Experimental and computational analysis of human GM-CSF producing T-helper cells

Abstract

T-helper cells are crucial elements of the immune system, and they differentiate into several subsets depending on their cytokine environment. Each subset contributes to a certain type of immune response by producing its characteristic cytokines. Classification of T-helper cells into subsets is a useful conceptual framework to investigate their biological functions. However, this classification is a simplification because the subsets are rather a continuum than discrete types. A necessary condition for health is the balanced presence and activity of the different T-helper subsets. Imbalanced activity of the T-helper subsets contributes to several diseases ranging from cancer to autoimmune and inflammatory diseases.

This thesis focuses on studying T-helper subsets that have been previously described as being associated with and contributing to autoimmune diseases, for example Multiple Sclerosis. T-helper cells producing the cytokines GM-CSF, IFN-g and/or IL-17 have been described to be important in the pathogenesis of this disease. The biological aspects studied in this thesis include the differentiation, cytokine profiles and gene regulatory patterns of these T-helper subsets. From a methodological point of view, this thesis also explores possibilities to combine experimental and computational approaches.

Paper I is focused on the (in vitro) differentiation of human GM-CSF producing T-helper cells. Herein, various types of stimuli are tested and analyzed in a data driven way. As a main result, the cytokine TGF-b is identified as a context dependent modulatory factor that can induce or repress the differentiation of human GM-CSF producing T-helper cells depending on activation type or sodium chloride concentration. GM-CSF production is highly correlated with IFN-g on the single cell level and with FOXP3 on the population level. Furthermore, human GM-CSF producing T-helper cells comprise several subpopulations, the composition of which is altered by the cytokine environment.

Paper II explores the role of splice isoforms of FOXP3 (the key transcription factor of immunosuppressive regulatory T cells) in Crohn’s disease and in the differentiation of human inflammatory T-helper cell subsets. This paper identifies a connection between the pro-inflammatory cytokine IL-1b, FOXP3 alternative splicing, and the differentiation of pro-inflammatory IL-17 producing T-helper cells. Furthermore, the paper reveals a significant correlation between a certain FOXP3 splice isoform and IL-17 expression in affected tissue from Crohn’s disease patients. Paper III presents a web application that allows non-expert users to apply pre-processing and advanced statistical methods on single cell cytometry data. The aim of this tool is to make the statistical approach to cytometry data more accessible to wet-lab biologists, and therefore serve this unmet need.

Paper IV aims to give an insight and understanding into the gene regulation and the connection between chromatin and transcriptional activity in human T-helper cells. Herein, the focus is on studying the characteristics of memory and GM-CSF producing T-helper cells. For this purpose, chromatin (ATAC-seq) and gene expression (RNA-seq) data are utilized in a combined manner and gene regulatory networks, including transcription factors that appear to be important for defining memory and GM-CSF producing T-helper cells, are identified. These transcription factors might be involved in diseases such as Multiple Sclerosis, and they can be potential candidates for future research towards therapeutic goals.

In summary, the thesis aims to contribute to our understanding of human T cell biology that is relevant for disease by combining experimental cellular immunology, next generation sequencing and computational approaches.