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      A Cross-Taxon Analysis of Insect-Associated Bacterial Diversity

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          Abstract

          Although it is well known that plants and animals harbor microbial symbionts that can influence host traits, the factors regulating the structure of these microbial communities often remain largely undetermined. This is particularly true for insect-associated microbial communities, as few cross-taxon comparisons have been conducted to date. To address this knowledge gap and determine how host phylogeny and ecology affect insect-associated microbial communities, we collected 137 insect specimens representing 39 species, 28 families, and 8 orders, and characterized the bacterial communities associated with each specimen via 16S rRNA gene sequencing. Bacterial taxa within the phylum Proteobacteria were dominant in nearly all insects sampled. On average, the insect-associated bacterial communities were not very diverse, with individuals typically harboring fewer than 8 bacterial phylotypes. Bacterial communities also tended to be dominated by a single phylotype; on average, the most abundant phylotype represented 54.7% of community membership. Bacterial communities were significantly more similar among closely related insects than among less-related insects, a pattern driven by within-species community similarity but detected at every level of insect taxonomy tested. Diet was a poor predictor of bacterial community composition. Individual insect species harbored remarkably unique communities: the distribution of 69.0% of bacterial phylotypes was limited to unique insect species, whereas only 5.7% of phylotypes were detected in more than five insect species. Together these results suggest that host characteristics strongly regulate the colonization and assembly of bacterial communities across insect lineages, patterns that are driven either by co-evolution between insects and their symbionts or by closely related insects sharing conserved traits that directly select for similar bacterial communities.

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          QIIME allows analysis of high-throughput community sequencing data.

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            UniFrac: a new phylogenetic method for comparing microbial communities.

            We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.
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              Bacterial community variation in human body habitats across space and time.

              Elucidating the biogeography of bacterial communities on the human body is critical for establishing healthy baselines from which to detect differences associated with diseases. To obtain an integrated view of the spatial and temporal distribution of the human microbiota, we surveyed bacteria from up to 27 sites in seven to nine healthy adults on four occasions. We found that community composition was determined primarily by body habitat. Within habitats, interpersonal variability was high, whereas individuals exhibited minimal temporal variability. Several skin locations harbored more diverse communities than the gut and mouth, and skin locations differed in their community assembly patterns. These results indicate that our microbiota, although personalized, varies systematically across body habitats and time; such trends may ultimately reveal how microbiome changes cause or prevent disease.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                16 April 2013
                : 8
                : 4
                Affiliations
                [1 ]Cooperative Institute for Research in Environmental Sciences, University of Colorado – Boulder, Boulder, Colorado, United States of America
                [2 ]Miramontes Arts and Sciences Program, University of Colorado – Boulder, Boulder, Colorado, United States of America
                [3 ]Department of Ecology and Evolutionary Biology, University of Colorado – Boulder, Boulder, Colorado, United States of America
                Argonne National Laboratory, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: RTJ NF. Performed the experiments: RTJ LGS. Analyzed the data: RTJ. Wrote the paper: RTJ LGS NF. Identified insects: LGS.

                [¤]

                Current address: Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana, United States of America

                Article
                PONE-D-12-39595
                10.1371/journal.pone.0061218
                3628706
                23613815

                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.

                Page count
                Pages: 10
                Funding
                RTJ’s salary was provided through an American Society for Microbiology Postdoctoral Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Ecology
                Community Ecology
                Community Assembly
                Species Interactions
                Ecological Environments
                Terrestrial Environments
                Biodiversity
                Biogeography
                Microbial Ecology
                Population Ecology
                Terrestrial Ecology
                Microbiology
                Microbial Ecology
                Population Biology
                Population Ecology
                Zoology
                Entomology

                Uncategorized

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