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      Biotic Interactions Shape the Ecological Distributions of Staphylococcus Species

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          ABSTRACT

          Many metagenomic sequencing studies have observed the presence of closely related bacterial species or genotypes in the same microbiome. Previous attempts to explain these patterns of microdiversity have focused on the abiotic environment, but few have considered how biotic interactions could drive patterns of microbiome diversity. We dissected the patterns, processes, and mechanisms shaping the ecological distributions of three closely related Staphylococcus species in cheese rind biofilms. Paradoxically, the most abundant species ( S. equorum) is the slowest colonizer and weakest competitor based on growth and competition assays in the laboratory. Through in vitro community reconstructions, we determined that biotic interactions with neighboring fungi help resolve this paradox. Species-specific stimulation of the poor competitor by fungi of the genus Scopulariopsis allows S. equorum to dominate communities in vitro as it does in situ. Results of comparative genomic and transcriptomic experiments indicate that iron utilization pathways, including a homolog of the S. aureus staphyloferrin B siderophore operon pathway, are potential molecular mechanisms underlying Staphylococcus- Scopulariopsis interactions. Our integrated approach demonstrates that fungi can structure the ecological distributions of closely related bacterial species, and the data highlight the importance of bacterium-fungus interactions in attempts to design and manipulate microbiomes.

          IMPORTANCE

          Decades of culture-based studies and more recent metagenomic studies have demonstrated that bacterial species in agriculture, medicine, industry, and nature are unevenly distributed across time and space. The ecological processes and molecular mechanisms that shape these distributions are not well understood because it is challenging to connect in situ patterns of diversity with mechanistic in vitro studies in the laboratory. Using tractable cheese rind biofilms and a focus on coagulase-negative Staphylococcus (CNS) species, we demonstrate that fungi can mediate the ecological distributions of closely related bacterial species. One of the Staphylococcus species studied, S. saprophyticus, is a common cause of urinary tract infections. By identifying processes that control the abundance of undesirable CNS species, cheese producers will have more precise control on the safety and quality of their products. More generally, Staphylococcus species frequently co-occur with fungi in mammalian microbiomes, and similar bacterium-fungus interactions may structure bacterial diversity in these systems.

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          Competition and Biodiversity in Spatially Structured Habitats

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            Patterns and processes of microbial community assembly.

            Recent research has expanded our understanding of microbial community assembly. However, the field of community ecology is inaccessible to many microbial ecologists because of inconsistent and often confusing terminology as well as unnecessarily polarizing debates. Thus, we review recent literature on microbial community assembly, using the framework of Vellend (Q. Rev. Biol. 85:183-206, 2010) in an effort to synthesize and unify these contributions. We begin by discussing patterns in microbial biogeography and then describe four basic processes (diversification, dispersal, selection, and drift) that contribute to community assembly. We also discuss different combinations of these processes and where and when they may be most important for shaping microbial communities. The spatial and temporal scales of microbial community assembly are also discussed in relation to assembly processes. Throughout this review paper, we highlight differences between microbes and macroorganisms and generate hypotheses describing how these differences may be important for community assembly. We end by discussing the implications of microbial assembly processes for ecosystem function and biodiversity.
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              InParanoid 7: new algorithms and tools for eukaryotic orthology analysis

              The InParanoid project gathers proteomes of completely sequenced eukaryotic species plus Escherichia coli and calculates pairwise ortholog relationships among them. The new release 7.0 of the database has grown by an order of magnitude over the previous version and now includes 100 species and their collective 1.3 million proteins organized into 42.7 million pairwise ortholog groups. The InParanoid algorithm itself has been revised and is now both more specific and sensitive. Based on results from our recent benchmarking of low-complexity filters in homology assignment, a two-pass BLAST approach was developed that makes use of high-precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows. We have also updated the InParanoid web site (http://InParanoid.sbc.su.se). Several features have been added, the response times have been improved and the site now sports a new, clearer look. As the number of ortholog databases has grown, it has become difficult to compare among these resources due to a lack of standardized source data and incompatible representations of ortholog relationships. To facilitate data exchange and comparisons among ortholog databases, we have developed and are making available two XML schemas: SeqXML for the input sequences and OrthoXML for the output ortholog clusters.
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                Author and article information

                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                18 October 2016
                Sep-Oct 2016
                : 7
                : 5
                : e01157-16
                Affiliations
                [a ]Department of Biology, Tufts University, Medford, Massachusetts, USA
                [b ]Division of Biological Sciences, University of California, San Diego, La Jolla, California, USA
                Author notes
                Address correspondence to Benjamin E. Wolfe, benjamin.wolfe@ 123456tufts.edu .

                Editor John W. Taylor, University of California

                Article
                mBio01157-16
                10.1128/mBio.01157-16
                5082897
                27795388
                16f31805-a111-4916-81a4-766f97a7ee04
                Copyright © 2016 Kastman et al.

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

                History
                : 24 June 2016
                : 16 September 2016
                Page count
                supplementary-material: 0, Figures: 4, Tables: 0, Equations: 0, References: 87, Pages: 13, Words: 11586
                Funding
                Funded by: HHS | National Institutes of Health (NIH) http://dx.doi.org/10.13039/100000002
                Award ID: P50 GM068763
                Award Recipient : Rachel J. Dutton Award Recipient : Benjamin E. Wolfe
                Funded by: Tufts University http://dx.doi.org/10.13039/100008090
                Award Recipient : Erik K. Kastman Award Recipient : Noelani Kamelamela Award Recipient : Josh Norville Award Recipient : Benjamin E. Wolfe
                Funded by: UC | University of California, San Diego (UCSD) http://dx.doi.org/10.13039/100007911
                Award Recipient : Rachel J. Dutton
                Categories
                Research Article
                Custom metadata
                September/October 2016

                Life sciences
                Life sciences

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