TREEOME: A framework for epigenetic and transcriptomic data integration to explore regulatory interactions controlling transcription

Motivation: Predictive modelling of gene expression is a powerful framework for the in silico exploration of transcriptional regulatory interactions through the integration of high-throughput -omics data. A major limitation of previous approaches is their inability to handle conditional and synergistic interactions that emerge when collectively analysing genes subject to different regulatory mechanisms. This limitation reduces overall predictive power and thus the reliability of downstream biological inference. Results: We introduce an analytical modelling framework (TREEOME: tree of models of expression) that integrates epigenetic and transcriptomic data by separating genes into putative regulatory classes. Current predictive modelling approaches have found both DNA methylation and histone modification epigenetic data to provide little or no improvement in accuracy of prediction of transcript abundance despite, for example, distinct anti-correlation between mRNA levels and promoter-localised DNA methylation. To improve on this, in TREEOME we evaluate four possible methods of formulating gene-level DNA methylation metrics, which provide a foundation for identifying gene-level methylation events and subsequent differential analysis, whereas most previous techniques operate at the level of individual CpG dinucleotides. We demonstrate TREEOME by integrating gene-level DNA methylation (bisulfite-seq) and histone modification (ChIP-seq) data to accurately predict genome-wide mRNA transcript abundance (RNA-seq) for H1-hESC and GM12878 cell lines. Availability: TREEOME is implemented using open-source software and made available as a pre-configured bootable reference environment. All scripts and data presented in this study are available online at http://sourceforge.net/projects/budden2015treeome/.Comment: 14 pages, 6 figure

Allosteric activation of the nitric oxide receptor soluble guanylate cyclase mapped by cryo-electron microscopy.

Soluble guanylate cyclase (sGC) is the primary receptor for nitric oxide (NO) in mammalian nitric oxide signaling. We determined structures of full-length Manduca sexta sGC in both inactive and active states using cryo-electron microscopy. NO and the sGC-specific stimulator YC-1 induce a 71° rotation of the heme-binding β H-NOX and PAS domains. Repositioning of the β H-NOX domain leads to a straightening of the coiled-coil domains, which, in turn, use the motion to move the catalytic domains into an active conformation. YC-1 binds directly between the β H-NOX domain and the two CC domains. The structural elongation of the particle observed in cryo-EM was corroborated in solution using small angle X-ray scattering (SAXS). These structures delineate the endpoints of the allosteric transition responsible for the major cyclic GMP-dependent physiological effects of NO

Complete Genome Sequence of Clostridium estertheticum DSM 8809, a Microbe Identified in Spoiled Vacuum Packed Beef

peer-reviewedBlown pack spoilage (BPS) is a major issue for the beef industry. Etiological agents of BPS involve members of a group of Clostridium species, including Clostridium estertheticum which has the ability to produce gas, mostly carbon dioxide, under anaerobic psychotrophic growth conditions. This spore-forming bacterium grows slowly under laboratory conditions, and it can take up to 3 months to produce a workable culture. These characteristics have limited the study of this commercially challenging bacterium. Consequently information on this bacterium is limited and no effective controls are currently available to confidently detect and manage this production risk. In this study the complete genome of C. estertheticum DSM 8809 was determined by SMRT® sequencing. The genome consists of a circular chromosome of 4.7 Mbp along with a single plasmid carrying a potential tellurite resistance gene tehB and a Tn3-like resolvase-encoding gene tnpR. The genome sequence was searched for central metabolic pathways that would support its biochemical profile and several enzymes contributing to this phenotype were identified. Several putative antibiotic/biocide/metal resistance-encoding genes and virulence factors were also identified in the genome, a feature that requires further research. The availability of the genome sequence will provide a basic blueprint from which to develop valuable biomarkers that could support and improve the detection and control of this bacterium along the beef production chain

Views of new internal medicine faculty of their preparedness and competence in physician-patient communication

