470 research outputs found

    Characterization of Pro-Inflammatory Flagellin Proteins Produced by Lactobacillus ruminis and Related Motile Lactobacilli

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    peer-reviewedLactobacillus ruminis is one of at least twelve motile but poorly characterized species found in the genus Lactobacillus. Of these, only L. ruminis has been isolated from mammals, and this species may be considered as an autochthonous member of the gastrointestinal microbiota of humans, pigs and cows. Nine L. ruminis strains were investigated here to elucidate the biochemistry and genetics of Lactobacillus motility. Six strains isolated from humans were non-motile while three bovine isolates were motile. A complete set of flagellum biogenesis genes was annotated in the sequenced genomes of two strains, ATCC25644 (human isolate) and ATCC27782 (bovine isolate), but only the latter strain produced flagella. Comparison of the L. ruminis and L. mali DSM20444T motility loci showed that their genetic content and gene-order were broadly similar, although the L. mali motility locus was interrupted by an 11.8 Kb region encoding rhamnose utilization genes that is absent from the L. ruminis motility locus. Phylogenetic analysis of 39 motile bacteria indicated that Lactobacillus motility genes were most closely related to those of motile carnobacteria and enterococci. Transcriptome analysis revealed that motility genes were transcribed at a significantly higher level in motile L. ruminis ATCC27782 than in non-motile ATCC25644. Flagellin proteins were isolated from L. ruminis ATCC27782 and from three other Lactobacillus species, while recombinant flagellin of aflagellate L. ruminis ATCC25644 was expressed and purified from E. coli. These native and recombinant Lactobacillus flagellins, and also flagellate L. ruminis cells, triggered interleukin-8 production in cultured human intestinal epithelial cells in a manner suppressed by short interfering RNA directed against Toll-Like Receptor 5. This study provides genetic, transcriptomic, phylogenetic and immunological insights into the trait of flagellum-mediated motility in the lactobacilli.This work was supported by a Principal Investigator Award (07/IN.1/B1780) from Science Foundation Ireland to PWOT. BAN was the recipient of an Embark studentship from the Irish Research Council for Science Engineering and Technology. TD and KN were supported by the Alimentary Pharmabiotic Centre, funded by Science Foundation Ireland

    Human-induced biotic invasions and changes in plankton interaction networks

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    Summary: Pervasive and accelerating changes to ecosystems due to human activities remain major sources of uncertainty in predicting the structure and dynamics of ecological communities. Understanding which biotic interactions within natural multitrophic communities are weakened or augmented by invasions of non-native species in the context of other environmental pressures is needed for effective management. We used multivariate autoregressive models with detailed time-series data from largely freshwater and brackish regions of the upper San Francisco Estuary to assess the topology, direction and strength of trophic interactions following major invasions and establishment of non-native zooplankton in the early 1990s. We simultaneously compared the effects of fish and clam predation, environmental temperature and salinity intrusion using time-series data from >60 monitoring locations spanning more than three decades. We found changes in the networks of biotic interactions in both regions after the major zooplankton invasions. Our results imply an increased pressure on native herbivores; intensified negative interactions between herbivores and omnivores; and stronger bottom-up influence of juvenile copepods but weaker influence of phytoplankton as a resource for higher trophic levels following the invasions. We identified salinity intrusion as a primary pressure but showed relatively stronger importance of biotic interactions for understanding the dynamics of entire communities. Synthesis and applications. Our findings highlight the dynamic nature of biotic interactions and provide evidence of how simultaneous invasions of exotic species may alter interaction networks in diverse natural ecosystems over large spatial and temporal scales. Efforts to restore declining fish stocks may be in vain without fully considering the trophic dynamics that limit the flow of energy to target populations. Focusing on multitrophic interactions that may be threatened by invasions rather than a limited focus on responses of individual species or diversity is likely to yield more effective management strategies. © 2014 British Ecological Society

    Drought, disturbance and river resilience in the southern Murray–Darling Basin, Australia

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    Increased frequency, duration and intensity of droughts are predicted for much of the world due to anthropogenic climate change. Understanding resilience to these kinds of disturbance events is becoming ever more critical to inform management and policy decisions. Here, we provide a conceptual framework for ecological resilience by uniting the resistance–resilience framework with adaptation-pathway thinking. Drawing on both published and unpublished data, we explore the effects of a large and intense drought (the Australian ‘Millennium Drought’) on several ecosystem components (floodplain trees, floodplain birds, frogs, aquatic macroinvertebrates and fish) in the southern Murray–Darling Basin, Australia. We describe changes in these communities during and after the Millennium Drought. There is some suggestion that for fish and aquatic invertebrates, traits associated with resistance and resilience may contribute to determining which species decline and which recover and over what time scales. There has been insufficient attention to understanding the mechanisms that underpin resistance and resilience in this context. Better understanding of these mechanisms would enable a more nuanced approach to managing for potential vulnerability to altered disturbance patterns arising from climate change.</p

