Dr Alexander Greenshields-Watson

Postdoctoral Researcher

About Me

I am a T cell immunologist who has worked at the intersection of structural biology, the wet lab and bioinformatics. My work has focused on CD4+ (helper) T cell recognition of HLA Class-II antigens in both influenza and cancer. However I have spent several years working in the field of cancer immunology and CD3xTCR-bispecific immunotherapy.

Research Interests

My primary research interests are building and exploiting cutting edge informatics tools to understand the rules that govern adaptive immune receptor recognition and their relationship to immune function and dysregulation.

Publications

Hassel, J., Stanhope, S., Greenshields-Watson, A., Machiraju, D., Enk, A., Holland, C., Abdullah, S., Benlahrech, A., Orloff, M., Nathan, P., Piperno-Neumann, S., Staeger, R., Dummer, R. and Meier-Schiesser, B. (2024) “Tebentafusp Induces a T-Cell-Driven Rash in Melanocyte-Bearing Skin as an Adverse Event Consistent with the Mechanism of Action.”, The Journal of investigative dermatology, pp. S0022–202X(24)01886.
Greenshields-Watson, A., Abanades, B. and Deane, C. (2024) “Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.”, Frontiers in immunology, 15, p. 1352703.
Gordon, G., Greenshields-Watson, A., Agarwal, P., Wong, A., Boyles, F., Hummer, A., Lujan Hernandez, A. and Deane, C. (2024) “PLAbDab-nano: a database of camelid and shark nanobodies from patents and literature”, bioRxiv.
Raybould, M., Greenshields-Watson, A., Agarwal, P., Aguilar-Sanjuan, B., Olsen, T., Turnbull, O., Quast, N. and Deane, C. (2024) “The Observed T cell receptor Space database enables paired-chain repertoire mining, coherence analysis and language modelling”, bioRxiv.
Chen, Y., Mason, G., Scourfield, D., Greenshields-Watson, A., Haigh, T., Sewell, A., Long, H., Gallimore, A., Rizkallah, P., MacLachlan, B. and Godkin, A. (2023) “Structural definition of HLA class II-presented SARS-CoV-2 epitopes reveals a mechanism to escape pre-existing CD4+ T cell immunity”, Cell Reports, 42(8).
Greenshields-Watson, A., Abanades, B. and Deane, C. (2023) “Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms”, bioRxiv.
MacLachlan, B., Mason, G., Greenshields-Watson, A., Triebel, F., Gallimore, A., Cole, D. and Godkin, A. (2021) “Molecular characterization of HLA class II binding to the LAG-3 T cell co-inhibitory receptor.”, European journal of immunology, 51(2), pp. 331–341.
Pires, A., Greenshields-Watson, A., Jones, E., Smart, K., Lauder, S., Somerville, M., Milutinovic, S., Kendrick, H., Hindley, J., French, R., Smalley, M., Watkins, W., Andrews, R., Godkin, A. and Gallimore, A. (2020) “Immune Remodeling of the Extracellular Matrix Drives Loss of Cancer Stem Cells and Tumor Rejection.”, Cancer immunology research, 8(12), pp. 1520–1531.
Greenshields-Watson, A., Attaf, M., MacLachlan, B., Whalley, T., Rius, C., Wall, A., Lloyd, A., Hughes, H., Strange, K., Mason, G., Schauenburg, A., Hulin-Curtis, S., Geary, J., Chen, Y., Lauder, S., Smart, K., Vijaykrishna, D., Grau, M., Shugay, M., Andrews, R., Dolton, G., Rizkallah, P., Gallimore, A., Sewell, A., Godkin, A. and Cole, D. (2020) “CD4<sup>+</sup> T Cells Recognize Conserved Influenza A Epitopes through Shared Patterns of V-Gene Usage and Complementary Biochemical Features.”, Cell reports, 32(2), p. 107885.
Bagaev, D., Vroomans, R., Samir, J., Stervbo, U., Rius, C., Dolton, G., Greenshields-Watson, A., Attaf, M., Egorov, E., Zvyagin, I., Babel, N., Cole, D., Godkin, A., Sewell, A., Kesmir, C., Chudakov, D., Luciani, F. and Shugay, M. (2020) “VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium.”, Nucleic acids research, 48(D1), pp. D1057 - D1062.

Contact Details

Email: alexander.greenshieldswatson@stats.ox.ac.uk

Office: 2.17

Research Groups

Oxford Protein Informatics Group

Computational Statistics and Machine Learning

Computational Biology and Bioinformatics