Bioinformatics Seminars

Bioinformatics Seminar

Time: 10:45am Tuesdays.
Venue:
Level 7 Seminar Room 2, WEHI1

17 April 2018

Bioinformatics analyses to uncover the molecular mechanism underlying T cell exhaustion caused by chronic infection

Yang Liao
WEHI Bioinformatics

Immune T cell exhaustion has been known as a result of persistent antigenic stimulation in chronic infection or cancer. Although T cell exhaustion is known to impair the ability of the immune system in clearing the antigen and prolong the course of infection, very little is known about the molecular mechanism underlying the initiation and maintenance of T cell exhaustion.

In this talk, I will present the bioinformatics analyses we carried out to try to understand the transcriptome changes and gene regulation that occurred during the process of T cell exhaustion. Using RNA-seq data generated from CD8+ T cells that were harvested from samples with acute or chronic viral infections, we identified a gene signature that characterizes the development of T cell exhaustion. We found that many of the signature genes are regulated by a master transcription factor, Irf4. The analysis of ChIP-seq data revealed that Irf4 binds to many of these signature genes and therefore directly regulates their expression. We further investigated the role of two other important transcription factors, Batf and Nfatc1, in regulating the expression of genes implicated in T cell exhaustion arising from chronic infection. A large portion of chronic signature genes were found to be transcriptionally bound by all three factors, manifesting the cooperative activity of these factors in establishing T cell exhaustion. The close proximity between the binding sites from different factors further signified the cooperation of the three factors. The genome-wide analysis of expression changes and transcription factor binding in samples with chronic infection suggests that T cell exhaustion is potentially established and maintained by a transcriptional network comprising transcription factors including Irf4, Batf and Nfatc1. Key genes identified from this study are potential therapeutic targets for improved diagnosis and treatment of patients with chronic infection.


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