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Objective: We undertook this study to evaluate the activation and functional relevance of inflammasome pathways in ankylosing spondylitis (AS) patients and rodent models and their relationship to dysbiosis. Methods: An inflammasome pathway was evaluated in the gut and peripheral blood from 40 AS patients using quantitative reverse transcriptase–polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC), flow cytometry, and confocal microscopy, and was compared to that of 20 healthy controls and 10 patients with Crohn’s disease. Bacteria was visualized using silver stain in human samples, and antibiotics were administered to HLA–B27–transgenic rats. The NLRP3 inhibitor MCC950 was administered to SKG mice, and ileal and joint tissues were assessed by IHC analysis and real-time qRT-PCR. The role of inflammasome in modulating the interleukin-23 (IL-23)/IL-17 axis was studied ex vivo. Results: Expression levels of Nlrp3, Nlrc4, and Aim2 were increased in the gut of HLA–B27–transgenic rats and reduced by antibiotic treatment (P < 0.05). In curdlan-treated SKG mice, NLRP3 blockade prevented ileitis and delayed arthritis onset (P < 0.05). Compared to healthy controls, AS patients demonstrated overexpression of NLRP3 (fold induction 2.33 versus 22.2; P < 0.001), NLRC4 (fold induction 1.90 versus 6.47; P < 0.001), AIM2 (fold induction 2.40 versus 20.8; P < 0.001), CASP1 (fold induction 2.53 versus 24.8; P < 0.001), IL1B (fold induction 1.07 versus 10.93; P < 0.001), and IL18 (fold induction 2.56 versus 15.67; P < 0.001) in the ileum, and caspase 1 activity was increased (P < 0.01). The score of adherent and invasive mucosa-associated bacteria was higher in AS (P < 0.01) and correlated with the expression of inflammasome components in peripheral blood mononuclear cells (P < 0.001). NLRP3 expression was associated with disease activity (the Ankylosing Spondylitis Disease Activity Score using the C-reactive protein level) (r2 = 0.28, P

Pleural mesothelioma is a cancer of serosal surfaces caused by environmental exposure to asbestos. Clinical outcome remains poor and while trials of new treatments are ongoing it remains an understudied cancer. Mesothelioma cell lines can readily be grown from primary tumour and from tumour cells shed into pleural effusion with the latter representing a particularly valuable source of DNA in clinical settings, procurable without the need for additional invasive procedures. However, it is not well understood how accurately patient-derived cultured tumour cells represent the molecular characteristics of their primary tumour. We used whole-genome sequencing of primary tumour and matched cultured cells to comprehensively characterize mutations and structural alterations. Most cases had complex rearranged genomes with evidence of chromoanagenesis and rearrangements reminiscent of chromoplexy. Many of the identified driver mutations were structural, indicating that mesothelioma is often caused by structural alterations and catastrophic genomic events, rather than point mutations. Because the majority of genomic changes detected in tumours were also displayed by the genomes of cultured tumour cells, we conclude that low-passage cultured tumour cells are generally suitable for molecular characterization of mesothelioma and may be particularly useful where tissue samples with high tumour cell content are not available. However, the subclonal compositions of the cell lines did not fully recapitulate the subclonal diversity of the primary tumours. Furthermore, longitudinal acquisition of major alterations in subclonal cell populations was observed after long-term passaging. These two factors define limitations of tumour-derived cell lines as genomic substrate for clinical purposes.

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page.

