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      Harnessing diversity and antagonism within the pig skin microbiota to identify novel mediators of colonization resistance to methicillin-resistant Staphylococcus aureus

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          ABSTRACT

          The microbiota mediate multiple aspects of skin barrier function, including colonization resistance to pathogens such as Staphylococcus aureus. The endogenous skin microbiota limits S. aureus colonization via competition and direct inhibition. Novel mechanisms of colonization resistance are promising therapeutic targets for drug-resistant infections, such as those caused by methicillin-resistant S. aureus (MRSA). Here, we developed and characterized a swine model of topical microbiome perturbation and MRSA colonization. As in other model systems, topical antimicrobial treatment had a little discernable effect on community diversity though the overall microbial load was sensitive to multiple types of intervention, including swabbing. In parallel, we established a porcine skin culture collection and screened 7,700 isolates for MRSA inhibition. Using genomic and phenotypic criteria, we curated three isolates to investigate whether prophylactic colonization would inhibit MRSA colonization in vivo. The three-member consortium together, but not individually, provided protection against MRSA colonization, suggesting cooperation and/or synergy among the strains. Inhibitory isolates were represented across all major phyla of the pig skin microbiota and did not have a strong preference for inhibiting closely related species, suggesting that relatedness is not a condition of antagonism. These findings reveal the porcine skin as an underexplored reservoir of skin commensal species with the potential to prevent MRSA colonization and infection.

          IMPORTANCE

          The skin microbiota is protective against pathogens or opportunists such as S. aureus, the most common cause of skin and soft tissue infections. S. aureus can colonize normal skin and nasal passages, and colonization is a risk factor for infection, especially on breach of the skin barrier. Here, we established a pig model to study the competitive mechanisms of the skin microbiota and their role in preventing colonization by MRSA. This drug-resistant strain is also a livestock pathogen, and swine herds can be reservoirs of MRSA carriage. From 7,700 cultured skin isolates, we identified 37 unique species across three phyla that inhibited MRSA. A synthetic community of three inhibitory isolates provided protection together, but not individually, in vivo in a murine model of MRSA colonization. These findings suggest that antagonism is widespread in the pig skin microbiota, and these competitive interactions may be exploited to prevent MRSA colonization.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: VisualizationRole: Writing – review and editingRole: Investigation
                Role: Data curationRole: InvestigationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Formal analysisRole: InvestigationRole: VisualizationRole: Writing – review and editing
                Role: ValidationRole: VisualizationRole: Writing – review and editing
                Role: InvestigationRole: VisualizationRole: Writing – review and editing
                Role: InvestigationRole: ValidationRole: VisualizationRole: Writing – review and editing
                Role: InvestigationRole: VisualizationRole: Writing – review and editing
                Role: InvestigationRole: Writing – review and editing
                Role: InvestigationRole: Writing – review and editing
                Role: Formal analysisRole: Writing – review and editing
                Role: Formal analysisRole: VisualizationRole: Writing – review and editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review and editing
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: Writing – review and editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Editor
                Journal
                mSphere
                mSphere
                mSphere
                mSphere
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5042
                05 July 2023
                Jul-Aug 2023
                05 July 2023
                : 8
                : 4
                : e00177-23
                Affiliations
                [1 ] Department of Dermatology & Microbiology, Perelman School of Medicine, University of Pennsylvania; , Philadelphia, Pennsylvania, USA
                [2 ] Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania; , Philadelphia, Pennsylvania, USA
                University of Wisconsin-Madison; , Madison, Wisconsin, USA
                Author notes
                Address correspondence to Elizabeth A. Grice, egrice@ 123456pennmedicine.upenn.edu

                Monica Wei and Laurice Flowers contributed equally to this article. Order was determined by contributions to manuscript drafting, editing, and revisions.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0003-3939-2200
                Article
                00177-23 msphere.00177-23
                10.1128/msphere.00177-23
                10449522
                37404023
                7ad36f50-8164-470a-a9d6-40c01cc7bee7
                Copyright © 2023 Wei et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 04 April 2023
                : 02 May 2023
                Page count
                supplementary-material: 1, authors: 15, Figures: 6, Tables: 0, Equations: 0, References: 51, Pages: 19, Words: 10309
                Funding
                Funded by: HHS | NIH | National Institute of Nursing Research (NINR);
                Award ID: R01NR015639
                Award Recipient :
                Funded by: Burroughs Wellcome Fund (BWF);
                Award ID: PATH Award
                Award Recipient :
                Funded by: Dermatology Foundation (DF);
                Award ID: Sun Pharma Award
                Award Recipient :
                Funded by: Penn | Perelman School of Medicine, University of Pennsylvania (Penn Med);
                Award ID: Linda Pechenik Montague Award
                Award Recipient :
                Funded by: Penn | Penn Skin Biology and Diseases Resource-based Center, University of Pennsylvania (SBDRC);
                Award ID: P30AR069589
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS);
                Award ID: T32AR007465
                Award Recipient :
                Funded by: HHS | NIH | National Institute of Allergy and Infectious Diseases (NIAID);
                Award ID: 5T32AI141393
                Award Recipient :
                Funded by: Blavatnik Family Foundation (BFF);
                Award Recipient :
                Funded by: Prevent Cancer Foundation (PCF);
                Award Recipient :
                Categories
                Research Article
                ,
                microbial-ecology, Microbial Ecology
                Custom metadata
                July/August 2023

                skin,skin microbiome,microbe–microbe interactions,staphylococcus aureus,porcine skin,colonization resistance,antagonism

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