    Estimating and Modelling Bias of the Hierarchical Partitioning Public-Domain Software: Implications in Environmental Management and Conservation

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    BACKGROUND: Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software "hier.part package" has been developed for running HP in R software. Its authors highlight a "minor rounding error" for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation. METHODOLOGY/PRINCIPAL FINDINGS: Using numerical simulations and two real examples, we assessed the robustness of this HP module in relation to the order the variables have in the analysis. Results indicated a considerable effect of the variable order on the amount of independent variance explained by predictors for models with >9 explanatory variables. For these models the nominal ranking of importance of the predictors changed with variable order, i.e. predictors declared important by its contribution in explaining the response variable frequently changed to be either most or less important with other variable orders. The probability of changing position of a variable was best explained by the difference in independent explanatory power between that variable and the previous one in the nominal ranking of importance. The lesser is this difference, the more likely is the change of position. CONCLUSIONS/SIGNIFICANCE: HP should be applied with caution when more than 9 explanatory variables are used to know ranking of covariate importance. The explained variance is not a useful parameter to use in models with more than 9 independent variables. The inconsistency in the results obtained by HP should be considered in future studies as well as in those already published. Some recommendations to improve the analysis with this HP module are given

    The identification of informative genes from multiple datasets with increasing complexity

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    Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

    Mapping of Data-Sharing Repositories for Paediatric Clinical Research—A Rapid Review

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    The re-use of paediatric individual patient data (IPD) from clinical trials (CTs) is essential to overcome specific ethical, regulatory, methodological, and economic issues that hinder the progress of paediatric research. Sharing data through repositories enables the aggregation and dissemination of clinical information, fosters collaboration between researchers, and promotes transparency. This work aims to identify and describe existing data-sharing repositories (DSRs) developed to store, share and re-use paediatric IPD from CTs. A desk review of platforms providing access to electronic DSRs was conducted. A two-stage process was used to characterize DSRs: a first step of identification, followed by a second step of suitability assessment using a set of eight purpose-built indicators. From an initial set of forty-five publicly available DSRs, twenty-one DSRs were identified as meeting the eligibility criteria. Only two DSRs were found to be totally focused on the paediatric population. Despite an increased awareness of the importance of data-sharing, the results of this study show that paediatrics remains an area in which targeted efforts are still needed. Promoting initiatives to raise awareness of these DSRs and creating ad-hoc measures and common standards for the sharing of paediatric CTs data could help to bridge this gap in paediatric research

    Multi-scale assessment of human-induced changes to Amazonian instream habitats

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    Context Land use change and forest degradation have myriad effects on tropical ecosystems. Yet their consequences for low-order streams remain very poorly understood, including in the world´s largest freshwater basin, the Amazon. Objectives Determine the degree to which physical and chemical characteristics of the instream habitat of low-order Amazonian streams change in response to past local- and catchment-level anthropogenic disturbances. Methods To do so, we collected field instream habitat (i.e., physical habitat and water quality) and landscape data from 99 stream sites in two eastern Brazilian Amazon regions. We used random forest regression trees to assess the relative importance of different predictor variables in determining changes in instream habitat response variables. Results Multiple drivers, operating at multiple spatial scales, were important in determining changes in the physical habitat and water quality of the sites. Although we found few similarities in modelled relationships between the two regions, we observed non-linear responses of specific instream characteristics to landscape change; for example 20 % of catchment deforestation resulted in consistently warmer streams. Conclusions Our results highlight the importance of local riparian and catchment-scale forest cover in shaping instream physical environments, but also underscore the importance of other land use changes and activities, such as road crossings and upstream agriculture intensification. In contrast to the property-scale focus of the Brazilian Forest code, which governs environmental regulations on private land, our results reinforce the importance of catchment-wide management strategies to protect stream ecosystem integrity

    Animal board invited review: advances in proteomics for animal and food sciences

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    Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002 - Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.European Science Foundation (Brussels, Belgium)info:eu-repo/semantics/publishedVersio

    Measurement of the Total Active 8B Solar Neutrino Flux at the Sudbury Neutrino Observatory with Enhanced Neutral Current Sensitivity

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    The Sudbury Neutrino Observatory (SNO) has precisely determined the total active (nu_x) 8B solar neutrino flux without assumptions about the energy dependence of the nu_e survival probability. The measurements were made with dissolved NaCl in the heavy water to enhance the sensitivity and signature for neutral-current interactions. The flux is found to be 5.21 +/- 0.27 (stat) +/- 0.38 (syst) x10^6 cm^{-2}s^{-1}, in agreement with previous measurements and standard solar models. A global analysis of these and other solar and reactor neutrino results yields Delta m^{2} = 7.1^{+1.2}_{-0.6}x10^{-5} ev^2 and theta = 32.5^{+2.4}_{-2.3} degrees. Maximal mixing is rejected at the equivalent of 5.4 standard deviations.Comment: Submitted to Phys. Rev. Let
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