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      Parallel Evolution of Streptococcus pneumoniae and Streptococcus mitis to Pathogenic and Mutualistic Lifestyles

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          ABSTRACT

          The bacterium Streptococcus pneumoniae is one of the leading causes of fatal infections affecting humans. Intriguingly, phylogenetic analysis shows that the species constitutes one evolutionary lineage in a cluster of the otherwise commensal Streptococcus mitis strains, with which humans live in harmony. In a comparative analysis of 35 genomes, including phylogenetic analyses of all predicted genes, we have shown that the pathogenic pneumococcus has evolved into a master of genomic flexibility while lineages that evolved into the nonpathogenic S. mitis secured harmonious coexistence with their host by stabilizing an approximately 15%-reduced genome devoid of many virulence genes. Our data further provide evidence that interspecies gene transfer between S. pneumoniae and S. mitis occurs in a unidirectional manner, i.e., from S. mitis to S. pneumoniae. Import of genes from S. mitis and other mitis, anginosus, and salivarius group streptococci ensured allelic replacements and antigenic diversification and has been driving the evolution of the remarkable structural diversity of capsular polysaccharides of S. pneumoniae. Our study explains how the unique structural diversity of the pneumococcal capsule emerged and conceivably will continue to increase and reveals a striking example of the fragile border between the commensal and pathogenic lifestyles. While genomic plasticity enabling quick adaptation to environmental stress is a necessity for the pathogenic streptococci, the commensal lifestyle benefits from stability.

          IMPORTANCE

          One of the leading causes of fatal infections affecting humans, Streptococcus pneumoniae, and the commensal Streptococcus mitis are closely related obligate symbionts associated with hominids. Faced with a shortage of accessible hosts, the two opposing lifestyles evolved in parallel. We have shown that the nonpathogenic S. mitis secured harmonious coexistence with its host by stabilizing a reduced genome devoid of many virulence genes. Meanwhile, the pathogenic pneumococcus evolved into a master of genomic flexibility and imports genes from S. mitis and other related streptococci. This process ensured antigenic diversification and has been driving the evolution of the remarkable structural diversity of capsular polysaccharides of S. pneumoniae, which conceivably will continue to increase and present a challenge to disease prevention.

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          Most cited references 58

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

           S Altschul (1997)
          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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            MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.

            Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
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              Application of phylogenetic networks in evolutionary studies.

              The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.
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                Author and article information

                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society of Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                22 July 2014
                Jul-Aug 2014
                : 5
                : 4
                Affiliations
                [ a ]Department of Biomedicine, Faculty of Health, Aarhus University, Aarhus, Denmark
                [ b ]Department of Microbiology and Immunology, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
                Author notes
                Address correspondence to Mogens Kilian, kilian@ 123456biomed.au.dk .

                Editor Michael Russell, University at Buffalo

                This article is a direct contribution from a Fellow of the American Academy of Microbiology.

                Article
                mBio01490-14
                10.1128/mBio.01490-14
                4120201
                25053789
                Copyright © 2014 Kilian et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Counts
                Pages: 9
                Categories
                Research Article
                Custom metadata
                July/August 2014

                Life sciences

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