Systematic classification of non-coding RNAs by epigenomic similarity

BACKGROUND: Even though only 1.5% of the human genome is translated into proteins, recent reports indicate that most of it is transcribed into non-coding RNAs (ncRNAs), which are becoming the subject of increased scientific interest. We hypothesized that examining how different classes of ncRNAs co-localized with annotated epigenomic elements could help understand the functions, regulatory mechanisms, and relationships among ncRNA families. RESULTS: We examined 15 different ncRNA classes for statistically significant genomic co-localizations with cell type-specific chromatin segmentation states, transcription factor binding sites (TFBSs), and histone modification marks using GenomeRunner (http://www.genomerunner.org). P-values were obtained using a Chi-square test and corrected for multiple testing using the Benjamini-Hochberg procedure. We clustered and visualized the ncRNA classes by the strength of their statistical enrichments and depletions. We found piwi-interacting RNAs (piRNAs) to be depleted in regions containing activating histone modification marks, such as H3K4 mono-, di- and trimethylation, H3K27 acetylation, as well as certain TFBSs. piRNAs were further depleted in active promoters, weak transcription, and transcription elongation regions, and enriched in repressed and heterochromatic regions. Conversely, transfer RNAs (tRNAs) were depleted in heterochromatin regions and strongly enriched in regions containing activating H3K4 di- and trimethylation marks, H2az histone variant, and a variety of TFBSs. Interestingly, regions containing CTCF insulator protein binding sites were associated with tRNAs. tRNAs were also enriched in the active, weak and poised promoters and, surprisingly, in regions with repetitive/copy number variations. CONCLUSIONS: Searching for statistically significant associations between ncRNA classes and epigenomic elements permits detection of potential functional and/or regulatory relationships among ncRNA classes, and suggests cell type-specific biological roles of ncRNAs

Suppression of ILC2 differentiation from committed T cell precursors by E protein transcription factors

Current models propose that group 2 innate lymphoid cells (ILC2s) are generated in the bone marrow. Here, we demonstrate that subsets of these cells can differentiate from multipotent progenitors and committed T cell precursors in the thymus, both in vivo and in vitro. These thymic ILC2s exit the thymus, circulate in the blood, and home to peripheral tissues. Ablation of E protein transcription factors greatly promotes the ILC fate while impairing B and T cell development. Consistently, a transcriptional network centered on the ZBTB16 transcription factor and IL-4 signaling pathway is highly up-regulated due to E protein deficiency. Our results show that ILC2 can still arise from what are normally considered to be committed T cell precursors, and that this alternative cell fate is restrained by high levels of E protein activity in these cells. Thymus-derived lung ILC2s of E protein-deficient mice show different transcriptomes, proliferative properties, and cytokine responses from wild-type counterparts, suggesting potentially distinct functions

Extending the mutual information measure to rank inferred literature relationships

BACKGROUND: Within the peer-reviewed literature, associations between two things are not always recognized until commonalities between them become apparent. These commonalities can provide justification for the inference of a new relationship where none was previously known, and are the basis of most observation-based hypothesis formation. It has been shown that the crux of the problem is not finding inferable associations, which are extraordinarily abundant given the scale-free networks that arise from literature-based associations, but determining which ones are informative. The Mutual Information Measure (MIM) is a well-established method to measure how informative an association is, but is limited to direct (i.e. observable) associations. RESULTS: Herein, we attempt to extend the calculation of mutual information to indirect (i.e. inferable) associations by using the MIM of shared associations. Objects of general research interest (e.g. genes, diseases, phenotypes, drugs, ontology categories) found within MEDLINE are used to create a network of associations for evaluation. CONCLUSIONS: Mutual information calculations can be effectively extended into implied relationships and a significance cutoff estimated from analysis of random word networks. Of the models tested, the shared minimum MIM (MMIM) model is found to correlate best with the observed strength and frequency of known associations. Using three test cases, the MMIM method tends to rank more specific relationships higher than counting the number of shared relationships within a network

Para-cresol production by Clostridium difficile affects microbial diversity and membrane integrity of Gram-negative bacteria

Clostridium difficile is a Gram-positive spore-forming anaerobe and a major cause of antibiotic-associated diarrhoea. Disruption of the commensal microbiota, such as through treatment with broad-spectrum antibiotics, is a critical precursor for colonisation by C. difficile and subsequent disease. Furthermore, failure of the gut microbiota to recover colonisation resistance can result in recurrence of infection. An unusual characteristic of C. difficile among gut bacteria is its ability to produce the bacteriostatic compound para-cresol (p-cresol) through fermentation of tyrosine. Here, we demonstrate that the ability of C. difficile to produce p-cresol in vitro provides a competitive advantage over gut bacteria including Escherichia coli, Klebsiella oxytoca and Bacteroides thetaiotaomicron. Metabolic profiling of competitive co-cultures revealed that acetate, alanine, butyrate, isobutyrate, p-cresol and p-hydroxyphenylacetate were the main metabolites responsible for differentiating the parent strain C. difficile (630Δerm) from a defined mutant deficient in p-cresol production. Moreover, we show that the p-cresol mutant displays a fitness defect in a mouse relapse model of C. difficile infection (CDI). Analysis of the microbiome from this mouse model of CDI demonstrates that colonisation by the p-cresol mutant results in a distinctly altered intestinal microbiota, and metabolic profile, with a greater representation of Gammaproteobacteria, including the Pseudomonales and Enterobacteriales. We demonstrate that Gammaproteobacteria are susceptible to exogenous p-cresol in vitro and that there is a clear divide between bacterial Phyla and their susceptibility to p-cresol. In general, Gram-negative species were relatively sensitive to p-cresol, whereas Gram-positive species were more tolerant. This study demonstrates that production of p-cresol by C. difficile has an effect on the viability of intestinal bacteria as well as the major metabolites produced in vitro. These observations are upheld in a mouse model of CDI, in which p-cresol production affects the biodiversity of gut microbiota and faecal metabolite profiles, suggesting that p-cresol production contributes to C. difficile survival and pathogenesis.Peer reviewedFinal Published versio

