Objective The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns. Results The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.

Abstract Epigenetic changes have likely contributed to the large size and enhanced cognitive abilities of the human brain which evolved within the last 2 million years after the human‐chimpanzee split. Using reduced representation bisulfite sequencing, we have compared the methylomes of neuronal and non‐neuronal cells from 3 human and 3 chimpanzee cortices. Differentially methylated regions (DMRs) with genome‐wide significance were enriched in specific genomic regions. Intraspecific methylation differences between neuronal and non‐neuronal cells were approximately 3 times more abundant than interspecific methylation differences between human and chimpanzee cell types. The vast majority (>90%) of human intraspecific DMRs (including DMRs in retrotransposons) were hypomethylated in neurons, compared with glia. Intraspecific DMRs were enriched in genes associated with different neuropsychiatric disorders. Interspecific DMRs were enriched in genes showing human‐specific brain histone modifications. Human‐chimpanzee methylation differences were much more frequent in non‐neuronal cells (n. DMRs = 666) than in neurons (n. DMRs = 96). More than 95% of interspecific DMRs in glia were hypermethylated in humans. Although without an outgroup we cannot assign whether a change in methylation occurred in the human or chimpanzee lineage, our results are consistent with a wave of methylation affecting several hundred non‐neuronal genes during human brain evolution.

Staphylococcus aureus is a major bacterial pathogen, which causes severe blood and tissue infections that frequently emerge by autoinfection with asymptomatically carried nose and skin populations. However, recent studies report that bloodstream isolates differ systematically from those found in the nose and skin, exhibiting reduced toxicity toward leukocytes. In two patients, an attenuated toxicity bloodstream infection evolved from an asymptomatically carried high-toxicity nasal strain by loss-of-function mutations in the gene encoding the transcription factor repressor of surface proteins (rsp). Here, we report that rsp knockout mutants lead to global transcriptional and proteomic reprofiling, and they exhibit the greatest signal in a genome-wide screen for genes influencing S. aureus survival in human cells. This effect is likely to be mediated in part via SSR42, a long-noncoding RNA. We show that rsp controls SSR42 expression, is induced by hydrogen peroxide, and is required for normal cytotoxicity and hemolytic activity. Rsp inactivation in laboratory-and bacteremiaderived mutants attenuates toxin production, but up-regulates other immune subversion proteins and reduces lethality during experimental infection. Crucially, inactivation of rsp preserves bacterial dissemination, because it affects neither formation of deep abscesses in mice nor survival in human blood. Thus, we have identified a spontaneously evolving, attenuated-cytotoxicity, nonhemolytic S. aureus phenotype, controlled by a pleiotropic transcriptional regulator/noncoding RNA virulence regulatory system, capable of causing S. aureus bloodstream infections. Such a phenotype could promote deep infection with limited early clinical manifestations, raising concerns that bacterial evolution within the human body may contribute to severe infection.

Community-acquired (CA) Staphylococcus aureus cause various diseases even in healthy individuals. Enhanced virulence of CA-strains is partly attributed to increased production of toxins such as phenol-soluble modulins (PSM). The pathogen is internalized efficiently by mammalian host cells and intracellular S. aureus has recently been shown to contribute to disease. Upon internalization, cytotoxic S. aureus strains can disrupt phagosomal membranes and kill host cells in a PSM-dependent manner. However, PSM are not sufficient for these processes. Here we screened for factors required for intracellular S. aureus virulence. We infected escape reporter host cells with strains from an established transposon mutant library and detected phagosomal escape rates using automated microscopy. We thereby, among other factors, identified a non-ribosomal peptide synthetase (NRPS) to be required for efficient phagosomal escape and intracellular survival of S. aureus as well as induction of host cell death. By genetic complementation as well as supplementation with the synthetic NRPS product, the cyclic dipeptide phevalin, wild-type phenotypes were restored. We further demonstrate that the NRPS is contributing to virulence in a mouse pneumonia model. Together, our data illustrate a hitherto unrecognized function of the S. aureus NRPS and its dipeptide product during S. aureus infection.

Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi human and fungi mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host fungi transcriptome and proteome data.

A current challenge for transcriptomic analysis is the extraction of biological meaning. We assessed and adapted multivariate ecological methods for transcriptomic data, which are widely used to discover associations between species and sample covariates: RLQ visualizes associations within and between covariates whereas the fourth-corner analysis (4CA) identifies significance of the associations. We used these methods to discover associations between patient phenotypes and gene functions and demonstrated their high potential to unravel complex relationships in large-scale transcriptomic data.

BACKGROUND Long noncoding ribonucleic acids (lncRNAs) are a subclass of regulatory noncoding ribonucleic acids for which expression and function in human endothelial cells and angiogenic processes is not well studied.OBJECTIVES The authors discovered hypoxia-sensitive human lncRNAs via next-generation ribonucleic acid sequencing and microarray approaches. To address their functional importance in angiogenic processes, several endothelial lncRNAs were characterized for their angiogenic characteristics in vitro and ex vivo.METHODS Ribonucleic acid sequencing and microarray-derived data showed specific endothelial lncRNA expression changes after hypoxia. Validation experiments confirmed strong hypoxia-dependent activation of 2 intergenic lncRNAs: LINC00323 and MIR503HG.RESULTS Silencing of these lncRNA transcripts led to angiogenic defects, including repression of growth factor signaling and/or the key endothelial transcription factor GATA2. Endothelial loss of these hypoxia-driven lncRNAs impaired cell-cycle control and inhibited capillary formation. The potential clinical importance of these endothelial lncRNAs to vascular structural integrity was demonstrated in an ex vivo model of human induced pluripotent stem cell-based engineered heart tissue.CONCLUSIONS The authors report an expression atlas of human hypoxia-sensitive lncRNAs and identified 2 lncRNAs with important functions to sustain endothelial cell biology. LncRNAs hold great promise to serve as important future therapeutic targets of cardiovascular disease. (C) 2015 by the American College of Cardiology Foundation.

The WHO has recently classified Neisseria gonorrhoeae as a super-bacterium due to the rapid spread of antibiotic resistant derivatives and an overall dramatic increase in infection incidences. Genome sequencing has identified potential genes, however, little is known about the transcriptional organization and the presence of non-coding RNAs in gonococci. We performed RNA sequencing to define the transcriptome and the transcriptional start sites of all gonococcal genes and operons. Numerous new transcripts including 253 potentially non-coding RNAs transcribed from intergenic regions or antisense to coding genes were identified. Strikingly, strong antisense transcription was detected for the phase-variable opa genes coding for a family of adhesins and invasins in pathogenic Neisseria, that may have regulatory functions. Based on the defined transcriptional start sites, promoter motifs were identified. We further generated and sequenced a high density Tn5 transposon library to predict a core of 827 gonococcal essential genes, 133 of which have no known function. Our combined RNA-Seq and Tn-Seq approach establishes a detailed map of gonococcal genes and defines the first core set of essential gonococcal genes.