244 research outputs found

    RCDI/eRCDI: a web-server to estimate codon usage deoptimization

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    <p>Abstract</p> <p>Background</p> <p>The Relative Codon Deoptimization Index (RCDI) was developed by Mueller et al. (2006) as measure of codon deoptimization by comparing how similar is the codon usage of a gene and the codon usage of a reference genome.</p> <p>Findings</p> <p>RCDI/eRCDI is a web application server that calculates the Relative Codon Deoptimization Index and a new expected value for the RCDI (eRCDI). The RCDI is used to estimate the similarity of the codon frequencies of a specific gene in comparison to a given reference genome. The eRCDI is determined by generating random sequences with similar G+C and amino acid composition to the input sequences and may be used as an indicator of the significance of the RCDI values. RCDI/eRCDI is freely available at <url>http://genomes.urv.cat/CAIcal/RCDI</url>.</p> <p>Conclusions</p> <p>This web server will be a useful tool for genome analysis, to understand host-virus phylogenetic relationships or to infer the potential host range of a virus and its replication strategy, as well as in experimental virology to ease the step of gene design for heterologous protein expression.</p

    Seeing the Tree of Life behind the phylogenetic forest

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    Genomes in turmoil: quantification of genome dynamics in prokaryote supergenomes

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    Background: Genomes of bacteria and archaea (collectively, prokaryotes) appear to exist in incessant flux, expanding via horizontal gene transfer and gene duplication, and contracting via gene loss. However, the actual rates of genome dynamics and relative contributions of different types of event across the diversity of prokaryotes are largely unknown, as are the sizes of microbial supergenomes, i.e. pools of genes that are accessible to the given microbial species.Results: We performed a comprehensive analysis of the genome dynamics in 35 groups (34 bacterial and one archaeal) of closely related microbial genomes using a phylogenetic birth-and-death maximum likelihood model to quantify the rates of gene family gain and loss, as well as expansion and reduction. The results show that loss of gene families dominates the evolution of prokaryotes, occurring at approximately three times the rate of gain. The rates of gene family expansion and reduction are typically seven and twenty times less than the gain and loss rates, respectively. Thus, the prevailing mode of evolution in bacteria and archaea is genome contraction, which is partially compensated by the gain of new gene families via horizontal gene transfer. However, the rates of gene family gain, loss, expansion and reduction vary within wide ranges, with the most stable genomes showing rates about 25 times lower than the most dynamic genomes. For many groups, the supergenome estimated from the fraction of repetitive gene family gains includes about tenfold more gene families than the typical genome in the group although some groups appear to have vast, 'open' supergenomes.Conclusions: Reconstruction of evolution for groups of closely related bacteria and archaea reveals an extremely rapid and highly variable flux of genes in evolving microbial genomes, demonstrates that extensive gene loss and horizontal gene transfer leading to innovation are the two dominant evolutionary processes, and yields robust estimates of the supergenome size

    HEG-DB: a database of predicted highly expressed genes in prokaryotic complete genomes under translational selection

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    The highly expressed genes database (HEG-DB) is a genomic database that includes the prediction of which genes are highly expressed in prokaryotic complete genomes under strong translational selection. The current version of the database contains general features for almost 200 genomes under translational selection, including the correspondence analysis of the relative synonymous codon usage for all genes, and the analysis of their highly expressed genes. For each genome, the database contains functional and positional information about the predicted group of highly expressed genes. This information can also be accessed using a search engine. Among other statistical parameters, the database also provides the Codon Adaptation Index (CAI) for all of the genes using the codon usage of the highly expressed genes as a reference set. The ‘Pathway Tools Omics Viewer’ from the BioCyc database enables the metabolic capabilities of each genome to be explored, particularly those related to the group of highly expressed genes. The HEG-DB is freely available at http://genomes.urv.cat/HEG-DB

    DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self

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    This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users

    The compositional and evolutionary logic of metabolism

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    Metabolism displays striking and robust regularities in the forms of modularity and hierarchy, whose composition may be compactly described. This renders metabolic architecture comprehensible as a system, and suggests the order in which layers of that system emerged. Metabolism also serves as the foundation in other hierarchies, at least up to cellular integration including bioenergetics and molecular replication, and trophic ecology. The recapitulation of patterns first seen in metabolism, in these higher levels, suggests metabolism as a source of causation or constraint on many forms of organization in the biosphere. We identify as modules widely reused subsets of chemicals, reactions, or functions, each with a conserved internal structure. At the small molecule substrate level, module boundaries are generally associated with the most complex reaction mechanisms and the most conserved enzymes. Cofactors form a structurally and functionally distinctive control layer over the small-molecule substrate. Complex cofactors are often used at module boundaries of the substrate level, while simpler ones participate in widely used reactions. Cofactor functions thus act as "keys" that incorporate classes of organic reactions within biochemistry. The same modules that organize the compositional diversity of metabolism are argued to have governed long-term evolution. Early evolution of core metabolism, especially carbon-fixation, appears to have required few innovations among a small number of conserved modules, to produce adaptations to simple biogeochemical changes of environment. We demonstrate these features of metabolism at several levels of hierarchy, beginning with the small-molecule substrate and network architecture, continuing with cofactors and key conserved reactions, and culminating in the aggregation of multiple diverse physical and biochemical processes in cells.Comment: 56 pages, 28 figure