Background: Infection with the Epstein-Barr virus (EBV) is associated with an increased risk of multiple sclerosis (MS). Objective: We sought genetic loci influencing EBV nuclear antigen-1 (EBNA-1) IgG titers and hypothesized that they may play a role in MS risk. Methods: We performed a genome-wide association study (GWAS) of anti-EBNA-1 IgG titers in 3599 individuals from an unselected twin family cohort, followed by a meta-analysis with data from an independent EBNA-1 GWAS. We then examined the shared polygenic risk between the EBNA-1 GWAS (effective sample size (Neff) = 5555) and a large MS GWAS (Neff = 15,231). Results: We identified one locus of strong association within the human leukocyte antigen (HLA) region, of which the most significantly associated genotyped single nucleotide polymorphism (SNP) was rs2516049 (p = 4.11 × 10-9). A meta-analysis including data from another EBNA-1 GWAS in a cohort of Mexican-American families confirmed that rs2516049 remained the most significantly associated SNP (p = 3.32 × 10-20). By examining the shared polygenic risk, we show that the genetic risk for elevated anti-EBNA-1 titers is positively correlated with the development of MS, and that elevated EBNA-1 titers are not an epiphenomena secondary to MS. In the joint meta-analysis of EBNA-1 titers and MS, loci at 1p22.1, 3p24.1, 3q13.33, and 10p15.1 reached genome-wide significance (p < 5 × 10-8). Conclusions: Our results suggest that apart from the confirmed HLA region, the association of anti-EBNA-1 IgG titer with MS risk is also mediated through non-HLA genes, and that studies aimed at identifying genetic loci influencing EBNA immune response provides a novel opportunity to identify new and characterize existing genetic risk factors for MS.

Phosphorylation by the cyclin-dependent kinase 1 (Cdk1) adjacent to nuclear localization signals (NLSs) is an important mechanism of regulation of nucleocytoplasmic transport. However, no systematic survey has yet been performed in human cells to analyze this regulatory process, and the corresponding cell-cycle dynamics have not yet been investigated. Here, we focused on the human proteome and found that numerous proteins, previously not identifi ed in this context, are associated with Cdk1-dependent phosphorylation sites adjacent to their NLSs. Interestingly, these proteins are involved in key regulatory events of DNA repair, epigenetics, or RNA editing and splicing. This finding indicates that cell-cycle dependent events of genome editing and gene expression profiling may be controlled by nucleocytoplasmic trafficking. For in-depth investigations, we selected a number of these proteins and analyzed how point mutations, expected to modify the phosphorylation ability of the NLS segments, perturb nucleocytoplasmic localization. In each case, we found that mutations mimicking hyper-phosphorylation abolish nuclear import processes. To understand the mechanism underlying these phenomena, we performed a video microscopy-based kinetic analysis to obtain information on cell-cycle dynamics on a model protein, dUTPase. We show that the NLS-adjacent phosphorylation by Cdk1 of human dUTPase, an enzyme essential for genomic integrity, results in dynamic cell cycle-dependent distribution of the protein. Non-phosphorylatable mutants have drastically altered protein re-import characteristics into the nucleus during the G1 phase. Our results suggest a dynamic Cdk1-driven mechanism of regulation of the nuclear proteome composition during the cell cycle.

Background: CD4+ T-cell epitopes play a crucial role in eliciting vigorous protective immune responses during peptide (epitope)-based vaccination. The prediction of these epitopes focuses on the peptide binding process by MHC class II proteins. The ability to account for MHC class II polymorphism is critical for epitope-based vaccine design tools, as different allelic variants can have different peptide repertoires. In addition, the specificity of CD4+ T-cells is often directed to a very limited set of immunodominant peptides in pathogen proteins. The ability to predict what epitopes are most likely to dominate an immune response remains a challenge.Results: We developed the computational tool Predivac to predict CD4+ T-cell epitopes. Predivac can make predictions for 95% of all MHC class II protein variants (allotypes), a substantial advance over other available methods. Predivac bases its prediction on the concept of specificity-determining residues. The performance of the method was assessed both for high-affinity HLA class II peptide binding and CD4+ T-cell epitope prediction. In terms of epitope prediction, Predivac outperformed three available pan-specific approaches (delivering the highest specificity). A central finding was the high accuracy delivered by the method in the identification of immunodominant and promiscuous CD4+ T-cell epitopes, which play an essential role in epitope-based vaccine design.Conclusions: The comprehensive HLA class II allele coverage along with the high specificity in identifying immunodominant CD4+ T-cell epitopes makes Predivac a valuable tool to aid epitope-based vaccine design in the context of a genetically heterogeneous human population.The tool is available at: http://predivac.biosci.uq.edu.au/.

Background: Smchd1 is an epigenetic modifier essential for X chromosome inactivation: female embryos lacking Smchd1 fail during midgestational development. Male mice are less affected by Smchd1-loss, with some (but not all) surviving to become fertile adu

Background: Ever since the ground-breaking work of Anfinsen et al. in which a denatured protein was found to refold to its native state, it has been frequently stated by the protein fold prediction community that all the information required for protein folding lies in the amino acid sequence. Recent in vitro experiments and in silico computational studies, however, have shown that cotranslation may affect the folding pathway of some proteins, especially those of ancient folds. In this paper aspects of cotranslational folding have been incorporated into a protein structure prediction algorithm by adapting the Rosetta program to fold proteins as the nascent chain elongates. This makes it possible to conduct a pairwise comparison of folding accuracy, by comparing folds created sequentially from each end of the protein.Results: A single main result emerged: in 94% of proteins analyzed, following the sense of translation, from N-terminus to C-terminus, produced better predictions than following the reverse sense of translation, from the C-terminus to N-terminus. Two secondary results emerged. First, this superiority of N-terminus to C-terminus folding was more marked for proteins showing stronger evidence of cotranslation and second, an algorithm following the sense of translation produced predictions comparable to, and occasionally better than, Rosetta.Conclusions: There is a directionality effect in protein fold prediction. At present, prediction methods appear to be too noisy to take advantage of this effect; as techniques refine, it may be possible to draw benefit from a sequential approach to protein fold prediction.

Many protein-RNA recognition events are known to exhibit conformational changes from qualitative observations of individual complexes. However, a quantitative estimation of conformational changes is required if protein-RNA docking and template-based methods for RNA binding site prediction are to be developed. This study presents the first quantitive evaluation of conformational changes that occur when proteins bind RNA. The analysis of twelve RNA-binding proteins in the bound and unbound states using error-scaled difference distance matrices is presented. The binding site residues are mapped to each structure, and the conformational changes that affect these residues are evaluated. Of the twelve proteins four exhibit greater movements in nonbinding site residues, and a further four show the greatest movements in binding site residues. The remaining four proteins display no significant conformational change. When interface residues are found to be in conformationally variable regions of the protein they are typically seen to move less than 2 Å between the bound and unbound conformations. The current data indicate that conformational changes in the binding site residues of RNA binding proteins may not be as significant as previously suggested, but a larger data set is required before wider conclusions may be drawn. The implications of the observed conformational changes for protein function prediction are discussed.

A data set of 89 protein-RNA complexes has been extracted from the Protein Data Bank, and the nucleic acid recognition sites characterized through direct contacts, accessible surface area, and secondary structure motifs. The differences between RNA recognition sites that bind to RNAs in functional classes has also been analyzed. Analysis of the complete data set revealed that van der Waals interactions are more numerous than hydrogen bonds and the contacts made to the nucleic acid backbone occur more frequently than specific contacts to nucleotide bases. Of the base-specific contacts that were observed, contacts to guanine and adenine occurred most frequently. The most favored amino acid-nucleotide pairings observed were lysine-phosphate, tyrosine-uracil, arginine-phosphate, phenylalanine-adenine and tryptophan-guanine. The amino acid propensities showed that positively charged and polar residues were favored as expected, but also so were tryptophan and glycine. The propensities calculated for the functional classes showed trends similar to those observed for the complete data set. However, the analysis of hydrogen bond and van der Waal contacts showed that in general proteins complexed with messenger RNA, transfer RNA and viral RNA have more base specific contacts and less backbone contacts than expected, while proteins complexed with ribosomal RNA have less base-specific contacts than the expected. Hence, whilst the types of amino acids involved in the interfaces are similar, the distribution of specific contacts is dependent upon the functional class of the RNA bound.