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In the next instalment of the MRC TIDU Spotlight Series, we are highlighting the research of the Koohy Group.

A photo of a man and woman looking at a laptop and smiling.

The Koohy Group is a research group within the MRC Translational Immune Discovery Unit led by Professor Hashem Koohy. This group aims to decipher the fundamental principles of T cell antigen recognition using data from single cell technologies and machine learning methods. 


T cells are a pillar of the adaptive immune system, with the unique ability to recognize aberrant and infected cells in the body and eliminate them. They achieve this through unique heterodimeric receptors on their surface known as T Cell Receptors (TCRs). When TCRs interact with antigens, the T cell response is triggered. However, the underlying principles of this interaction remain unclear. Despite advancements in Systems Immunology and Artificial Intelligence/Machine Learning (AI/ML), scientists still cannot predict which antigen a given T cell will recognize.

Research within the Koohy group is primarily focused on developing machine learning models (mostly deep neural networks) and statistical approaches to gain a deeper understanding of T cell’s role in the immune system.  Members of the lab also work to develop new pipelines and platforms to help analyse the vast noisy datasets produced by rapidly advancing single cell experimental technologies.

The group has invested extensively in mapping T cells and their target antigens under various immunological conditions, including autoinflammatory and infectious diseases. For instance, during the early months of SARS-CoV-2 emergence, when experimental approaches were limited due to lockdowns and issues accessing samples, researchers in the Koohy lab were among the first to identify CD8 T cell targets from the virus genome in silico, facilitating vaccine development and providing insights into disease variation. Work in the group has also explored the role of genetic factors in T cell cross-reactivity. In September 2023, the Koohy group published a Deep Neural Network model for accurately predicting CD8 T cell targets applicable to both cancers and infectious diseases.

Speaking about the challenges facing research in this field, Prof Koohy said:

As I have highlighted in a recent Perspective article published in Nature Reviews Immunology, we are in the era of digital systems immunology. On one hand, fast-developing single cell technologies produce an unprecedented amount of multimodal data at the single cell level. On the other hand, breakthroughs in AI and Data Science have resolved some seemingly intractable questions. However, decoding the rules of T cell recognition of antigens remains a significant challenge. We still cannot construct a comprehensive map between T cells and their targets. Without solving this problem, we cannot fully harness the power of T cell immunity to treat diseases and develop the next generation of vaccines.

The research conducted by this lab is highly immunology-driven. Its primary goal is utilizing machine learning and data science techniques to investigate the mechanisms of immune development and function, disease development and progression and how to harness the immune system for treatment. This multidisciplinary strategy requires close collaboration with immunologists and medical colleagues, and the MRC TIDU provides an excellent research culture and environment for fostering such collaborations.