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Analysis of Genome Content Evolution in PVC Bacterial Super-Phylum: Assessment of Candidate Genes Associated with Cellular Organization and Lifestyle

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      Abstract

      The Planctomycetes, Verrucomicrobia, Chlamydiae (PVC) super-phylum contains bacteria with either complex cellular organization or simple cell structure; it also includes organisms of different lifestyles (pathogens, mutualists, commensal, and free-living). Genome content evolution of this group has not been studied in a systematic fashion, which would reveal genes underlying the emergence of PVC-specific phenotypes. Here, we analyzed the evolutionary dynamics of 26 PVC genomes and several outgroup species. We inferred HGT, duplications, and losses by reconciliation of 27,123 gene trees with the species phylogeny. We showed that genome expansion and contraction have driven evolution within Planctomycetes and Chlamydiae, respectively, and balanced each other in Verrucomicrobia and Lentisphaerae. We also found that for a large number of genes in PVC genomes the most similar sequences are present in Acidobacteria, suggesting past and/or current ecological interaction between organisms from these groups. We also found evidence of shared ancestry between carbohydrate degradation genes in the mucin-degrading human intestinal commensal Akkermansia muciniphila and sequences from Acidobacteria and Bacteroidetes, suggesting that glycoside hydrolases are transferred laterally between gut microbes and that the process of carbohydrate degradation is crucial for microbial survival within the human digestive system. Further, we identified a highly conserved genetic module preferentially present in compartmentalized PVC species and possibly associated with the complex cell plan in these organisms. This conserved machinery is likely to be membrane targeted and involved in electron transport, although its exact function is unknown. These genes represent good candidates for future functional studies.

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      Most cited references 80

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        We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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          A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

          The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page: http://www.lirmm.fr/w3ifa/MAAS/.
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            Author and article information

            Affiliations
            1Department of Molecular Biology, University of Wyoming
            2Department of Botany, University of Wyoming
            3Program in Ecology, University of Wyoming
            Author notes
            *Corresponding author: E-mail: nlward@ 123456uwyo.edu .

            Data deposition: All the sequence data used in this study are available via GenBank.

            Associate editor: Bill Martin

            Journal
            Genome Biol Evol
            Genome Biol Evol
            gbe
            gbe
            Genome Biology and Evolution
            Oxford University Press
            1759-6653
            2012
            4 December 2012
            December 2012
            4 December 2012
            : 4
            : 12
            : 1375-1390
            23221607
            3542564
            10.1093/gbe/evs113
            evs113
            © The Author(s) 2012. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Counts
            Pages: 16
            Categories
            Research Article

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