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      Production of germ-free mosquitoes via transient colonisation allows stage-specific investigation of host–microbiota interactions

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          Abstract

          The mosquito microbiota impacts the physiology of its host and is essential for normal larval development, thereby influencing transmission of vector-borne pathogens. Germ-free mosquitoes generated with current methods show larval stunting and developmental deficits. Therefore, functional studies of the mosquito microbiota have so far mostly been limited to antibiotic treatments of emerging adults. In this study, we introduce a method to produce germ-free Aedes aegypti mosquitoes. It is based on reversible colonisation with bacteria genetically modified to allow complete decolonisation at any developmental stage. We show that, unlike germ-free mosquitoes previously produced using sterile diets, reversibly colonised mosquitoes show no developmental retardation and reach the same size as control adults. This allows us to uncouple the study of the microbiota in larvae and adults. In adults, we detect no impact of bacterial colonisation on mosquito fecundity or longevity. In larvae, data from our transcriptome analysis and diet supplementation experiments following decolonisation suggest that bacteria support larval development by contributing to folate biosynthesis and by enhancing energy storage. Our study establishes a tool to study the microbiota in insects and deepens our knowledge on the metabolic contribution of bacteria to mosquito development.

          Abstract

          Germ-free mosquitoes generated with current methods exhibit developmental deficits. Here, the authors use genetically modified bacteria to allow complete decolonisation at any developmental stage of Aedes aegypti mosquitoes and show that bacteria support larval development by contributing to folate biosynthesis and enhancing energy storage.

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          Most cited references49

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              Fiji: an open-source platform for biological-image analysis.

              Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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                Author and article information

                Contributors
                oromoli@pasteur-cayenne.fr
                mathilde.gendrin@pasteur.fr
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 February 2021
                11 February 2021
                2021
                : 12
                : 942
                Affiliations
                [1 ]GRID grid.418525.f, ISNI 0000 0001 2206 8813, Microbiota of Insect Vectors Group, Institut Pasteur de la Guyane, ; Cayenne, French Guiana France
                [2 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Institute for Infectious Diseases, , University of Bern, ; Bern, Switzerland
                [3 ]GRID grid.428999.7, ISNI 0000 0001 2353 6535, Parasites and Insect Vectors Department, , Institut Pasteur, ; Paris, France
                Author information
                http://orcid.org/0000-0002-7608-2650
                http://orcid.org/0000-0002-6913-7932
                http://orcid.org/0000-0001-6405-6458
                Article
                21195
                10.1038/s41467-021-21195-3
                7878806
                33574256
                9bae22da-ba11-4c58-84d6-69e585fc8418
                © The Author(s) 2021

                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
                : 5 March 2020
                : 15 January 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001665, Agence Nationale de la Recherche (French National Research Agency);
                Award ID: ANR-10-LABX-62-IBEID
                Award ID: ANR-18-CE15-0007
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                developmental biology,gene regulation,microbiome,entomology
                Uncategorized
                developmental biology, gene regulation, microbiome, entomology

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