    TreeKO: a duplication-aware algorithm for the comparison of phylogenetic trees

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    Comparisons of tree topologies provide relevant information in evolutionary studies. Most existing methods share the drawback of requiring a complete and exact mapping of terminal nodes between the compared trees. This severely limits the scope of genome-wide analyses, since trees containing duplications are pruned arbitrarily or discarded. To overcome this, we have developed treeKO, an algorithm that enables the comparison of tree topologies, even in the presence of duplication and loss events. To do so treeKO recursively splits gene trees into pruned trees containing only orthologs to subsequently compute a distance based on the combined analyses of all pruned tree comparisons. In addition treeKO, implements the possibility of computing phylome support values, and reconciliation-based measures such as the number of inferred duplication and loss events

    A Pilot Study for Metabolic Profiling of Obesity-Associated Microbial Gut Dysbiosis in Male Wistar Rats

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    Obesity is one of the most incident and concerning disease worldwide. Definite strategies to prevent obesity and related complications remain elusive. Among the risk factors of the onset of obesity, gut microbiota might play an important role in the pathogenesis of the disease, and it has received extensive attention because it affects the host metabolism. In this study, we aimed to define a metabolic profile of the segregated obesity-associated gut dysbiosis risk factor. The study of the metabolome, in an obesity-associated gut dysbiosis model, provides a relevant way for the discrimination on the different biomarkers in the obesity onset. Thus, we developed a model of this obesity risk factors through the transference of gut microbiota from obese to non-obese male Wistar rats and performed a subsequent metabolic analysis in the receptor rats. Our results showed alterations in the lipid metabolism in plasma and in the phenylalanine metabolism in urine. In consequence, we have identified metabolic changes characterized by: (1) an increase in DG:34:2 in plasma, a decrease in hippurate, (2) an increase in 3-HPPA, and (3) an increase in o-coumaric acid. Hereby, we propose these metabolites as a metabolic profile associated to a segregated dysbiosis state related to obesity disease

    Integration of an [FeFe]-hydrogenase into the anaerobic metabolism of <i>Escherichia coli</i>

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    AbstractBiohydrogen is a potentially useful product of microbial energy metabolism. One approach to engineering biohydrogen production in bacteria is the production of non-native hydrogenase activity in a host cell, for example Escherichia coli. In some microbes, hydrogenase enzymes are linked directly to central metabolism via diaphorase enzymes that utilise NAD+/NADH cofactors. In this work, it was hypothesised that heterologous production of an NAD+/NADH-linked hydrogenase could connect hydrogen production in an E. coli host directly to its central metabolism. To test this, a synthetic operon was designed and characterised encoding an apparently NADH-dependent, hydrogen-evolving [FeFe]-hydrogenase from Caldanaerobacter subterranus. The synthetic operon was stably integrated into the E. coli chromosome and shown to produce an active hydrogenase, however no H2 production was observed. Subsequently, it was found that heterologous co-production of a pyruvate::ferredoxin oxidoreductase and ferredoxin from Thermotoga maritima was found to be essential to drive H2 production by this system. This work provides genetic evidence that the Ca.subterranus [FeFe]-hydrogenase could be operating in vivo as an electron-confurcating enzyme

    Accurate Detection of Recombinant Breakpoints in Whole-Genome Alignments

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    We propose a novel method for detecting sites of molecular recombination in multiple alignments. Our approach is a compromise between previous extremes of computationally prohibitive but mathematically rigorous methods and imprecise heuristic methods. Using a combined algorithm for estimating tree structure and hidden Markov model parameters, our program detects changes in phylogenetic tree topology over a multiple sequence alignment. We evaluate our method on benchmark datasets from previous studies on two recombinant pathogens, Neisseria and HIV-1, as well as simulated data. We show that we are not only able to detect recombinant regions of vastly different sizes but also the location of breakpoints with great accuracy. We show that our method does well inferring recombination breakpoints while at the same time maintaining practicality for larger datasets. In all cases, we confirm the breakpoint predictions of previous studies, and in many cases we offer novel predictions
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