Chikungunya virus (CHIKV) is an arthritogenic alphavirus causing epidemics of acute and chronic arthritic disease. Herein we describe a comprehensive RNA-Seq analysis of feet and lymph nodes at peak viraemia (day 2 post infection), acute arthritis (day 7) and chronic disease (day 30) in the CHIKV adult wild-type mouse model. Genes previously shown to be up-regulated in CHIKV patients were also up-regulated in the mouse model. CHIKV sequence information was also obtained with up to ≈8% of the reads mapping to the viral genome; however, no adaptive viral genome changes were apparent. Although day 2, 7 and 30 represent distinct stages of infection and disease, there was a pronounced overlap in up-regulated host genes and pathways. Type I interferon response genes (IRGs) represented up to ≈50% of up-regulated genes, even after loss of type I interferon induction on days 7 and 30. Bioinformatic analyses suggested a number of interferon response factors were primarily responsible for maintaining type I IRG induction. A group of genes prominent in the RNA-Seq analysis and hitherto unexplored in viral arthropathies were granzymes A, B and K. Granzyme A-/- and to a lesser extent granzyme K-/-, but not granzyme B-/-, mice showed a pronounced reduction in foot swelling and arthritis, with analysis of granzyme A-/- mice showing no reductions in viral loads but reduced NK and T cell infiltrates post CHIKV infection. Treatment with Serpinb6b, a granzyme A inhibitor, also reduced arthritic inflammation in wild-type mice. In non-human primates circulating granzyme A levels were elevated after CHIKV infection, with the increase correlating with viral load. Elevated granzyme A levels were also seen in a small cohort of human CHIKV patients. Taken together these results suggest granzyme A is an important driver of arthritic inflammation and a potential target for therapy.Trial Registration: ClinicalTrials.gov NCT00281294

The diversity of peptides displayed by class I human leukocyte antigen (HLA) plays an essential role in T cell immunity. The peptide repertoire is extended by various posttranslational modifications, including proteasomal splicing of peptide fragments from distinct regions of an antigen to form nongenomically templated cis-spliced sequences. Previously, it has been suggested that a fraction of the immunopeptidome constitutes such cis-spliced peptides; however, because of computational limitations, it has not been possible to assess whether trans-spliced peptides (i.e., the fusion of peptide segments from distinct antigens) are also bound and presented by HLA molecules, and if so, in what proportion. Here, we have developed and applied a bioinformatic workflow and demonstrated that trans-spliced peptides are presented by HLA-I, and their abundance challenges current models of proteasomal splicing that predict cis-splicing as the most probable outcome. These trans-spliced peptides display canonical HLA-binding sequence features and are as frequently identified as cis-spliced peptides found bound to a number of different HLA-A and HLA-B allotypes. Structural analysis reveals that the junction between spliced peptides is highly solvent exposed and likely to participate in T cell receptor interactions. These results highlight the unanticipated diversity of the immunopeptidome and have important implications for autoimmunity, vaccine design, and immunotherapy.

The availability of large amounts of high-throughput genomic, transcriptomic and epigenomic data has provided opportunity to understand regulation of the cellular transcriptome with an unprecedented level of detail. As a result, research has advanced from identifying gene expression patterns associated with particular conditions to elucidating signalling pathways that regulate expression. There are over 1,000 transcription factors (TFs) in vertebrates that play a role in this regulation. Determining which of these are likely to be controlling a set of genes can be assisted by computational prediction, utilising experimentally verified binding site motifs. Here we present CiiiDER, an integrated computational toolkit for transcription factor binding analysis, written in the Java programming language, to make it independent of computer operating system. It is operated through an intuitive graphical user interface with interactive, high-quality visual outputs, making it accessible to all researchers. CiiiDER predicts transcription factor binding sites (TFBSs) across regulatory regions of interest, such as promoters and enhancers derived from any species. It can perform an enrichment analysis to identify TFs that are significantly over- or under-represented in comparison to a bespoke background set and thereby elucidate pathways regulating sets of genes of pathophysiological importance.

