Christopher Arendt

PKC-θ is required for TCR-induced NF-κB activation in mature but not immature T lymphocytes

Productive interaction of a T lymphocyte with an antigen-presenting cell results in the clustering of the T-cell antigen receptor (TCR) and the recruitment of a large signalling complex to the site of cell–cell contact. Subsequent signal transduction resulting in cytokine gene expression requires the activation of one or more of the multiple isoenzymes of serine/threonine-specific protein kinase C (PKC). Among the several PKC isoenzymes expressed in T cells, PKC-θ is unique in being rapidly recruited to the site of TCR clustering. Here we show that PKC-θ is essential for TCR-mediated T-cell activation, but is dispensable during TCR-dependent thymocyte development. TCR-initiated NF-κB activation was absent from PKC-θ-/- mature T lymphocytes, but was intact in thymocytes. Activation of NF-κB by tumour-necrosis factor α and interleukin-1 was unaffected in the mutant mice. Although studies in T-cell lines had suggested that PKC-θ regulates activation of the JNK signalling pathway, induction of JNK was normal in T cells from mutant mice. These results indicate that PKC-θ functions in a unique pathway that links the TCR signalling complex to the activation of NF-κB in mature T lymphocytes.

Protein kinase C-θ: signaling from the center of the T-cell synapse

The hypothesis that protein kinase C (PKC)-θ plays an important role in T-lymphocyte activation, as indicated by numerous studies in cell lines, was recently confirmed in mice deficient in the expression of this enzyme. In response to TCR stimulation, peripheral T cells lacking PKC-θ failed to activate NF-κB and AP-1, and to express IL-2. This revealed a critical function for this PKC family member in linking membrane-proximal activation cascades to transcriptional responses governing T-cell activation. Although the molecular interactions in which PKC-θ engages have not been fully delineated, insights from a variety of recent studies have permitted new models to be formulated regarding the mechanisms through which it achieves its unique effector functions.

Complementarity and redundancy of IL-22-producing innate lymphoid cells

Intestinal T cells and group 3 innate lymphoid cells (ILC3 cells) control the composition of the microbiota and gut immune responses. Within the gut, ILC3 subsets coexist that either express or lack the natural cytoxicity receptor (NCR) NKp46. We identified here the transcriptional signature associated with the transcription factor T-bet–dependent differentiation of NCR− ILC3 cells into NCR+ ILC3 cells. Contrary to the prevailing view, we found by conditional deletion of the key ILC3 genes Stat3, Il22, Tbx21 and Mcl1 that NCR+ ILC3 cells were redundant for the control of mouse colonic infection with Citrobacter rodentium in the presence of T cells. However, NCR+ ILC3 cells were essential for cecal homeostasis. Our data show that interplay between intestinal ILC3 cells and adaptive lymphocytes results in robust complementary failsafe mechanisms that ensure gut homeostasis.

Teriflunomide Attenuates Immunopathological Changes in the Dark Agouti Rat Model of Experimental Autoimmune Encephalomyelitis

Teriflunomide is an oral disease-modifying therapy recently approved in several locations for relapsing-remitting multiple sclerosis. To gain insight into the effects of teriflunomide, immunocyte population changes were measured during progression of experimental autoimmune encephalomyelitis in Dark Agouti rats. Treatment with teriflunomide attenuated levels of spinal cord-infiltrating T cells, natural killer cells, macrophages, and neutrophils. Teriflunomide also mitigated the disease-induced changes in immune cell populations in the blood and spleen suggesting an inhibitory effect on pathogenic immune responses.

Robust methods for population stratification in genome wide association studies

BackgroundGenome-wide association studies can provide novel insights into diseases of interest, as well as to the responsiveness of an individual to specific treatments. In such studies, it is very important to correct for population stratification, which refers to allele frequency differences between cases and controls due to systematic ancestry differences. Population stratification can cause spurious associations if not adjusted properly. The principal component analysis (PCA) method has been relied upon as a highly useful methodology to adjust for population stratification in these types of large-scale studies. Recently, the linear mixed model (LMM) has also been proposed to account for family structure or cryptic relatedness. However, neither of these approaches may be optimal in properly correcting for sample structures in the presence of subject outliers.ResultsWe propose to use robust PCA combined with k-medoids clustering to deal with population stratification. This approach can adjust for population stratification for both continuous and discrete populations with subject outliers, and it can be considered as an extension of the PCA method and the multidimensional scaling (MDS) method. Through simulation studies, we compare the performance of our proposed methods with several widely used stratification methods, including PCA and MDS. We show that subject outliers can greatly influence the analysis results from several existing methods, while our proposed robust population stratification methods perform very well for both discrete and admixed populations with subject outliers. We illustrate the new method using data from a rheumatoid arthritis study.ConclusionsWe demonstrate that subject outliers can greatly influence the analysis result in GWA studies, and propose robust methods for dealing with population stratification that outperform existing population stratification methods in the presence of subject outliers.

Gene signature-based mapping of immunological systems and diseases

BackgroundThe immune system is multifaceted, structured by diverse components that interconnect using multilayered dynamic cellular processes. Genomic technologies provide a means for investigating, at the molecular level, the adaptations of the immune system in host defense and its dysregulation in pathological conditions. A critical aspect of intersecting and investigating complex datasets is determining how to best integrate genomic data from diverse platforms and heterogeneous sample populations to capture immunological signatures in health and disease.ResultWe focus on gene signatures, representing highly enriched genes of immune cell subsets from both diseased and healthy tissues. From these, we construct a series of biomaps that illustrate the molecular linkages between cell subsets from different lineages, the connectivity between different immunological diseases, and the enrichment of cell subset signatures in diseased tissues. Finally, we overlay the downstream genes of drug targets with disease gene signatures to display the potential therapeutic applications for these approaches.ConclusionAn in silico approach has been developed to characterize immune cell subsets and diseases based on the gene signatures that most differentiate them from other biological states. This modular ‘biomap’ reveals the linkages between different diseases and immune subtypes, and provides evidence for the presence of specific immunocyte subsets in mixed tissues. The over-represented genes in disease signatures of interest can be further investigated for their functions in both host defense and disease.