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      Phylosymbiosis: Relationships and Functional Effects of Microbial Communities across Host Evolutionary History

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          Abstract

          Phylosymbiosis was recently proposed to describe the eco-evolutionary pattern, whereby the ecological relatedness of host-associated microbial communities parallels the phylogeny of related host species. Here, we test the prevalence of phylosymbiosis and its functional significance under highly controlled conditions by characterizing the microbiota of 24 animal species from four different groups ( Peromyscus deer mice, Drosophila flies, mosquitoes, and Nasonia wasps), and we reevaluate the phylosymbiotic relationships of seven species of wild hominids. We demonstrate three key findings. First, intraspecific microbiota variation is consistently less than interspecific microbiota variation, and microbiota-based models predict host species origin with high accuracy across the dataset. Interestingly, the age of host clade divergence positively associates with the degree of microbial community distinguishability between species within the host clades, spanning recent host speciation events (~1 million y ago) to more distantly related host genera (~108 million y ago). Second, topological congruence analyses of each group's complete phylogeny and microbiota dendrogram reveal significant degrees of phylosymbiosis, irrespective of host clade age or taxonomy. Third, consistent with selection on host–microbiota interactions driving phylosymbiosis, there are survival and performance reductions when interspecific microbiota transplants are conducted between closely related and divergent host species pairs. Overall, these findings indicate that the composition and functional effects of an animal's microbial community can be closely allied with host evolution, even across wide-ranging timescales and diverse animal systems reared under controlled conditions.

          Author Summary

          Studies on the assembly and function of host-microbiota symbioses are inherently complicated by the diverse effects of diet, age, sex, host genetics, and endosymbionts. Central to unraveling one effect from the other is an experimental framework that reduces confounders. Using common rearing conditions across four animal groups (deer mice, flies, mosquitoes, and wasps) that span recent host speciation events to more distantly related host genera, this study tests whether microbial community assembly is generally random with respect to host relatedness or "phylosymbiotic," in which the phylogeny of the host group is congruent with ecological relationships of their microbial communities. Across all four animal groups and one external dataset of great apes, we apply several statistics for analyzing congruencies and demonstrate phylosymbiosis to varying degrees in each group. Moreover, consistent with selection on host–microbiota interactions driving phylosymbiosis, transplanting interspecific microbial communities in mice significantly decreased their ability to digest food. Similarly, wasps that received transplants of microbial communities from different wasp species had lower survival than those given their own microbiota. Overall, this experimental and statistical framework shows how microbial community assembly and functionality across related species can be linked to animal evolution, health, and survival.

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          Most cited references37

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          Integration of biological networks and gene expression data using Cytoscape.

          Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
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            Evolution of genes and genomes on the Drosophila phylogeny.

            Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
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              Drosophila microbiome modulates host developmental and metabolic homeostasis via insulin signaling.

              The symbiotic microbiota profoundly affect many aspects of host physiology; however, the molecular mechanisms underlying host-microbe cross-talk are largely unknown. Here, we show that the pyrroloquinoline quinone-dependent alcohol dehydrogenase (PQQ-ADH) activity of a commensal bacterium, Acetobacter pomorum, modulates insulin/insulin-like growth factor signaling (IIS) in Drosophila to regulate host homeostatic programs controlling developmental rate, body size, energy metabolism, and intestinal stem cell activity. Germ-free animals monoassociated with PQQ-ADH mutant bacteria displayed severe deregulation of developmental and metabolic homeostasis. Importantly, these defects were reversed by enhancing host IIS or by supplementing the diet with acetic acid, the metabolic product of PQQ-ADH.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                18 November 2016
                November 2016
                18 November 2016
                : 14
                : 11
                : e2000225
                Affiliations
                [1 ]Department of Biological Sciences, Vanderbilt University, Nashville, Tennessee, United States of America
                [2 ]Vanderbilt Genetics Institute, Vanderbilt University, Nashville, Tennessee, United States of America
                [3 ]The Rowland Institute at Harvard, Harvard University, Cambridge, Massachusetts, United States of America
                [4 ]Department of Pathology, Microbiology, and Immunology, Vanderbilt University, Nashville, Tennessee, United States of America
                Stanford University School of Medicine, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                ‡ These authors share first authorship on this work.

                Article
                pbio.2000225
                10.1371/journal.pbio.2000225
                5115861
                27861590
                b703e832-0a57-4f80-83d7-48ee95d4d439
                © 2016 Brooks et al

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

                History
                : 7 June 2016
                : 20 October 2016
                Page count
                Figures: 6, Tables: 0, Pages: 29
                Funding
                Rowland Institute at Harvard University Junior Fellowship to RMB. National Science Foundation—Division of Integrative Organismal Systems https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503623 (grant number 1456778). Received by SRB. National Science Foundation—Division of Biological Infrastructure http://www.nsf.gov/div/index.jsp?div=DBI (grant number 1400456). Received by KDK. National Institute of Health—Predoctoral Training Grant https://researchtraining.nih.gov (grant number 5T32GM080178). Received by AWB. National Science Foundation—Division of Environmental Biology http://www.nsf.gov/div/index.jsp?div=DEB (grant number 1046149). Received by SRB. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Rodents
                Peromyscus
                Biology and Life Sciences
                Microbiology
                Microbial Evolution
                Biology and Life Sciences
                Evolutionary Biology
                Organismal Evolution
                Microbial Evolution
                Research and Analysis Methods
                Model Organisms
                Animal Models
                Drosophila Melanogaster
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Insects
                Drosophila
                Drosophila Melanogaster
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
                Biology and Life Sciences
                Zoology
                Animal Phylogenetics
                Medicine and Health Sciences
                Epidemiology
                Disease Vectors
                Insect Vectors
                Mosquitoes
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                Organisms
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                Arthropoda
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                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Phylogenetic Analysis
                Research and Analysis Methods
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Phylogenetic Analysis
                Biology and Life Sciences
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                Invertebrates
                Arthropoda
                Insects
                Custom metadata
                All sequencing and mapping files are available from the Dryad database repository: doi: 10.5061/dryad.n3v49. A GitHub repository contains custom analysis scripts and all of the necessary data for figure reconstruction (including BIOM Tables and Mapping files) for each clade are also publicly available: https://github.com/awbrooks19/phylosymbiosis.

                Life sciences
                Life sciences

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