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Infection triggers large-scale changes in the phenotype and function of T cells that are critical for immune clearance, yet the gene regulatory mechanisms that control these changes are largely unknown. Using ChIP-seq for specific histone post-translational modifications (PTMs), we mapped the dynamics of ∼25,000 putative CD8 T cell transcriptional enhancers (TEs) differentially utilized during virus-specific T cell differentiation. Interestingly, we identified a subset of dynamically regulated TEs that exhibited acquisition of a non-canonical (H3K4me3) chromatin signature upon differentiation. This unique TE subset exhibited characteristics of poised enhancers in the naive CD8 T cell subset and demonstrated enrichment for transcription factor binding motifs known to be important for virus-specific CD8 T cell differentiation. These data provide insights into the establishment and maintenance of the gene transcription profiles that define each stage of virus-specific T cell differentiation.

Background The presence of histone 3 lysine 9 (H3K9) methylation on the mouse inactive X chromosome has been controversial over the last 15 years, and the functional role of H3K9 methylation in X chromosome inactivation in any species has remained largely unexplored.ResultsHere we report the first genomic analysis of H3K9 di- and tri-methylation on the inactive X: we find they are enriched at the intergenic, gene poor regions of the inactive X, interspersed between H3K27 tri-methylation domains found in the gene dense regions. Although H3K9 methylation is predominantly non-genic, we find that depletion of H3K9 methylation via depletion of H3K9 methyltransferase Set domain bifurcated 1 (Setdb1) during the establishment of X inactivation, results in failure of silencing for around 150 genes on the inactive X. By contrast, we find a very minor role for Setdb1-mediated H3K9 methylation once X inactivation is fully established. In addition to failed gene silencing, we observed a specific failure to silence X-linked long-terminal repeat class repetitive elements.ConclusionsHere we have shown that H3K9 methylation clearly marks the murine inactive X chromosome. The role of this mark is most apparent during the establishment phase of gene silencing, with a more muted effect on maintenance of the silent state. Based on our data, we hypothesise that Setdb1-mediated H3K9 methylation plays a role in epigenetic silencing of the inactive X via silencing of the repeats, which itself facilitates gene silencing through alterations to the conformation of the whole inactive X chromosome.Electronic supplementary materialThe online version of this article (doi:10.1186/s13072-016-0064-6) contains supplementary material, which is available to authorized users.

Pooled short hairpin RNA sequencing (shRNA-seq) screens are becoming increasingly popular in functional genomics research, and there is a need to establish optimal analysis tools to handle such data. Our open-source shRNA processing pipeline in edgeR provides a complete analysis solution for shRNA-seq screen data, that begins with the raw sequence reads and ends with a ranked lists of candidate shRNAs for downstream biological validation. We first summarize the raw data contained in a fastq file into a matrix of counts (samples in the columns, hairpins in the rows) with options for allowing mismatches and small shifts in hairpin position. Diagnostic plots, normalization and differential representation analysis can then be performed using established methods to prioritize results in a statistically rigorous way, with the choice of either the classic exact testing methodology or a generalized linear modelling that can handle complex experimental designs. A detailed users' guide that demonstrates how to analyze screen data in edgeR along with a point-and-click implementation of this workflow in Galaxy are also provided. The edgeR package is freely available from http://www.bioconductor.org.

Mitochondria are important regulators of macrophage polarisation. Here, we show that arginase-2 (Arg2) is a microRNA-155 (miR-155) and interleukin-10 (IL-10) regulated protein localized at the mitochondria in inflammatory macrophages, and is critical for IL-10-induced modulation of mitochondrial dynamics and oxidative respiration. Mechanistically, the catalytic activity and presence of Arg2 at the mitochondria is crucial for oxidative phosphorylation. We further show that Arg2 mediates this process by increasing the activity of complex II (succinate dehydrogenase). Moreover, Arg2 is essential for IL-10-mediated downregulation of the inflammatory mediators succinate, hypoxia inducible factor 1α (HIF-1α) and IL-1β in vitro. Accordingly, HIF-1α and IL-1β are highly expressed in an LPS-induced in vivo model of acute inflammation using Arg2−/− mice. These findings shed light on a new arm of IL-10-mediated metabolic regulation, working to resolve the inflammatory status of the cell.