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The T-cell receptor in Health and disease

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  • Full or part time
    Prof A Sewell
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

BACKGROUND: T-cells orchestrate immunity by distinguishing ‘self’ from ‘non-self’ and choreographing immune attack on pathogens and cancerous cells. The key to this recognition resides in the αβ T cell receptor (TCR) which acts as acts as the ‘Swiss Army Knife’ of the immune system by recognising foreign peptides, lipids and metabolites (reference 1). This remarkable receptor can theoretically exist in over 1018 different forms (reference 2) and sits at the heart of most human pathologies. T-cells protect us from infection, can eliminate cancer and hold the key to successful vaccination. On the negative side, these cells are thought to instigate all autoimmune disease (type 1 diabetes, multiple sclerosis, rheumatoid arthritis etc) and cause acute rejection of transplanted organs. They are also responsible for many allergic reactions. Understanding how TCRs are generated and maintained throughout life is therefore likely to become a very important research area in future medicine and diagnostics. In short, we believe that diseases can be diagnosed or predicted from TCR sequencing and we are in the process of building a repository for these sequences and associated tools that will enable us, and other researchers, to answer a wide variety of medically important research questions.

PROJECT: Our TCRs are made somatically by gene rearrangement. This process generates several million unique TCR sequences in any individual collectively termed “the repertoire”. No two individuals, even if they are genetically identical, will have the same repertoire (hence even identical twins can be discordant for autoimmune diseases). The primary research focus of this project is to dissect the genetic forces that govern the assembly and the maintenance of the mature repertoire in different settings, including, healthy twins, cancer-specific responses following successful immunotherapy and autoimmune responses. This will be done at the molecular level, using high-throughput sequencing of sorted T-cell populations. This “systems” approach will undoubtedly shed light into the genetic and environmental factors at work to shape the TCR repertoire in health and disease (reference 3). The successful candidate will pursue a PhD in bioinformatics/systems biology over 4 years using high–throughput sequencing data of TCR repertoires. While the range of important future applications of TCR repertoire technologies is vast and a number of proof-of-concept studies have been done, the full potential of these technologies is far from being reached. In order to contribute to this development cutting-edge experimental technology in the Sewell lab needs to be combined with critical and deep analyses to distinguish biases caused by experimental artefacts from signals informing biological phenomena. This involves computer programming, running large computations both in terms of memory usage and CPU usage, and statistical techniques for data exploration and analysis. We will combine computational/statistical method development with targeted data analyses exploring medically important questions.

This project will be supervised by Prof Andrew Sewell, Dr Barbara Szomolay, Dr Sasch Ott, Dr Tom Connor, Dr Meriem Attaf

Please submit a CV and a covering letter in the first instance to Dr Meriem Attaf - [Email Address Removed]
Please be aware that Cardiff University reserves the right to close this vacancy early should sufficient applications be received

Funding Notes

UK/EU tuition fees (if applicable, any eligible non-EU candidates must fund the remainder of the overseas fee)
Doctoral Stipend matching UK Research Council National Minimum (£14,057 p.a. for 2015/16 updated each year)

How good is research at Cardiff University in Clinical Medicine?

FTE Category A staff submitted: 59.01

Research output data provided by the Research Excellence Framework (REF)

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