory skills, mathematical ability and programming skills
St Mary's Hospital, University of Reading, Institute of Zoology
Yes
2017-10-01 20:49:50