BACKGROUND: We sought to assess self-rated importance of the medical interview to clinical practice and competence in physician-patient communication among new internal medicine faculty at an academic medical center. METHODS: Since 2001, new internal medicine faculty at the Mayo Clinic College of Medicine (Rochester, Minnesota) have completed a survey on physician-patient communication. The survey asks the new faculty to rate their overall competence in medical interviewing, the importance of the medical interview to their practice, their confidence and adequacy of previous training in handling eight frequently encountered challenging communication scenarios, and whether they would benefit from additional communication training. RESULTS: Between 2001 and 2004, 75 general internists and internal medicine subspecialists were appointed to the faculty, and of these, 58 (77%) completed the survey. The faculty rated (on a 10-point scale) the importance of the medical interview higher than their competence in interviewing; this difference was significant (average ± SD, 9.4 ± 1.0 vs 7.7 ± 1.2, P < .001). Similar results were obtained by sex, age, specialty, years since residency or fellowship training, and perceived benefit of training. Experienced faculty rated their competence in medical interviewing and the importance of the medical interview higher than recent graduates (ie, less than one year since training). For each challenging communication scenario, the new faculty rated the adequacy of their previous training in handling the scenario relatively low. A majority (57%) said they would benefit from additional communication training. CONCLUSION: Although new internal medicine faculty rate high the importance of the medical interview, they rate their competence and adequacy of previous training in medical interviewing relatively low, and many indicate that they would benefit from additional communication training. These results should encourage academic medical centers to make curricula in physician-patient communication available to their faculty members because many of them not only care for patients, but also teach clinical skills, including communication skills, to trainees

Cooperative Behavior of Kinetically Constrained Lattice Gas Models of Glassy Dynamics

Kinetically constrained lattice models of glasses introduced by Kob and Andersen (KA) are analyzed. It is proved that only two behaviors are possible on hypercubic lattices: either ergodicity at all densities or trivial non-ergodicity, depending on the constraint parameter and the dimensionality. But in the ergodic cases, the dynamics is shown to be intrinsically cooperative at high densities giving rise to glassy dynamics as observed in simulations. The cooperativity is characterized by two length scales whose behavior controls finite-size effects: these are essential for interpreting simulations. In contrast to hypercubic lattices, on Bethe lattices KA models undergo a dynamical (jamming) phase transition at a critical density: this is characterized by diverging time and length scales and a discontinuous jump in the long-time limit of the density autocorrelation function. By analyzing generalized Bethe lattices (with loops) that interpolate between hypercubic lattices and standard Bethe lattices, the crossover between the dynamical transition that exists on these lattices and its absence in the hypercubic lattice limit is explored. Contact with earlier results are made via analysis of the related Fredrickson-Andersen models, followed by brief discussions of universality, of other approaches to glass transitions, and of some issues relevant for experiments.Comment: 59 page

Quantifying the health impacts of ambient air pollutants: recommendations of a WHO/Europe project.

OBJECTIVE: Quantitative estimates of air pollution health impacts have become an increasingly critical input to policy decisions. The WHO project "Health risks of air pollution in Europe--HRAPIE" was implemented to provide the evidence-based concentration-response functions for quantifying air pollution health impacts to support the 2013 revision of the air quality policy for the European Union (EU). METHODS: A group of experts convened by WHO Regional Office for Europe reviewed the accumulated primary research evidence together with some commissioned reviews and recommended concentration-response functions for air pollutant-health outcome pairs for which there was sufficient evidence for a causal association. RESULTS: The concentration-response functions link several indicators of mortality and morbidity with short- and long-term exposure to particulate matter, ozone and nitrogen dioxide. The project also provides guidance on the use of these functions and associated baseline health information in the cost-benefit analysis. CONCLUSIONS: The project results provide the scientific basis for formulating policy actions to improve air quality and thereby reduce the burden of disease associated with air pollution in Europe

Gene network inference and visualization tools for biologists: application to new human transcriptome datasets.

Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions