High-Resolution Functional Mapping of the Venezuelan Equine Encephalitis Virus Genome by Insertional Mutagenesis and Massively Parallel Sequencing

We have developed a high-resolution genomic mapping technique that combines transposon-mediated insertional mutagenesis with either capillary electrophoresis or massively parallel sequencing to identify functionally important regions of the Venezuelan equine encephalitis virus (VEEV) genome. We initially used a capillary electrophoresis method to gain insight into the role of the VEEV nonstructural protein 3 (nsP3) in viral replication. We identified several regions in nsP3 that are intolerant to small (15 bp) insertions, and thus are presumably functionally important. We also identified nine separate regions in nsP3 that will tolerate small insertions at low temperatures (30°C), but not at higher temperatures (37°C, and 40°C). Because we found this method to be extremely effective at identifying temperature sensitive (ts) mutations, but limited by capillary electrophoresis capacity, we replaced the capillary electrophoresis with massively parallel sequencing and used the improved method to generate a functional map of the entire VEEV genome. We identified several hundred potential ts mutations throughout the genome and we validated several of the mutations in nsP2, nsP3, E3, E2, E1 and capsid using single-cycle growth curve experiments with virus generated through reverse genetics. We further demonstrated that two of the nsP3 ts mutants were attenuated for virulence in mice but could elicit protective immunity against challenge with wild-type VEEV. The recombinant ts mutants will be valuable tools for further studies of VEEV replication and virulence. Moreover, the method that we developed is applicable for generating such tools for any virus with a robust reverse genetics system

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Biochemical and Structural Insights into the Mechanisms of SARS Coronavirus RNA Ribose 2′-O-Methylation by nsp16/nsp10 Protein Complex

The 5′-cap structure is a distinct feature of eukaryotic mRNAs, and eukaryotic viruses generally modify the 5′-end of viral RNAs to mimic cellular mRNA structure, which is important for RNA stability, protein translation and viral immune escape. SARS coronavirus (SARS-CoV) encodes two S-adenosyl-L-methionine (SAM)-dependent methyltransferases (MTase) which sequentially methylate the RNA cap at guanosine-N7 and ribose 2′-O positions, catalyzed by nsp14 N7-MTase and nsp16 2′-O-MTase, respectively. A unique feature for SARS-CoV is that nsp16 requires non-structural protein nsp10 as a stimulatory factor to execute its MTase activity. Here we report the biochemical characterization of SARS-CoV 2′-O-MTase and the crystal structure of nsp16/nsp10 complex bound with methyl donor SAM. We found that SARS-CoV nsp16 MTase methylated m7GpppA-RNA but not m7GpppG-RNA, which is in contrast with nsp14 MTase that functions in a sequence-independent manner. We demonstrated that nsp10 is required for nsp16 to bind both m7GpppA-RNA substrate and SAM cofactor. Structural analysis revealed that nsp16 possesses the canonical scaffold of MTase and associates with nsp10 at 1∶1 ratio. The structure of the nsp16/nsp10 interaction interface shows that nsp10 may stabilize the SAM-binding pocket and extend the substrate RNA-binding groove of nsp16, consistent with the findings in biochemical assays. These results suggest that nsp16/nsp10 interface may represent a better drug target than the viral MTase active site for developing highly specific anti-coronavirus drugs

Genetic susceptibility to burnout in a Swedish twin cohort

Most previous studies of burnout have focused on work environmental stressors, while familial factors so far mainly have been overlooked. The aim of the study was to estimate the relative importance of genetic influences on burnout (measured with Pines Burnout Measure) in a sample of monozygotic (MZ) and dizygotic (DZ) Swedish twins. The study sample consisted of 20,286 individuals, born 1959–1986 from the Swedish twin registry who participated in the cross-sectional study of twin adults: genes and environment. Probandwise concordance rates (the risk for one twin to be affected given that his/her twin partner is affected by burnout) and within pair correlations were calculated for MZ and DZ same—and opposite sexed twin pairs. Heritability coefficients i.e. the proportion of the total variance attributable to genetic factors were calculated using standard biometrical model fitting procedures. The results showed that genetic factors explained 33% of the individual differences in burnout symptoms in women and men. Environmental factors explained a substantial part of the variation as well and are thus important to address in rehabilitation and prevention efforts to combat burnout

Burnout among chiropractic practitioners: real or imagined an exploratory study protocol

Burnout is a psychological syndrome of emotional exhaustion, depersonalization and reduced personal accomplishment that has been found to exist in a significant number of healthcare and helping professionals. It imposes a significant societal burden by shortened practitioner lifespan, decreased efficiency, negative health outcomes and poorer levels of patient care. Theoretical models suggest that it appears to be the result of a complex interaction between job resources and job demands. It may be reasonable to conclude that Chiropractic professionals experience similar vocational demands and thus experience significant levels of occupational stress and subsequent burnout. However the data on burnout within the chiropractic profession is limited. It is possible that this results in significant negative outcomes on chiropractors and their patients. Therefore, the objective of this paper is to demonstrate the need to explore burnout in chiropractic practice and offer a research protocol for a potential study

Crystal Structure and Functional Analysis of the SARS-Coronavirus RNA Cap 2′-O-Methyltransferase nsp10/nsp16 Complex

Cellular and viral S-adenosylmethionine-dependent methyltransferases are involved in many regulated processes such as metabolism, detoxification, signal transduction, chromatin remodeling, nucleic acid processing, and mRNA capping. The Severe Acute Respiratory Syndrome coronavirus nsp16 protein is a S-adenosylmethionine-dependent (nucleoside-2′-O)-methyltransferase only active in the presence of its activating partner nsp10. We report the nsp10/nsp16 complex structure at 2.0 Å resolution, which shows nsp10 bound to nsp16 through a ∼930 Å2 surface area in nsp10. Functional assays identify key residues involved in nsp10/nsp16 association, and in RNA binding or catalysis, the latter likely through a SN2-like mechanism. We present two other crystal structures, the inhibitor Sinefungin bound in the S-adenosylmethionine binding pocket and the tighter complex nsp10(Y96F)/nsp16, providing the first structural insight into the regulation of RNA capping enzymes in (+)RNA viruses

Climate change, phenological shifts, eco-evolutionary responses and population viability: toward a unifying predictive approach

The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere–ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change

Systematic Identification of Novel, Essential Host Genes Affecting Bromovirus RNA Replication

Positive-strand RNA virus replication involves viral proteins and cellular proteins at nearly every replication step. Brome mosaic virus (BMV) is a well-established model for dissecting virus-host interactions and is one of very few viruses whose RNA replication, gene expression and encapsidation have been reproduced in the yeast Saccharomyces cerevisiae. Previously, our laboratory identified ∼100 non-essential host genes whose loss inhibited or enhanced BMV replication at least 3-fold. However, our isolation of additional BMV-modulating host genes by classical genetics and other results underscore that genes essential for cell growth also contribute to BMV RNA replication at a frequency that may be greater than that of non-essential genes. To systematically identify novel, essential host genes affecting BMV RNA replication, we tested a collection of ∼900 yeast strains, each with a single essential gene promoter replaced by a doxycycline-repressible promoter, allowing repression of gene expression by adding doxycycline to the growth medium. Using this strain array of ∼81% of essential yeast genes, we identified 24 essential host genes whose depleted expression reproducibly inhibited or enhanced BMV RNA replication. Relevant host genes are involved in ribosome biosynthesis, cell cycle regulation and protein homeostasis, among other cellular processes. BMV 2aPol levels were significantly increased in strains depleted for a heat shock protein (HSF1) or proteasome components (PRE1 and RPT6), suggesting these genes may affect BMV RNA replication by directly or indirectly modulating 2aPol localization, post-translational modification or interacting partners. Investigating the diverse functions of these newly identified essential host genes should advance our understanding of BMV-host interactions and normal cellular pathways, and suggest new modes of virus control

Digit ratios have poor indicator value in a wild bird population

Early androgen exposure is known to have long-lasting effects on phenotype, behaviour and even fitness, but difficulties in measuring the exposure hinders the study of its importance in evolutionary context. Digit ratios have been highlighted as a potential easy-to-measure indicator of early steroid exposure, as they have been suggested to reflect steroid, mainly testosterone levels during prenatal development. However, evidence for digit ratios reflecting early steroid levels is weak, as experimental studies, especially in wild populations, are scarce. We studied the association between maternally derived yolk androgens and digit ratios (2D:4D, 2D:3D and 3D:4D) using both correlative data and a rather high level of experimental elevation of yolk androgens in a passerine bird, the pied flycatcher (Ficedula hypoleuca). We also examined whether digit ratios have indicator value in an evolutionary context by studying correlations between digit ratios and reproductive traits, secondary sexual traits and exploratory behaviour. We did not find any association between digit ratios and yolk androgen level either in correlative or experimental data. Digit ratios were neither related to any of the reproductive and secondary sexual traits or exploratory behaviour measured. There was, however, a sex difference in 2D:3D and 3D:4D of adult birds (due to second and fourth digits being shorter in females), which was not apparent in fledglings or captivity-raised juveniles. This suggests that either the sex difference may develop as late as during the sexual maturation for breeding. These results indicate that, in this species, digit ratios are not reliable markers of maternally derived yolk androgen exposure and that they bear little relevance as correlates of the adaptive traits we measured

Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs

Background A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference. In recent years, a number of approaches have been developed for probabilistic sampling of alignments, rather than simply generating a single optimum. However, this type of probabilistic information is currently not widely used in the context of downstream inference, since most existing algorithms are set up to make use of a single alignment. Results In this work we present a framework for representing a set of sampled alignments as a directed acyclic graph (DAG) whose nodes are alignment columns; each path through this DAG then represents a valid alignment. Since the probabilities of individual columns can be estimated from empirical frequencies, this approach enables sample-based estimation of posterior alignment probabilities. Moreover, due to conditional independencies between columns, the graph structure encodes a much larger set of alignments than the original set of sampled MSAs, such that the effective sample size is greatly increased. Conclusions The alignment DAG provides a natural way to represent a distribution in the space of MSAs, and allows for existing algorithms to be efficiently scaled up to operate on large sets of alignments. As an example, we show how this can be used to compute marginal probabilities for tree topologies, averaging over a very large number of MSAs. This framework can also be used to generate a statistically meaningful summary alignment; example applications show that this summary alignment is consistently more accurate than the majority of the alignment samples, leading to improvements in downstream tree inference. Implementations of the methods described in this article are available at http://statalign.github.io/WeaveAlign webcite