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      Pyrosequencing reveals a shift in symbiotic bacteria populations across life stages of Bactrocera dorsalis

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          Abstract

          Bactrocera dorsalis is one of the most economically important fruit flies around the world. In this study, 454 pyrosequencing was used to identify the bacteria associated with different developmental stages of B. dorsalis. At ≥ 97% nucleotide similarity, total reads could be assigned to 172 Operational Taxonomic Units belonging to six phyla. Proteobacteria dominated in immature stages while Firmicutes dominated in adult stages. The most abundant families were Enterococcaceae and Comamondaceae. The genus Comamonas was most abundant in pupae whereas completely absent in adults. Some identified species had low sequence similarity to reported species indicating the possibility of novel taxa. However, a majority sequence reads were similar to sequences previously identified to be associated with Bactrocera correcta, suggesting a characteristic microbial fauna for this insect genus. The type and abundance of different bacterial groups varied across the life stages of B. dorsalis. Selection pressure exerted by the host insect as a result of its habitat and diet choices could be the reason for the observed shift in the bacteria groups. These findings increase our understanding of the intricate symbiotic relationships between bacteria and B. dorsalis and provide clues to develop potential biocontrol techniques against this fruit fly.

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          Most cited references 43

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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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            Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies

            The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×106 reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.
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              The gut bacteria of insects: nonpathogenic interactions.

              The diversity of the Insecta is reflected in the large and varied microbial communities inhabiting the gut. Studies, particularly with termites and cockroaches, have focused on the nutritional contributions of gut bacteria in insects living on suboptimal diets. The indigenous gut bacteria, however, also play a role in withstanding the colonization of the gut by non-indigenous species including pathogens. Gut bacterial consortia adapt by the transfer of plasmids and transconjugation between bacterial strains, and some insect species provide ideal conditions for bacterial conjugation, which suggests that the gut is a "hot spot" for gene transfer. Genomic analysis provides new avenues for the study of the gut microbial community and will reveal the molecular foundations of the relationships between the insect and its microbiome. In this review the intestinal bacteria is discussed in the context of developing our understanding of symbiotic relationships, of multitrophic interactions between insects and plant or animal host, and in developing new strategies for controlling insect pests.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                30 March 2015
                2015
                : 5
                Affiliations
                [1 ]College of Plant Science & Technology, Huazhong Agricultural University , Wuhan 430070, China
                [2 ]Pest Control Division, National Agricultural Technology Extension and Service Center, Ministry of Agriculture , Beijing 100125, China
                [3 ]French National Institute for Agricultural Research (INRA) , UMR1355-ISA, 06903 Sophia-Antipolis, France
                [4 ]Department of Entomology, University of Kentucky , Lexington, KY 40546-0091, USA
                Author notes
                Article
                srep09470
                10.1038/srep09470
                5380164
                25822599
                Copyright © 2015, Macmillan Publishers Limited. All rights reserved

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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