Truth, Probability, and Frameworks

Yeshttp://www.plosmedicine.org/static/editorial#pee

PDGFRα signaling drives adipose tissue fibrosis by targeting progenitor cell plasticity

Fibrosis is a common disease process in which profibrotic cells disturb organ function by secreting disorganized extracellular matrix (ECM). Adipose tissue fibrosis occurs during obesity and is associated with metabolic dysfunction, but how profibrotic cells originate is still being elucidated. Here, we use a developmental model to investigate perivascular cells in white adipose tissue (WAT) and their potential to cause organ fibrosis. We show that a Nestin-Cre transgene targets perivascular cells (adventitial cells and pericyte-like cells) in WAT, and Nestin-GFP specifically labels pericyte-like cells. Activation of PDGFRα signaling in perivascular cells causes them to transition into ECM-synthesizing profibrotic cells. Before this transition occurs, PDGFRα signaling up-regulates mTOR signaling and ribosome biogenesis pathways and perturbs the expression of a network of epigenetically imprinted genes that have been implicated in cell growth and tissue homeostasis. Isolated Nestin-GFP+ cells differentiate into adipocytes ex vivo and form WAT when transplanted into recipient mice. However, PDGFRα signaling opposes adipogenesis and generates profibrotic cells instead, which leads to fibrotic WAT in transplant experiments. These results identify perivascular cells as fibro/adipogenic progenitors in WAT and show that PDGFRα targets progenitor cell plasticity as a profibrotic mechanism

Data-Mining Analysis Suggests an Epigenetic Pathogenesis for Type 2 Diabetes

The etiological origin of type 2 diabetes mellitus (T2DM) has long been controversial. The body of literature related to T2DM is vast and varied in focus, making a broad epidemiological perspective difficult, if not impossible. A data-mining approach was used to analyze all electronically available scientific literature, over 12 million Medline records, for “objects” such as genes, diseases, phenotypes, and chemical compounds linked to other objects within the T2DM literature but were not themselves within the T2DM literature. The goal of this analysis was to conduct a comprehensive survey to identify novel factors implicated in the pathology of T2DM by statistically evaluating mutually shared associations. Surprisingly, epigenetic factors were among the highest statistical scores in this analysis, strongly implicating epigenetic changes within the body as causal factors in the pathogenesis of T2DM. Further analysis implicates adipocytes as the potential tissue of origin, and cytokines or cytokine-like genes as the dysregulated factor(s) responsible for the T2DM phenotype. The analysis provides a wealth of literature supporting this hypothesis, which—if true—represents an important paradigm shift for researchers studying the pathogenesis of T2DM

The Life Science Exchange: a case study of a sectoral and sub-sectoral knowledge exchange programme

Background: Local and national governments have implemented sector-specific policies to support economic development through innovation, entrepreneurship and knowledge exchange. Supported by the Welsh Government through the European Regional Development Fund, The Life Science Exchange® project was created with the aim to increase interaction between stakeholders, to develop more effective knowledge exchange mechanisms, and to stimulate the formation and maintenance of long-term collaborative relationships within the Welsh life sciences ecosystem. The Life Science Exchange allowed participants to interact with other stakeholder communities (clinical, academic, business, governmental), exchange perspectives and discover new opportunities.Methods: Six sub-sector focus groups comprising over 200 senior stakeholders from academia, industry, the Welsh Government and National Health Service were established. Over 18 months, each focus group provided input to inform healthcare innovation policy and knowledge mapping exercises of their respective sub-sectors. Collaborative projects identified during the focus groups and stakeholder engagement were further developed through sandpit events and bespoke support.Results: Each sub-sector focus group produced a report outlining the significant strengths and opportunities in their respective areas of focus, made recommendations to overcome any ‘system failures’, and identified the stakeholder groups which needed to take action. A second outcome was a stakeholder-driven knowledge mapping exercise for each area of focus. Finally, the sandpit events and bespoke support resulted in participants generating more than £1.66 million in grant funding and inward investment. This article outlines four separate outcomes from the Life Science Exchange programme.Conclusions: The Life Science Exchange process has resulted in a multitude of collaborations, projects, inward investment opportunities and special interest group formations, in addition to securing over ten times its own costs in funding for Wales. The Life Science Exchange model is a simple and straightforward mechanism for a regional or national government to adapt and implement in order to improve innovation, skills, networks and knowledge exchange