Dissecting the effects of inhibitory signalling on T cell activation using optogenetics

T cells are an essential part of our immune system that eliminate infections to keep us healthy despite constant exposure to pathogens. T cells contain an intricate signalling network that decides whether the cells of our body have become infected, but sometimes this decision-making process is ineffective and leads to disease. Many current drugs are designed to manipulate these signalling pathways to improve the immune response to infection or cancer. Whilst great progress has been made in identifying the parts of these networks, we must also understand the dynamic connections between them to know how these therapies work and hopefully improve them. However, for most signalling networks this knowledge remains very limited. To address this, we develop new molecular tools to investigate the dynamics of the T cell signalling network by engineering inputs that are light-responsive, giving us precise control over signalling in space and time.

In this project, we will explore how different input signals are combined together by T cells to control the downstream output response. We will develop and implement new tools to investigate this question at the mechanistic level. Understanding how T cells 'integrate' information has important consequences, as many of the 'checkpoint' inhibitor drugs currently used for cancer immunotherapy disrupt this process, so elucidating how they work is required to improve their clinical function.

The PhD student undertaking this project will master an array of biochemical and cell-biological techniques required to investigate questions relevant to medical research using quantitative approaches. The student will also get an excellent grounding in the principles and application of dataset modelling using computational and mathematical approaches from the second supervisor, which will provide strong interdisciplinary skills-training.