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      The microbiomes of blowflies and houseflies as bacterial transmission reservoirs

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          Abstract

          Blowflies and houseflies are mechanical vectors inhabiting synanthropic environments around the world. They feed and breed in fecal and decaying organic matter, but the microbiome they harbour and transport is largely uncharacterized. We sampled 116 individual houseflies and blowflies from varying habitats on three continents and subjected them to high-coverage, whole-genome shotgun sequencing. This allowed for genomic and metagenomic analyses of the host-associated microbiome at the species level. Both fly host species segregate based on principal coordinate analysis of their microbial communities, but they also show an overlapping core microbiome. Legs and wings displayed the largest microbial diversity and were shown to be an important route for microbial dispersion. The environmental sequencing approach presented here detected a stochastic distribution of human pathogens, such as Helicobacter pylori, thereby demonstrating the potential of flies as proxies for environmental and public health surveillance.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

                Contributors
                anacmj@gmail.com
                scschuster@ntu.edu.sg
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                24 November 2017
                24 November 2017
                2017
                : 7
                : 16324
                Affiliations
                [1 ]ISNI 0000 0001 2224 0361, GRID grid.59025.3b, Present Address: Singapore Centre for Environmental Life Sciences Engineering, Nanyang Technological University, ; Singapore, 637551 Singapore
                [2 ]ISNI 0000 0000 9136 933X, GRID grid.27755.32, Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia, ; Charlottesville, VA 22908 USA
                [3 ]ISNI 0000 0004 0495 846X, GRID grid.4709.a, European Molecular Biology Laboratory, Structural and Computational Biology Unit, ; Heidelberg, 69117 Germany
                [4 ]ISNI 0000 0004 1936 738X, GRID grid.213876.9, Center for Vaccines and Immunology, College of Veterinary Medicine, University of Georgia, ; Athens, 30602 GA USA
                [5 ]ISNI 0000 0001 0723 2494, GRID grid.411087.b, Centro de Biologia Molecular e Engenharia Genética, Departamento de Genética, Evolução e Bioagentes, Instituto de Biologia, Universidade Estadual de Campinas, ; Campinas, SP 13083-875 Brazil
                [6 ]CosmosID Inc, Rockville, MD 20850 USA
                [7 ]ISNI 0000 0001 0941 7177, GRID grid.164295.d, Center for Bioinformatics and Computational Biology, University of Maryland. Institute for Computational Biology, University of Maryland College Park, ; College Park, MD 20742 USA
                [8 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Johns Hopkins Bloomberg School of Public Health, ; Baltimore, MD 21205 USA
                [9 ]ISNI 0000 0001 2097 4281, GRID grid.29857.31, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, ; University Park, PA 16802 USA
                [10 ]ISNI 0000 0001 2294 473X, GRID grid.8536.8, Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, ; Rio de Janeiro, RJ 21941-902 Brazil
                Author information
                http://orcid.org/0000-0003-2382-9842
                http://orcid.org/0000-0003-1645-3947
                Article
                16353
                10.1038/s41598-017-16353-x
                5701178
                29176730
                27fe33df-65a2-495b-9dd3-81d123a2ca21
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 June 2017
                : 10 November 2017
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