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Networks involved in the calibration of T cell activation thresholds

Primary Supervisor: Dr David Bending, Institute of Immunology and Immunotherapy

Secondary supervisor: Dr Fabian Spill

PhD project title: Networks involved in the calibration of T cell activation thresholds

University of Registration: University of Birmingham

Project outline:

T cells are an essential population of lymphocytes that co-ordinate adaptive immune responses. T cell function is heavily dependent on their T cell receptors (TCRs) which respond to peptide fragments (called antigens) presented to them by antigen presenting cells (APCs). We have recently shown that in certain contexts, high amounts of antigen render T cells refractory to further restimulation1. This is in part due to the upregulation of immune checkpoints, such as PD1, Lag3 and CTLA4 on the cell surface, that act to restrain TCR signalling, as reported using a novel TCR reporter system2. Whilst immune checkpoint expression can account for some of this resistance to restimulation, we hypothesise that T cells also undergo rapid re-wiring of downstream intracellular signalling networks. In this project, we will employ state of the art in vivo research tools to investigate the intracellular signalosome in T cells that are rendered refractory to further stimulation. Proteomic analysis will be used to inform network approaches to make predictions about key pathways that may contribute to the raising of T cell activation thresholds. These can then be tested in a variety of in vitro and in vivo immunology models. This project will therefore gain insight into how T cells sense and adapt to antigen in their environment, providing fundamental insight into the workings of the immune system.


  1. Elliot et al., bioRxiv 2021, (in press at Immunity)
  2. Jennings et al., Cell Reports 2020,

BBSRC Strategic Research Priority:

Sustainable Agriculture and Food: Understanding the Rules of Life: Immunology

    Techniques that will be undertaken during the project:

    • In vivo immunology models (mice) – immunisation, analysis of T cell responses
    • Flow cytometry
    • Proteomics
    • RNA sequencing
    • Bioinformatics (training provided)
    • Network analysis
    • Systems biology modelling
    • Training for all techniques will be provided at a level suitable for the candidates. Specifically, candidates from the life sciences will be trained on computational/mathematical methods.

    Contact: Dr David Bending, University of Birmingham