116 research outputs found

    Metagenomic analysis of the saliva microbiome with merlin

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    In recent years, metagenomics has demonstrated to play an essential role on the study of the microorganisms that live in microbial communities, particularly those who inhabit the human body. Several bioinformatics tools and pipelines have been developed for the analysis of these data, but they usually only address one topic: to identify the taxonomic composition or to address the metabolic functional profile. This work aimed to implement a computational framework able to answer the two questions simultaneously. Merlin, a previously released software aiming at the reconstruction of genome-scale metabolic models for single organisms, was extended to deal with metagenomics data. It has an user-friendly and intuitive interface, being suitable for those with limited bioinformatics skills. The performance of the tool was evaluated with samples from the Human Microbiome Project, particularly from saliva. Overall, the results show the same patterns reported before: while the pathways needed for microbial life remain relatively stable, the community composition varies extensively among individuals

    Social adaptation of the elderly people to the conditions of the stationary social service institution

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    The article discusses the concepts of social adaptation, identifies the psychological characteristics of the elderly, describes the conducted research, its methodology, sampling and analysis of the results obtained on the quality of social adaptation of older people to the conditions of a hospital. The article describes a program that will lead to successful social adaptation of the elderly to the conditions of an inpatient social service institution.В статье рассмотрены понятия социальной адаптации, определены психологические особенности пожилого возраста, описано проведенное исследование, его методика, выборка и анализ полученных результатов о качестве социальной адаптации пожилых людей к условиям стационарного учреждения. В статье описана программа, которая преведет к успешной социальной адаптации пожилых к условиям стационарного учреждения социального обслуживания

    Astrometric Control of the Inertiality of the Hipparcos Catalog

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    Based on the most complete list of the results of an individual comparison of the proper motions for stars of various programs common to the Hipparcos catalog, each of which is an independent realization of the inertial reference frame with regard to stellar proper motions, we redetermined the vector ω\omega of residual rotation of the ICRS system relative to the extragalactic reference frame. The equatorial components of this vector were found to be the following: ωx=+0.04±0.15\omega_x = +0.04\pm 0.15 mas yr1^{-1}, ωy=+0.18±0.12\omega_y = +0.18\pm 0.12 mas yr1^{-1}, and ωz=0.35±0.09\omega_z = -0.35\pm 0.09 mas yr1^{-1}.Comment: 8 pages, 1 figur

    Meningococcus genome informatics platform: a system for analyzing multilocus sequence typing data

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    The Meningococcus Genome Informatics Platform (MGIP) is a suite of computational tools for the analysis of multilocus sequence typing (MLST) data, at http://mgip.biology.gatech.edu. MLST is used to generate allelic profiles to characterize strains of Neisseria meningitidis, a major cause of bacterial meningitis worldwide. Neisseria meningitidis strains are characterized with MLST as specific sequence types (ST) and clonal complexes (CC) based on the DNA sequences at defined loci. These data are vital to molecular epidemiology studies of N. meningitidis, including outbreak investigations and population biology. MGIP analyzes DNA sequence trace files, returns individual allele calls and characterizes the STs and CCs. MGIP represents a substantial advance over existing software in several respects: (i) ease of use—MGIP is user friendly, intuitive and thoroughly documented; (ii) flexibility—because MGIP is a website, it is compatible with any computer with an internet connection, can be used from any geographic location, and there is no installation; (iii) speed—MGIP takes just over one minute to process a set of 96 trace files; and (iv) expandability—MGIP has the potential to expand to more loci than those used in MLST and even to other bacterial species

    Prokaryote genome fluidity is dependent on effective population size

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    Many prokaryote species are known to have fluid genomes, with different strains varying markedly in accessory gene content through the combined action of gene loss, gene gain via lateral transfer, as well as gene duplication. However, the evolutionary forces determining genome fluidity are not yet well understood. We here for the first time systematically analyse the degree to which this distinctive genomic feature differs between bacterial species. We find that genome fluidity is positively correlated with synonymous nucleotide diversity of the core genome, a measure of effective population size Ne. No effects of genome size, phylogeny or homologous recombination rate on genome fluidity were found. Our findings are consistent with a scenario where accessory gene content turnover is for a large part dictated by neutral evolution

    Robust estimation of microbial diversity in theory and in practice

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    Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

    Bacterial microevolution and the Pangenome

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    The comparison of multiple genome sequences sampled from a bacterial population reveals considerable diversity in both the core and the accessory parts of the pangenome. This diversity can be analysed in terms of microevolutionary events that took place since the genomes shared a common ancestor, especially deletion, duplication, and recombination. We review the basic modelling ingredients used implicitly or explicitly when performing such a pangenome analysis. In particular, we describe a basic neutral phylogenetic framework of bacterial pangenome microevolution, which is not incompatible with evaluating the role of natural selection. We survey the different ways in which pangenome data is summarised in order to be included in microevolutionary models, as well as the main methodological approaches that have been proposed to reconstruct pangenome microevolutionary history

    A computational genomics pipeline for prokaryotic sequencing projects

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    Motivation: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data

    Genomic fluidity: an integrative view of gene diversity within microbial populations

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    <p>Abstract</p> <p>Background</p> <p>The dual concepts of pan and core genomes have been widely adopted as means to assess the distribution of gene families within microbial species and genera. The core genome is the set of genes shared by a group of organisms; the pan genome is the set of all genes seen in any of these organisms. A variety of methods have provided drastically different estimates of the sizes of pan and core genomes from sequenced representatives of the same groups of bacteria.</p> <p>Results</p> <p>We use a combination of mathematical, statistical and computational methods to show that current predictions of pan and core genome sizes may have no correspondence to true values. Pan and core genome size estimates are problematic because they depend on the estimation of the occurrence of rare genes and genomes, respectively, which are difficult to estimate precisely because they are rare. Instead, we introduce and evaluate a robust metric - genomic fluidity - to categorize the gene-level similarity among groups of sequenced isolates. Genomic fluidity is a measure of the dissimilarity of genomes evaluated at the gene level.</p> <p>Conclusions</p> <p>The genomic fluidity of a population can be estimated accurately given a small number of sequenced genomes. Further, the genomic fluidity of groups of organisms can be compared robustly despite variation in algorithms used to identify genes and their homologs. As such, we recommend that genomic fluidity be used in place of pan and core genome size estimates when assessing gene diversity within genomes of a species or a group of closely related organisms.</p
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