1,364 research outputs found

    Bacterial genospecies that are not ecologically coherent : population genomics of Rhizobium leguminosarum

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    Biological species may remain distinct because of genetic isolation or ecological adaptation, but these two aspects do not always coincide. To establish the nature of the species boundary within a local bacterial population, we characterized a sympatric population of the bacterium Rhizobium leguminosarum by genomic sequencing of 72 isolates. Although all strains have 16S rRNA typical of R. leguminosarum, they fall into five genospecies by the criterion of average nucleotide identity (ANI). Many genes, on plasmids as well as the chromosome, support this division: recombination of core genes has been largely within genospecies. Nevertheless, variation in ecological properties, including symbiotic host range and carbon-source utilization, cuts across these genospecies, so that none of these phenotypes is diagnostic of genospecies. This phenotypic variation is conferred by mobile genes. The genospecies meet the Mayr criteria for biological species in respect of their core genes, but do not correspond to coherent ecological groups, so periodic selection may not be effective in purging variation within them. The population structure is incompatible with traditional 'polyphasic taxonomy' that requires bacterial species to have both phylogenetic coherence and distinctive phenotypes. More generally, genomics has revealed that many bacterial species share adaptive modules by horizontal gene transfer, and we envisage a more consistent taxonomic framework that explicitly recognizes this. Significant phenotypes should be recognized as 'biovars' within species that are defined by core gene phylogeny

    Sequences, sequence clusters and bacterial species

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    Whatever else they should share, strains of bacteria assigned to the same species should have house-keeping genes that are similar in sequence. Single gene sequences (or rRNA gene sequences) have very few informative sites to resolve the strains of closely related species, and relationships among similar species may be confounded by interspecies recombination. A more promising approach (multilocus sequence analysis, MLSA) is to concatenate the sequences of multiple house-keeping loci and to observe the patterns of clustering among large populations of strains of closely related named bacterial species. Recent studies have shown that large populations can be resolved into non-overlapping sequence clusters that agree well with species assigned by the standard microbiological methods. The use of clustering patterns to inform the division of closely related populations into species has many advantages for poorly studied bacteria (or to re-evaluate well-studied species), as it provides a way of recognizing natural discontinuities in the distribution of similar genotypes. Clustering patterns can be used by expert groups as the basis of a pragmatic approach to assigning species, taking into account whatever additional data are available (e.g. similarities in ecology, phenotype and gene content). The development of large MLSA Internet databases provides the ability to assign new strains to previously defined species clusters and an electronic taxonomy. The advantages and problems in using sequence clusters as the basis of species assignments are discussed

    Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

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    Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected

    Pseudoclavibacter-like subcutaneous infection: a case report

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    <p>Abstract</p> <p>Background</p> <p><it>Arthrobacter</it>-like organisms, including <it>Pseudoclavibacter </it>organisms, have rarely been documented as being responsible for infection in humans.</p> <p>Case presentation</p> <p>An 81-year-old French man developed a subcutaneous infection despite antibiotic treatment combining clindamycin and metronidazole for chronic wound infection. A skin biopsy showed numerous polymorphonuclear cells and no bacteria, but a subcutaneous swab yielded numerous polymorphonuclear cells, a few Gram-positive cocci, Gram-negative cocci, and Gram-positive rods. The Gram-positive rod sequence exhibited 99% sequence similarity with uncultured <it>Pseudoclavibacter </it>sp. [GenBank:<ext-link ext-link-id="EF419350" ext-link-type="gen">EF419350</ext-link>] and 99% sequence similarity with uncultured <it>Pseudoclavibacter </it>sp. [GenBank:<ext-link ext-link-id="EF419347" ext-link-type="gen">EF419347</ext-link>]. The genetic data and unique peptide profile of this <it>Pseudoclavibacter</it>-like isolate, determined by matrix-assisted laser desorption ionization-time of flight mass spectrometry, underscored its uniqueness.</p> <p>Conclusions</p> <p><it>Pseudoclavibacter</it>-like organisms are identifiable in cutaneous and subcutaneous infections in humans.</p

    Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

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    Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g. mammals and microbes) using diverse types of data

    A direct comparison of the KB™ Basecaller and phred for identifying the bases from DNA sequencing using chain termination chemistry

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    <p>Abstract</p> <p>Background</p> <p>Relatively recently, the software KB™ Basecaller has replaced <it>phred </it>for identifying the bases from raw sequence data in DNA sequencing employing dideoxy chemistry. We have measured quantitatively the consequences of that change.</p> <p>Results</p> <p>The high quality sequence segment of reads derived from the KB™ Basecaller were, on average, 30-to-50 bases longer than reads derived from <it>phred</it>. However, microbe identification appeared to have been unaffected by the change in software.</p> <p>Conclusions</p> <p>We have demonstrated a modest, but statistically significant, superiority in high quality read length of the KB™ Basecaller compared to <it>phred</it>. We found no statistically significant difference between the numbers of microbial species identified from the sequence data.</p

    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
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