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Phylogenomics and Comparative Genomic Studies Robustly Support Division of the Genus Mycobacterium into an Emended Genus Mycobacterium and Four Novel Genera

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      Abstract

      The genus Mycobacterium contains 188 species including several major human pathogens as well as numerous other environmental species. We report here comprehensive phylogenomics and comparative genomic analyses on 150 genomes of Mycobacterium species to understand their interrelationships. Phylogenetic trees were constructed for the 150 species based on 1941 core proteins for the genus Mycobacterium, 136 core proteins for the phylum Actinobacteria and 8 other conserved proteins. Additionally, the overall genome similarity amongst the Mycobacterium species was determined based on average amino acid identity of the conserved protein families. The results from these analyses consistently support the existence of five distinct monophyletic groups within the genus Mycobacterium at the highest level, which are designated as the “ Tuberculosis-Simiae,” “ Terrae,”Triviale,” “ Fortuitum-Vaccae,” and “ Abscessus-Chelonae” clades. Some of these clades have also been observed in earlier phylogenetic studies. Of these clades, the “ Abscessus-Chelonae” clade forms the deepest branching lineage and does not form a monophyletic grouping with the “ Fortuitum-Vaccae” clade of fast-growing species. In parallel, our comparative analyses of proteins from mycobacterial genomes have identified 172 molecular signatures in the form of conserved signature indels and conserved signature proteins, which are uniquely shared by either all Mycobacterium species or by members of the five identified clades. The identified molecular signatures (or synapomorphies) provide strong independent evidence for the monophyly of the genus Mycobacterium and the five described clades and they provide reliable means for the demarcation of these clades and for their diagnostics. Based on the results of our comprehensive phylogenomic analyses and numerous identified molecular signatures, which consistently and strongly support the division of known mycobacterial species into the five described clades, we propose here division of the genus Mycobacterium into an emended genus Mycobacterium encompassing the “ Tuberculosis-Simiae” clade, which includes all of the major human pathogens, and four novel genera viz. Mycolicibacterium gen. nov., Mycolicibacter gen. nov., Mycolicibacillus gen. nov. and Mycobacteroides gen. nov. corresponding to the “ Fortuitum-Vaccae,”Terrae,”Triviale,” and “ Abscessus-Chelonae” clades, respectively. With the division of mycobacterial species into these five distinct groups, attention can now be focused on unique genetic and molecular characteristics that differentiate members of these groups.

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      Most cited references 202

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      Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

      The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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        RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

        Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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          New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

          PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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            Author and article information

            Affiliations
            Department of Biochemistry and Biomedical Sciences, McMaster University , Hamilton, CA, Canada
            Author notes

            Edited by: Antonio Ventosa, Universidad de Sevilla, Spain

            Reviewed by: Stephanus Nicolaas Venter, University of Pretoria, South Africa; Alice Rebecca Wattam, Virginia Tech, United States

            *Correspondence: Radhey S. Gupta gupta@ 123456mcmaster.ca

            This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

            Contributors
            Journal
            Front Microbiol
            Front Microbiol
            Front. Microbiol.
            Frontiers in Microbiology
            Frontiers Media S.A.
            1664-302X
            13 February 2018
            2018
            : 9
            5819568 10.3389/fmicb.2018.00067
            Copyright © 2018 Gupta, Lo and Son.

            This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

            Counts
            Figures: 10, Tables: 11, Equations: 0, References: 202, Pages: 41, Words: 28584
            Funding
            Funded by: Natural Sciences and Engineering Research Council of Canada 10.13039/501100000038
            Award ID: 249924
            Categories
            Microbiology
            Original Research

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