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      Deciphering the unexplored Leptospira diversity from soils uncovers genomic evolution to virulence

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          Abstract

          Despite recent advances in our understanding of the genomics of members of the genus Leptospira, little is known on how virulence has emerged in this heterogeneous bacterial genus as well as on the lifestyle of pathogenic members of the genus Leptospira outside animal hosts. Here, we isolated 12 novel species of the genus Leptospira from tropical soils, significantly increasing the number of known species to 35 and finding evidence of highly unexplored biodiversity in the genus. Extended comparative phylogenomics and pan-genome analyses at the genus level by incorporating 26 novel genomes, revealed that, the traditional leptospiral ‘pathogens’ cluster, as defined by their phylogenetic position, can be split in two groups with distinct virulence potential and accessory gene patterns. These genomic distinctions are strongly linked to the ability to cause or not severe infections in animal models and humans. Our results not only provide new insights into virulence evolution in the members of the genus Leptospira, but also lay the foundations for refining the classification of the pathogenic species.

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          Most cited references30

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          The Pfam protein families database.

          Pfam is a large collection of protein families and domains. Over the past 2 years the number of families in Pfam has doubled and now stands at 6190 (version 10.0). Methodology improvements for searching the Pfam collection locally as well as via the web are described. Other recent innovations include modelling of discontinuous domains allowing Pfam domain definitions to be closer to those found in structure databases. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://Pfam.cgb.ki.se/).
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            eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges

            Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721 801 orthologous groups, encompassing a total of 4 396 591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101 208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450 904 orthologous groups (62.5%).
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              ape 3.0: New tools for distance-based phylogenetics and evolutionary analysis in R.

              Reflecting its continuously increasing versatility and functionality, the popularity of the ape (analysis of phylogenetics and evolution) software package has grown steadily over the years. Among its features, it has a strong distance-based component allowing the user to compute distances from aligned DNA sequences based on most methods from the literature and also build phylogenetic trees from them. However, even data generated with modern genomic approaches can fail to give rise to sufficiently reliable distance estimates. One way to overcome this problem is to exclude such estimates from data analysis giving rise to an incomplete distance data set (as opposed to a complete one). So far their analysis has been out of reach for ape. To remedy this, we have incorporated into ape several methods from the literature for phylogenetic inference from incomplete distance matrices. In addition, we have also extended ape's repertoire for phylogenetic inference from complete distances, added a new object class to efficiently encode sets of splits of taxa, and extended the functionality of some of its existing functions. ape is distributed through the Comprehensive R Archive Network: http://cran.r-project.org/web/packages/ape/index.html Further information may be found at http://ape.mpl.ird.fr/pegas/
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                Author and article information

                Journal
                Microbial Genomics
                Microbiology Society
                2057-5858
                January 01 2018
                January 01 2018
                : 4
                : 1
                Affiliations
                [1 ] 1​Institut Pasteur in New Caledonia, Institut Pasteur International Network, Leptospirosis Research and Expertise Unit, Noumea, New Caledonia
                [2 ] 2​Institut Pasteur Montevideo, Bioinformatics Unit, Uruguay
                [3 ] 3​Institut Pasteur, Unité de Biologie des Spirochètes, 28 rue du docteur Roux, 75724 Paris Cedex 15, France
                Article
                10.1099/mgen.0.000144
                96922782-4288-46b3-b1f6-a7f18b62a1a2
                © 2018
                History

                Social policy & Welfare,Medicine,Biochemistry,Ecology,Environmental studies,Life sciences

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