The influence of T cell development on pathogen specificity and autoreactivity

T cells orchestrate adaptive immune responses upon activation. T cell activation requires sufficiently strong binding of T cell receptors on their surface to short peptides derived from foreign proteins bound to protein products of the major histocompatibility (MHC) gene products, which are displayed on the surface of antigen presenting cells. T cells can also interact with peptide-MHC complexes, where the peptide is derived from host (self) proteins. A diverse repertoire of relatively self-tolerant T cell receptors is selected in the thymus. We study a model, computationally and analytically, to describe how thymic selection shapes the repertoire of T cell receptors, such that T cell receptor recognition of pathogenic peptides is both specific and degenerate. We also discuss the escape probability of autoimmune T cells from the thymus.Comment: 12 pages, 7 figure

CD8αα intraepithelial lymphocytes arise from two main thymic precursors.

TCRαβ+CD4−CD8α+CD8β− intestinal intraepithelial lymphocytes (CD8αα IELs) are an abundant population of thymus-derived T cells that protect the gut barrier surface. We sought to better define the thymic IEL precursor (IELp) through analysis of its maturation, localization and emigration. We defined two precursor populations among TCRβ+CD4−CD8− thymocytes by dependence on the kinase TAK1 and rigorous lineage-exclusion criteria. Those IELp populations included a nascent PD-1+ population and a T-bet+ population that accumulated with age. Both gave rise to intestinal CD8αα IELs after adoptive transfer. The PD-1+ IELp population included more strongly self-reactive clones and was largely restricted by classical major histocompatibility complex (MHC) molecules. Those cells localized to the cortex and efficiently emigrated in a manner dependent on the receptor S1PR1. The T-bet+ IELp population localized to the medulla, included cells restricted by non-classical MHC molecules and expressed the receptor NK1.1, the integrin CD103 and the chemokine receptor CXCR3. The two IELp populations further differed in their use of the T cell antigen receptor (TCR) α-chain variable region (Vα) and β-chain variable region (Vβ). These data provide a foundation for understanding the biology of CD8αα IELs.11166sciescopu

Lymphoid hyperplasia in transgenic mice over-expressing a secreted form of the human interleukin-1β gene product

To evaluate the biological effects of over-expression of interleukin-1β (IL-1β) on the immune system we have generated transgenic mice, expressing the IL-1β gene fused to a heterologous signal sequence under the control of the mouse immunoglobulin enhancer (Eμ). A prominent hyperplasia and a disturbed microarchitecture of lymphoid tissues were observed in the transgenic mice. The CD4+ T cells in the hyperplastic lymphoid organs seemed to invade the majority of the lymphoid organs including B-cell restricted areas. Analysis of lymph node cells revealed an increased frequency of CD4+ CD44high CD62L− T cells and local secretion of IL-2 and IL-4, compatible with an elevated number of activated T cells. Furthermore, significant levels of human IL-1β in sera and high concentrations of serum immunoglobulin G (IgG) were observed in the transgenic mice. The data suggest a role for IL-1β in controlling lymphoid microarchitecture and, when over-expressed, breaking the threshold in T-helper–B-cell interaction

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion