Characterization of Burkholderia rhizoxinica and B. endofungorum Isolated from Clinical Specimens

Eight isolates submitted to CDC from 1989 to 2006 from clinical specimens were initially identified as members of the genus Burkholderia based on preliminary cellular fatty acid analysis and/or 16S rRNA gene sequencing. With the recent descriptions of the new species B. rhizoxinica and B. endofungorum, which are considered endosymbiotic bacteria in Rhizopus microsporus fungi, we now identify seven of these clinical isolates as B. rhizoxinica and one as B. endofungorum based on biochemical testing, 16s rRNA, and DNA-DNA hybridization results. We also further characterize these isolates by assessing toxin production and/or by multiple locus sequence typing

Cryptic Polyketide Synthase Genes in Non-Pathogenic Clostridium SPP

Modular type I polyketide synthases (PKS) produce a vast array of bacterial metabolites with highly diverse biological functions. Notably, all known polyketides were isolated from aerobic bacteria, and yet no example has been reported for strict anaerobes. In this study we explored the diversity and distribution of PKS genes in the genus Clostridium. In addition to comparative genomic analyses combined with predictions of modular type I polyketide synthase (PKS) gene clusters in sequenced genomes of Clostridium spp., a representative selection of other species inhabiting a variety of ecological niches was investigated by PCR screening for PKS genes. Our data reveal that all studied pathogenic Clostridium spp. are devoid of putative PKS genes. In stark contrast, cryptic PKS genes are widespread in genomes of non-pathogenic Clostridium species. According to phylogenetic analyses, the Clostridium PKS genes have unusual and diverse origins. However, reverse transcription quantitative PCR demonstrates that these genes are silent under standard cultivation conditions, explaining why the related metabolites have been overlooked until now. This study presents clostridia as a putative source for novel bioactive polyketides

The Cyclophilin-Binding Agent Sanglifehrin A Is a Dendritic Cell Chemokine and Migration Inhibitor

Sanglifehrin A (SFA) is a cyclophilin-binding immunosuppressant but the immunobiology of action is poorly understood. We and others have reported that SFA inhibits IL-12 production and antigen uptake in dendritic cells (DC) and exhibits lower activity against lymphocytes. Here we show that SFA suppresses DC chemokine production and migration. Gene expression analysis and subsequent protein level confirmation revealed that SFA suppressed CCL5, CCL17, CCL19, CXCL9 and CXCL10 expression in human monocyte-derived DC (moDC). A systems biology analysis, Onto Express, confirmed that SFA interferes with chemokine-chemokine receptor gene expression with the highest impact. Direct comparison with the related agent cyclosporine A (CsA) and dexamethasone indicated that SFA uniquely suppresses moDC chemokine expression. Competitive experiments with a 100-fold molar excess of CsA and with N-Methyl-Val-4-cyclosporin, representing a nonimmunosuppressive derivative of CsA indicated chemokine suppression through a cyclophilin-A independent pathway. Functional assays confirmed reduced migration of CD4+ Tcells and moDCs to supernatant of SFA-exposed moDCs. Vice versa, SFA-exposed moDC exhibited reduced migration against CCL19. Moreover, SFA suppressed expression of the ectoenzyme CD38 that was reported to regulate DC migration and cytokine production. These results identify SFA as a DC chemokine and migration inhibitor and provide novel insight into the immunobiology of SFA

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN

The genetics of myopia

Myopia is the most common eye condition worldwide and its prevalence is increasing. While changes in environment, such as time spent outdoors, have driven myopia rates, within populations myopia is highly heritable. Genes are estimated to explain up to 80% of the variance in refractive error. Initial attempts to identify myopia genes relied on family studies using linkage analysis or candidate gene approaches with limited progress. More genome-wide association study (GWAS) approaches have taken over, ultimately resulting in the identification of hundreds of genes for refractive error and myopia, providing new insights into its molecular machinery. These studies showed myopia is a complex trait, with many genetic variants of small effect influencing retinal signaling, eye growth and the normal process of emmetropization. The genetic architecture and its molecular mechanisms are still to be clarified and while genetic risk score prediction models are improving, this knowledge must be expanded to have impact on clinical practice

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk