PhD Research Project: A Hyper-Omics approach to reveal how diet reduces ageing
Living longer and, especially, healthier is a key objective of medical science and a growing priority in our ageing society. The only known reliable option to achieve this is dietary restriction. When the results from model organisms are extrapolated to humans, interventions or drugs that mimic dietary restriction are predicted to lead to life- and health-span extension that is larger than curing all cancer and cardiovascular disease. Hence, the impact of understanding the mechanisms underlying dietary restriction for medical science is immense, yet progress to uncover these mechanisms has been limited. In addition, on a fundamental theoretical level, the mechanisms of ageing underlie all major life-history trade-offs and understanding ageing is thus key to understand many areas of biology.
We propose a novel Hyper-Omics approach in flies (Drosophila melanogaster) to reveal the mechanisms of dietary restriction. Flies are a convenient model, because dietary restriction reduces mortality risk strongly (over 5-fold) and instantly (within a day). Furthermore, flies have a comprehensively annotated transcriptome, proteome and genome available; and candidate genes can be tested readily using transgenic flies.
Datasets will be generated that consist of full (phospho-)proteomes, metabolomes and transcriptomes in a time-series after exposure to dietary restriction. Combined inference from different omics is in its infancy, but has great promise to understand complex biology. You will develop the first complete framework for such combined inference and will extend this using molecular evolution approaches. Statistical techniques can involve (amongst others) principle-component-analysis, meta-analysis, molecular evolution and Bayesian Network analysis. Experimental results from tests of candidate genes identified (Simons’ lab) will further inform the developed framework to provide a detailed insight into the complex biology of dietary restriction. You will require a strong quantitative skillset, but direct experience in any of these statistical techniques or in biology is no requirement to be considered for the studentship.
Mirre Simons (lead) is a Vice-Chancellor’s fellow and works from a combined evolutionary and biomedical perspective on the biology of ageing. He uses comparative, theoretical and meta-analytic methods to study the process of ageing and uses Drosophila melanogaster (the fruit fly) as a powerful genetic model system. Mirre has a strong statistical skillset with a proven track record of developing novel statistical approaches to understand the biology of ageing. Mirre’s lab will provide the data required for this project and can directly test candidates revealed by the efforts of the student. This ensures a direct embedding of the work of the student in actual biology and empirical feedback through experimental testing. Mirre will further specifically support the statistical approaches to develop the combined inference methods.
Toni Gossmann (co-supervisor) is a Leverhulme Early Career Fellow with a background in bioinformatics. He works on theoretical aspects of evolutionary biology using the latest techniques in proteomics, genomics and transcriptomics. He has experience in the application of several computational approaches in sequence analyses using molecular evolution and population genetic frameworks. His key interest is to understand how evolution operates on the genomic level, but also uses novel tools to understand complex biology. A key aspect of this is reflected by his work on NAD metabolism, a fundamental component in ageing, and an important field in metabolomics. Toni will advise on the statistical approaches, on the generation of sequence datasets and will specifically support the student regarding the computational aspects of the project, in particular the molecular evolutionary approaches that are crucial for the understanding of the genetics of the underlying traits
External international collaboration & the Research environment
Further support and feedback on the project will be obtained through established collaborations of Simons on statistics and fly ageing at Brown University (USA) and of Gossmann on proteomics (University of Singapore and Mainz) and metabolomics of NAD metabolism (University of Bergen and Tromsoe, Norway). These external collaborators ensure a vibrant and stimulating international environment for the student. We are well-funded for this work and additional data can be generated if this should be required. There is a growing group of researchers working on ageing at the University of Sheffield. The Faculty of Science and the Department of Animal and Plant Sciences, specifically, are excellent in using quantitative and statistical techniques to understand complex biology.
Please do not hesitate to ask either Mirre (firstname.lastname@example.org) or Toni (email@example.com) should you have any questions about the project.
This project will be funded by the Leverhulme Trust Centre for Advanced Biological Modelling