University of Cambridge
Systematic analysis of the molecular mechanisms of T cell entry into tissues
Abstract
dc:description.abstractIt has now become evident that a subset of T cells establish residency in non-lymphoid tissues and function to provide local immune protection and tissue homeostasis. Classically, immunologists have inferred immune function from immune cells sampled from the blood and lymphoid organs, despite the challenged tissue representing the key site of immune pathology. The discovery of tissue-resident T cells has birthed the field of tissue immunity in which immunologists are seeking to understand immunity at the level of the tissue. In humans, tissue-resident T cells have been isolated from various tissues and linked to infectious disease, autoimmunity, transplantation and cancer pathology. However, a thorough understanding of the subset-specific and tissue-specific features of tissue-resident T cells has not yet been realised. Progress in this field has been supported enormously by the technical advances in single-cell genomics and high-dimensional profiling such as flow cytometry and cytometry by time of flight (CyTOF). These technologies have made it possible to profile T cells at the single-cell resolution, aiding in the identification of their distinctive transcriptional profile when compared to recirculating T cells as well as tissue-specific features of tissue-resident T cells. Nonetheless, the mechanisms governing the localisation of subset-specific tissue-resident T cells within specific tissues remains to be explored. CRISPR-Cas9 genome editing technologies coupled with single-cell RNA-sequencing readouts, have revolutionised our ability to identify novel gene functions whilst obtaining comprehensive transcriptomic phenotypes. However, limitations in cell throughput and lack of protein-level data make single-cell RNA-sequencing readouts incompatible with studies assessing cells present at low frequencies and questions in which precise data on protein expression is crucial. With that in mind, we developed the FlowCode vector barcoding system adapted from the ProCode system to track T cells in vivo. The FlowCode system, like the ProCode system, utilises protein epitopes in triplet combination fused to a carrier protein; each unique combination of triplet barcode can then be decoded by a panel of antibodies targeting the epitope tags. The FlowCode system was adapted for flow cytometry-based detection via the modification of the carrier protein. I then used the FlowCode systems to barcode our CRISPR retroviral library targeting 158 migration genes with the aim to systematically assess the genes governing the trafficking and infiltration of T cell subsets into tissues. In this thesis, I demonstrate the use of FlowCode for efficient flow cytometry-based gRNA identification, allowing for the assessment of genes functioning to facilitate or impede T cell entry into 16 different tissues. Additionally, I demonstrated the ability of FlowCodes to enable the simultaneous assessment of T cell phenotype, allowing for the T cell subset-specific characterisation of gene perturbations. In conclusion, I have demonstrated the use of FlowCode, a protein-level vector and cell barcoding systems for tracking T cells in vivo and characterising the molecular mediator required for their localisation during homeostasis. This system can be used to track T cells in murine models of diseases where tissue-resident T cells are known to play an active role, with the hope of providing insights into novel therapeutic targets.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Ali, Magda
- Advisor dc:contributor.advisor
-
- Liston, Adrian
Subjects
dc:subject × 4Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.117849
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/383509