T-Cell Receptor Repertoire Analysis with Computational Tools—An Immunologist’s Perspective

Over the last few years, there has been a rapid expansion in the application of information technology to biological data. Particularly the field of immunology has seen great strides in recent years. The development of next-generation sequencing (NGS) and single-cell technologies also brought forth a revolution in the characterization of immune repertoires. T-cell receptor (TCR) repertoires carry comprehensive information on the history of an individual’s antigen exposure. They serve as correlates of host protection and tolerance, as well as biomarkers of immunological perturbation by natural infections, vaccines or immunotherapies. Their interrogation yields large amounts of data. This requires a suite of highly sophisticated bioinformatics tools to leverage the meaning and complexity of the large datasets. Many different tools and methods, specifically designed for various aspects of immunological research, have recently emerged. Thus, researchers are now confronted with the issue of having to choose the right kind of approach to analyze, visualize and ultimately solve their task at hand. In order to help immunologists to choose from the vastness of available tools for their data analysis, this review addresses and compares commonly used bioinformatics tools for TCR repertoire analysis and illustrates the advantages and limitations of these tools from an immunologist’s perspective

Human TH17 cells engage gasdermin E pores to release IL-1α on NLRP3 inflammasome activation

It has been shown that innate immune responses can adopt adaptive properties such as memory. Whether T cells utilize innate immune signaling pathways to diversify their repertoire of effector functions is unknown. Gasdermin E (GSDME) is a membrane pore-forming molecule that has been shown to execute pyroptotic cell death and thus to serve as a potential cancer checkpoint. In the present study, we show that human T cells express GSDME and, surprisingly, that this expression is associated with durable viability and repurposed for the release of the alarmin interleukin (IL)-1α. This property was restricted to a subset of human helper type 17 T cells with specificity for Candida albicans and regulated by a T cell-intrinsic NLRP3 inflammasome, and its engagement of a proteolytic cascade of successive caspase-8, caspase-3 and GSDME cleavage after T cell receptor stimulation and calcium-licensed calpain maturation of the pro-IL-1α form. Our results indicate that GSDME pore formation in T cells is a mechanism of unconventional cytokine release. This finding diversifies our understanding of the functional repertoire and mechanistic equipment of T cells and has implications for antifungal immunity

T-Cell Receptor Repertoire Analysis with Computational Tools—An Immunologist’s Perspective

Over the last few years, there has been a rapid expansion in the application of information technology to biological data. Particularly the field of immunology has seen great strides in recent years. The development of next-generation sequencing (NGS) and single-cell technologies also brought forth a revolution in the characterization of immune repertoires. T-cell receptor (TCR) repertoires carry comprehensive information on the history of an individual’s antigen exposure. They serve as correlates of host protection and tolerance, as well as biomarkers of immunological perturbation by natural infections, vaccines or immunotherapies. Their interrogation yields large amounts of data. This requires a suite of highly sophisticated bioinformatics tools to leverage the meaning and complexity of the large datasets. Many different tools and methods, specifically designed for various aspects of immunological research, have recently emerged. Thus, researchers are now confronted with the issue of having to choose the right kind of approach to analyze, visualize and ultimately solve their task at hand. In order to help immunologists to choose from the vastness of available tools for their data analysis, this review addresses and compares commonly used bioinformatics tools for TCR repertoire analysis and illustrates the advantages and limitations of these tools from an immunologist’s perspective