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      DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure

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          Abstract

          The recent development of methods applying next-generation sequencing to microbial community characterization has led to the proliferation of these studies in a wide variety of sample types. Yet, variation in the physical properties of environmental samples demands that optimal DNA extraction techniques be explored for each new environment. The microbiota associated with many species of insects offer an extraction challenge as they are frequently surrounded by an armored exoskeleton, inhibiting disruption of the tissues within. In this study, we examine the efficacy of several commonly used protocols for extracting bacterial DNA from ants. While bacterial community composition recovered using Illumina 16S rRNA amplicon sequencing was not detectably biased by any method, the quantity of bacterial DNA varied drastically, reducing the number of samples that could be amplified and sequenced. These results indicate that the concentration necessary for dependable sequencing is around 10,000 copies of target DNA per microliter. Exoskeletal pulverization and tissue digestion increased the reliability of extractions, suggesting that these steps should be included in any study of insect-associated microorganisms that relies on obtaining microbial DNA from intact body segments. Although laboratory and analysis techniques should be standardized across diverse sample types as much as possible, minimal modifications such as these will increase the number of environments in which bacterial communities can be successfully studied.

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          Most cited references 53

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          QIIME allows analysis of high-throughput community sequencing data.

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            Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

            mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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              Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.

              A 16S rRNA gene database (http://greengenes.lbl.gov) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria.
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                Author and article information

                Journal
                Microbiologyopen
                Microbiologyopen
                mbo3
                MicrobiologyOpen
                BlackWell Publishing Ltd (Oxford, UK )
                2045-8827
                2045-8827
                December 2014
                26 September 2014
                : 3
                : 6
                : 910-921
                Affiliations
                [1 ]Committee on Evolutionary Biology, University of Chicago Chicago, Illinois
                [2 ]Department of Science and Education, Field Museum of Natural History Chicago, Illinois
                [3 ]Department of Organismic and Evolutionary Biology, Harvard University Cambridge, Massachusetts
                [4 ]Institute of Genomic and Systems Biology, Argonne National Laboratory Lemont, Illinois
                [5 ]Department of Ecology and Evolution, University of Chicago Chicago, Illinois
                [6 ]Computation Institute, University of Chicago Chicago, Illinois
                Author notes
                Correspondence Benjamin E. R. Rubin, Committee on Evolutionary Biology, University of Chicago, Culver Hall 402, 1025 E. 57th Street, Chicago 60637, IL. Tel: (312) 665-7776; Fax: (312) 665-7754; E-mail: brubin@ 123456fieldmuseum.org

                Funding Information This work was supported in part by the U.S. Dept. of Energy under Contract DE-AC02-06CH11357, National Science Foundation DEB Grant no. 1050243 to Corrie S. Moreau, a Grainger Foundation grant to Corrie S. Moreau, and a Negaunee Foundation grant to Corrie S. Moreau. Benjamin E. R. Rubin was supported in part by an NSF Graduate Research Fellowship, the Field Museum Brown Family Graduate Fellowship, and NSF Doctoral Dissertation Improvement Grant no. 1311417.

                Article
                10.1002/mbo3.216
                4263514
                25257543
                © 2014 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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