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  • Project No: NC-5
  • Intake: 2024 KIR Non Clinical


The efficient development of vaccines effective against global and emerging pathogens is complicated by geographic differences in vaccine responsiveness. The relative contribution of genetic and environmental factors to differential immune responses after vaccination remains poorly defined, and is complicated by the spectrum of immune cell types involved. The Lymph nodE single-cell Genomics AnCestrY (LEGACY) Network aims to generate an ethnically-diverse single-cell atlas of lymph node (LN) vaccine response, by applying single-cell technologies to lymph node samples obtained by fine needle aspiration before and after vaccination from individuals of Black (East and West African, Afro-Caribbean) and Asian (South and South-East Asian) ancestry. These technologies capture the transcriptome, cell-surface proteome and the T-cell and B-cell receptor repertoires at high resolution. Single-cell repertoire analysis provides insights into an individual’s immunological memory but the prediction of antigen/epitope specificity from the knowledge of repertoire sequences is an on-going challenge with important implications for vaccine design.

The project will involve developing and implementing single-cell approaches for the identification of antigen-specific T and B cells, by employing spectral flow cytometry and omics methods such as BEAM-seq and LIBRA-seq. The results of these experimental analyses will be assessed against computational predictions of antigen specificity. For example, the T-cell receptor computational analyses will involve the utilisation of tools such as GLIPH2 and NetMHCIIpan, amongst others, as well the possibility to refine relevant machine learning approaches. The student will benefit from interactions with the broader LEGACY Network team, including collaborators at the Uganda Virus Research Institute, who have extensive expertise in vaccine clinical trialling. Moreover, the development of a robust workflow for capturing antigen-specificity through single-cell multi-omics will be useful not only in the context of vaccination, but will also have applications for elucidating immune response dynamics in infection, autoimmunity and malignancy.



Immunology, single-cell genomics, vaccination, lymph node, ethnic diversity



The Kennedy Institute of Rheumatology is a world-class research centre, located in the University of Oxford’s Old Road campus, housing basic and clinical scientists and bioinformatics working on immunology and inflammation. This project will combine state-of-the-art single-cell technologies, bioinformatics, and machine learning approaches and the student will receive regular training and mentoring with respect to immunology, vaccinology and computational biology. The student will join a vibrant postgraduate community at the Kennedy, and will benefit from attending seminars delivered by world-leading scientists in the department and across the University, from public engagement opportunities and from transferable skills and other training sessions. The student will present their work at group meetings and national and international conferences.

The Oxford Vaccine Group is a world-renowned leader in the field of vaccinology. Numbering over 250 employees, the team develop and test vaccines across the spectrum of infectious disease, most notably the Oxford Astra-Zeneca COVID-19 vaccine, which saved 6 million lives in its first year of use. As an exciting new addition to the Oxford Vaccine Group, the LEGACY Network is the only established team to be delivering multiple in vivo human lymph node studies of vaccine immunogenicity. The student will have the unique opportunity to join the LEGACY Network and to research many novel aspects of lymph node function in the context of human vaccinology, whilst broadening their knowledge through collaboration in this emerging field of experimental medicine.



Day S, et al. (2022) Comparison of blood and lymph node cells after intramuscular injection with HIV envelope immunogens. Front Immunol, 13, 991509.

Turner JS, et al. (2020) Human germinal centres engage memory and naive B cells after influenza vaccination. Nature, 586, 127-132.

COMBAT Consortium (2022) A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. Cell, 185, 916-938.

Rich-Griffin C, et al. (2023) Panpipes: Pipelines for multimodal single-cell data analysis. bioRxiv;;


THEMES (4 key themes)


Computational biology


Lymph node biology