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      The composition and abundance of bacterial communities residing in the gut of Glossina palpalis palpalis captured in two sites of southern Cameroon

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          Abstract

          Background

          A number of reports have demonstrated the role of insect bacterial flora on their host’s physiology and metabolism. The tsetse host and vector of trypanosomes responsible for human sleeping sickness (human African trypanosomiasis, HAT) and nagana in animals (African animal trypanosomiasis, AAT) carry bacteria that influence its diet and immune processes. However, the mechanisms involved in these processes remain poorly documented. This underscores the need for increased research into the bacterial flora composition and structure of tsetse flies. The aim of this study was to identify the diversity and relative abundance of bacterial genera in Glossina palpalis palpalis flies collected in two trypanosomiasis foci in Cameroon.

          Methods

          Samples of G. p. palpalis which were either negative or naturally trypanosome-positive were collected in two foci located in southern Cameroon (Campo and Bipindi). Using the V3V4 and V4 variable regions of the small subunit of the 16S ribosomal RNA gene, we analyzed the respective bacteriome of the flies’ midguts.

          Results

          We identified ten bacterial genera. In addition, we observed that the relative abundance of the obligate endosymbiont Wigglesworthia was highly prominent (around 99%), regardless of the analyzed region. The remaining genera represented approximately 1% of the bacterial flora, and were composed of Salmonella, Spiroplasma, Sphingomonas, Methylobacterium, Acidibacter, Tsukamurella, Serratia, Kluyvera and an unidentified bacterium. The genus Sodalis was present but with a very low abundance. Globally, no statistically significant difference was found between the bacterial compositions of flies from the two foci, and between positive and trypanosome-negative flies. However, Salmonella and Serratia were only described in trypanosome-negative flies, suggesting a potential role for these two bacteria in fly refractoriness to trypanosome infection. In addition, our study showed the V4 region of the small subunit of the 16S ribosomal RNA gene was more efficient than the V3V4 region at describing the totality of the bacterial diversity.

          Conclusions

          A very large diversity of bacteria was identified with the discovering of species reported to secrete anti-parasitic compounds or to modulate vector competence in other insects. For future studies, the analyses should be enlarged with larger sampling including foci from several countries.

          Electronic supplementary material

          The online version of this article (10.1186/s13071-019-3402-2) contains supplementary material, which is available to authorized users.

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          Most cited references60

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          Swarm: robust and fast clustering method for amplicon-based studies

          Popular de novo amplicon clustering methods suffer from two fundamental flaws: arbitrary global clustering thresholds, and input-order dependency induced by centroid selection. Swarm was developed to address these issues by first clustering nearly identical amplicons iteratively using a local threshold, and then by using clusters’ internal structure and amplicon abundances to refine its results. This fast, scalable, and input-order independent approach reduces the influence of clustering parameters and produces robust operational taxonomic units.
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            Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform

            With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina's MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%.
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              Calypso: a user-friendly web-server for mining and visualizing microbiome–environment interactions

              Abstract Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web-interface is accessible via http://cgenome.net/calypso/. The software is programmed in Java, PERL and R and the source code is available from Zenodo (https://zenodo.org/record/50931). The software is freely available for non-commercial users. Contact: l.krause@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                tsagmoj@yahoo.fr
                julie.reveillaud@cirad.fr
                guilhem.sempere@cirad.fr
                njiokouf@yahoo.com
                metatitre@yahoo.fr
                luc.abate@ird.fr
                Majoline.TCHIOFFOTSAPI@pasteur.fr
                anne.geiger@libertysurf.fr
                Journal
                Parasit Vectors
                Parasit Vectors
                Parasites & Vectors
                BioMed Central (London )
                1756-3305
                2 April 2019
                2 April 2019
                2019
                : 12
                : 151
                Affiliations
                [1 ]ISNI 0000 0001 2097 0141, GRID grid.121334.6, INTERTRYP, Institut de Recherche pour le Développement, , University of Montpellier, ; Montpellier, France
                [2 ]ISNI 0000 0001 2173 8504, GRID grid.412661.6, Faculty of Science, , University of Yaoundé I, ; P.O. Box 812, Yaoundé, Cameroon
                [3 ]ISNI 0000 0001 2097 0141, GRID grid.121334.6, ASTRE, INRA, CIRAD, University of Montpellier, ; Montpellier, France
                [4 ]GRID grid.433120.7, UMR Maladies Infectieuses Et Vecteurs Écologie, Génétique, Évolution Et Contrôle, IRD 224-Centre National de la Recherche Scientifique, ; 5290-UM1-UM2, Montpellier, France
                [5 ]Center for Research on Filariasis and other Tropical Diseases (CRFilMT), P.O. Box 5797, Yaoundé, Cameroon
                [6 ]ISNI 0000 0001 2173 8504, GRID grid.412661.6, Faculty of Science, , University of Yaoundé I, ; P.O. Box 812, Yaoundé, Cameroon
                Article
                3402
                10.1186/s13071-019-3402-2
                6444424
                30940213
                a9bb9c41-d769-48d1-898f-4bd19adae7d6
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 27 September 2018
                : 20 March 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002887, Conseil Régional Languedoc-Roussillon;
                Award ID: Chercheur d’Avenir 2011
                Award Recipient :
                Funded by: Institut de Recherche pour le Développement
                Funded by: FundRef http://dx.doi.org/10.13039/501100004493, International Atomic Energy Agency;
                Funded by: Aix-Marseille Université (FR)
                Award ID: ANR-10-INBS-0009-10
                Funded by: CIRAD
                Award ID: AGAP HPC Data Center of the South Green Bioinformatics platform
                Funded by: Institut de Recherche pour le Développement
                Award ID: Bourse ARTS
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                Parasitology
                glossina,bacterial flora,sleeping sickness,nagana,trypanosome,metabarcoding
                Parasitology
                glossina, bacterial flora, sleeping sickness, nagana, trypanosome, metabarcoding

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