During the first three years of this grant the team used animal models to study T cell populations, including Salmonella and malaria infections. By focussing on the TCR in the Salmonella model, we found that a number of functionally distinct Th subpopulations developed from a single precursor cell. We developed a computational model, called TraCeR, that is able to identify specific regions of the TCR gene that are activated in any given single cell (Stubbington 2016 Nat Methods).
In the malaria model, populations of malaria-specific Th cells were analysed at different time points after exposure to the parasite. We developed a computational tool that allowed us to draw a continuous timeline (pseudotime) of a response even though we only tested cells at pre-defined time points. This helped us to better understand the process of cell activation and identified the point at which two distinct subpopulations arose from a shared group of precursor cells (Lönnberg 2017 Sci Immunol).
We then went onto study the relationship between cell cycling, proliferation and differentiation during in vivo CD4+ T cell responses in the malaria model. We investigated the development of T helper memory responses with a combination of FACS indexing, gene perturbation, scRNAseq and computational modelling. These results were published in (Soon 2020 Nat Immunol).
Another line of investigation concentrated on the role of different pathways and transcription factors in Th2 responses. We demonstrated the role of XBP-1 in co-ordinating the unfolded protein response, driving Th2 specific gene expression and accelerating proliferation (Pramanik 2018 Genome Medicine). Additionally we published a new method for single-cell ATAC-seq (Chen 2018 Nat Commun).
Our advances in T cell biology during the initial 3 years of the project meant we were able to direct this project towards studying T cells in human tissues. The single-cell transcriptome profile of the thymus, the organ responsible for T cell development, across the human lifetime and across mouse and human is a high resolution census of T cell development within the native tissue microenvironment (Park 2020 Science).
We investigated the activation and migration profiles of helper T cells along the human colon and characterised the transcriptional adaptation of regulatory T cells between the colon and associated mesenteric lymph nodes (James et al., 2020 Nature Immunology).
Expanding this work, we used single-cell genomics to examine immune cell identity across multiple tissues of the human body (Dominguez-Conde 2022 Science). This generated a map of human immune cells of unprecedented size and detail, revealing under-appreciated cell states, in particular in the memory T cell compartment. The processed data can be accessed at
https://www.tissueimmunecellatlas.org/(si apre in una nuova finestra) and the raw data has been deposited in ArrayExpress. We also developed an immune cell type classifier (CellTypist) which includes a large variety of T cell types and cell states. This tool enables the fast and accurate prediction of cell identity and is accessible via
https://www.celltypist.org/(si apre in una nuova finestra). We envision that both data and CellTypist will be a great resource for the community.
