Bioinformatic methods to interrogate flow cytometry and RNA sequencing data to understand T-cell interactions in disease

Griffiths, Daniel 2025. Bioinformatic methods to interrogate flow cytometry and RNA sequencing data to understand T-cell interactions in disease. MPhil Thesis, Cardiff University. Item availability restricted.

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Abstract

Conventional T cells are defined by expression of CD4+ or CD8+ surface antigens. These are the most abundant of the CD3+ T cell lineage, and are the most characterised in their role in immune response, regulation, and disease. Unconventional T cells do not present these conventional markers, and are not fully characterised. These cells are of low frequency in peripheral blood and are tissue resident, with phenotypes and roles that are tissue specific. Tissue specific analysis of immune cells allows these unconventional immune cells, which are of low frequency / absent from peripheral blood, to be analysed. Colorectal cancer treatment often involves colorectal resection, removal of the tumour, and stitching the remaining colon back together; this process is called anastomosis. Anastomotic leak (AL) occurs in approximately 10% of patients undergoing anastomosis and is associated with significantly increased mortality and complications. Current diagnostic confirmation relies on elevated systemic C-reactive protein (CRP) and clinical symptoms, typically enabling detection only from postoperative day 2-3. Earlier and more specific markers are needed to improve patient outcomes. Evidence from peritonitis studies suggests that unconventional T cells in peritoneal fluid may predict complications, motivating investigation in AL. Innate immune cells such as MAIT and γδ T cells are often the first immune cells at the site of a bacterial infection. Previous work by the Eberl lab indicated a regulatory role of γδ T cells on CD4+ T cells, and collected RNA sequencing data of γδ T cells in different relevant tissue specific cytokine environments for a more in depth mechanistic understanding. In this thesis, a workflow for quality control is proposed and analysis of the data is performed. Previous researchers acquired many flow cytometry files in many individual batches and with variable quality. This thesis discusses the ability for these flow cytometry files to be analysed together and batch-corrected using publicly available packages, within a reproducible bioinformatic pipeline. These findings suggest that unconventional T cells are in measurable frequency using flow cytometry, and sets a proof-of concept for the use of peritoneal fluid to measure immune cell frequency, particularly of tissue resident unconventional T cells. Further, RNA sequencing analysis found CXCL13 and CD30 expression correlating with an inflammatory related IL-21 environment, with indications of the role of γδ T cells in initiating an immune response at the site of infection. This data further advances the understanding of innate immune response, and indicates potential candidates for novel, specific targets for immune therapy for chronic inflammatory conditions. These initial studies also highlight improvements to study design and data acquisition that can improve quality of data along the course of a longitudinal study.

Item Type:	Thesis (MPhil)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Medicine
Date of First Compliant Deposit:	2 October 2026
Last Modified:	02 Oct 2026 16:03
URI:	https://orca.cardiff.ac.uk/id/eprint/189958

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