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      Severe infections emerge from commensal bacteria by adaptive evolution

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          Abstract

          Bacteria responsible for the greatest global mortality colonize the human microbiota far more frequently than they cause severe infections. Whether mutation and selection among commensal bacteria are associated with infection is unknown. We investigated de novo mutation in 1163 Staphylococcus aureus genomes from 105 infected patients with nose colonization. We report that 72% of infections emerged from the nose, with infecting and nose-colonizing bacteria showing parallel adaptive differences. We found 2.8-to-3.6-fold adaptive enrichments of protein-altering variants in genes responding to rsp, which regulates surface antigens and toxin production; agr, which regulates quorum-sensing, toxin production and abscess formation; and host-derived antimicrobial peptides. Adaptive mutations in pathogenesis-associated genes were 3.1-fold enriched in infecting but not nose-colonizing bacteria. None of these signatures were observed in healthy carriers nor at the species-level, suggesting infection-associated, short-term, within-host selection pressures. Our results show that signatures of spontaneous adaptive evolution are specifically associated with infection, raising new possibilities for diagnosis and treatment.

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          Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads.

          High-volume sequencing of DNA and RNA is now within reach of any research laboratory and is quickly becoming established as a key research tool. In many workflows, each of the short sequences ("reads") resulting from a sequencing run are first "mapped" (aligned) to a reference sequence to infer the read from which the genomic location derived, a challenging task because of the high data volumes and often large genomes. Existing read mapping software excel in either speed (e.g., BWA, Bowtie, ELAND) or sensitivity (e.g., Novoalign), but not in both. In addition, performance often deteriorates in the presence of sequence variation, particularly so for short insertions and deletions (indels). Here, we present a read mapper, Stampy, which uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation. This results in a higher useable sequence yield and improved accuracy compared to that of existing software.
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            ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

            Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.
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              Cospeciation of gut microbiota with hominids.

              The evolutionary origins of the bacterial lineages that populate the human gut are unknown. Here we show that multiple lineages of the predominant bacterial taxa in the gut arose via cospeciation with humans, chimpanzees, bonobos, and gorillas over the past 15 million years. Analyses of strain-level bacterial diversity within hominid gut microbiomes revealed that clades of Bacteroidaceae and Bifidobacteriaceae have been maintained exclusively within host lineages across hundreds of thousands of host generations. Divergence times of these cospeciating gut bacteria are congruent with those of hominids, indicating that nuclear, mitochondrial, and gut bacterial genomes diversified in concert during hominid evolution. This study identifies human gut bacteria descended from ancient symbionts that speciated simultaneously with humans and the African apes.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                19 December 2017
                2017
                : 6
                : e30637
                Affiliations
                [1 ]deptNuffield Department of Medicine, Experimental Medicine Division University of Oxford OxfordUnited Kingdom
                [2 ]deptMicrobiology and Infectious Diseases Department Oxford University Hospitals NHS Foundation Trust OxfordUnited Kingdom
                [3 ]deptDepartment of Infectious Diseases and Microbiology Royal Sussex County Hospital BrightonUnited Kingdom
                [4 ]deptDepartment of Global Health and Infection Brighton and Sussex Medical School, University of Sussex BrightonUnited Kingdom
                [5 ]NIHR Health Protection Unit in Healthcare Associated Infections and Antimicrobial Resistance at University of Oxford in partnership with Public Health England OxfordUnited Kingdom
                [6 ]deptWellcome Trust Centre for Human Genetics University of Oxford OxfordUnited Kingdom
                [7 ]deptSchool of Cellular and Molecular Medicine University of Bristol BristolUnited Kingdom
                [8 ]deptNational Infection Service Public Health England LondonUnited Kingdom
                [9 ]National Institute for Health Research, Oxford Biomedical Research Centre OxfordUnited Kingdom
                [10 ]deptCentre for Molecular and Cellular Physiology Jenner Institute OxfordUnited Kingdom
                [11 ]deptInstitute for Emerging Infections Oxford Martin School, University of Oxford OxfordUnited Kingdom
                University of St Andrews United Kingdom
                University of St Andrews United Kingdom
                Author information
                https://orcid.org/0000-0001-6071-6770
                https://orcid.org/0000-0002-8154-4039
                https://orcid.org/0000-0002-0940-3311
                Article
                30637
                10.7554/eLife.30637
                5736351
                29256859
                5b62cd84-790c-4db3-9b2c-fe6e4742e821
                © 2017, Young et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 21 July 2017
                : 02 December 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome;
                Award ID: Health Innovation Challenge Fund WT098615/Z/12/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: Oxford NIHR Biomedical Research Centre
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000276, Department of Health;
                Award ID: Health Innovation Challenge Fund HICF-T5-358
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000288, Royal Society;
                Award ID: Sir Henry Dale Fellowship 101237/Z/13/Z
                Award Recipient :
                Funded by: Institut Mérieux;
                Award ID: Mérieux Research Grant
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002141, Public Health England;
                Award ID: HPRU in Healthcare Associated Infections and Antimicrobial Resistance HPRU-2012-10041
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: HPRU in Healthcare Associated Infections and Antimicrobial Resistance HPRU-2012-10041
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome;
                Award ID: Sir Henry Dale Fellowship 101237/Z/13/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome;
                Award ID: Sir Henry Dale Fellowship 102541/Z/13/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000288, Royal Society;
                Award ID: Sir Henry Dale Fellowship 102541/Z/13/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome;
                Award ID: Research Training Fellowship 101611/Z/13/Z
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010269, Wellcome;
                Award ID: Wellcome Trust Centre for Human Genetics core funding 090532/Z/09/Z
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Microbiology and Infectious Disease
                Custom metadata
                Life-threatening S. aureus infections emerge from commensal nose bacteria in association with repeatable adaptive evolution.

                Life sciences
                staphylococcus aureus,within-host evolution,infection,virulence,pathogen genomics,adaptation,human,other

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