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      Exploring Changes in the Microbiota of Aedes albopictus: Comparison Among Breeding Site Water, Larvae, and Adults

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          Abstract

          The mosquito body hosts highly diverse microbes, which influence different physiological traits of both larvae and adults. The composition of adult mosquito microbiota is tightly linked to that of larvae, which are aquatic and feed on organic detritus, algae and prokaryotic microorganisms present in their breeding sites. Unraveling the ecological features of larval habitats that shape the structure of bacterial communities and their interactions with the mosquito host is still a poorly investigated topic in the Asian tiger mosquito Aedes albopictus, a highly invasive species that is vector of numerous arboviruses, including Dengue, Chikungunya, and Zika viruses. In this study, we investigated the composition of the bacterial community present in the water from a natural larval breeding site in which we separately reared wild-collected larvae and hatched eggs of the Foshan reference laboratory strain. Using sequence analysis of bacterial 16S rRNA gene amplicons, we comparatively analyzed the microbiota of the larvae and that of adult mosquitoes, deriving information about the relative impact of the breeding site water on shaping mosquito microbiota. We observed a higher bacterial diversity in breeding site water than in larvae or adults, irrespective of the origin of the sample. Moreover, larvae displayed a significantly different and most diversified microbial community than newly emerged adults, which appeared to be dominated by Proteobacteria. The microbiota of breeding site water significantly increased its diversity over time, suggesting the presence of a dynamic interaction among bacterial communities, breeding sites and mosquito hosts. The analysis of Wolbachia prevalence in adults from Foshan and five additional strains with different geographic origins confirmed the described pattern of dual wAlbA and wAlbB strain infection. However, differences in Wolbachia prevalence were detected, with one strain from La Reunion Island showing up to 18% uninfected individuals. These findings contribute in further understanding the dynamic interactions between the ecology of larval habitats and the structure of host microbiota, as well as providing additional information relative to the patterns of Wolbachia infection.

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            QIIME allows analysis of high-throughput community sequencing data.

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              phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

              Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                28 January 2021
                2021
                : 12
                : 624170
                Affiliations
                [1] 1Department of Biology and Biotechnology, University of Pavia , Pavia, Italy
                [2] 2Department of Biotechnology and Biosciences, University of Milano–Bicocca , Milan, Italy
                Author notes

                Edited by: Mathilde Gendrin, Institut Pasteur de la Guyane, French Guiana

                Reviewed by: Kerri Coon, University of Wisconsin–Madison, United States; Eric Caragata, University of Florida, United States; Anubis Vega Rua, Institut Pasteur de la Guadeloupe, Guadeloupe

                *Correspondence: Mariangela Bonizzoni, m.bonizzoni@ 123456unipv.it

                Present address: Francesca Scolari, Institute of Molecular Genetics IGM-CNR “Luigi Luca Cavalli-Sforza”, Pavia, Italy; Anna Sandionigi, Quantia Consulting srl., Milan, Italy

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.624170
                7876458
                33584626
                40545a39-eaf2-40e9-a175-bdde0c1fad81
                Copyright © 2021 Scolari, Sandionigi, Carlassara, Bruno, Casiraghi and Bonizzoni.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 October 2020
                : 04 January 2021
                Page count
                Figures: 7, Tables: 3, Equations: 0, References: 121, Pages: 18, Words: 0
                Funding
                Funded by: Horizon 2020 10.13039/501100007601
                Award ID: 682394
                Funded by: Ministero dell’Istruzione, dell’Università e della Ricerca 10.13039/501100003407
                Award ID: R1623HZAH5
                Funded by: Human Frontier Science Program 10.13039/501100000854
                Award ID: RGP0007/2017
                Funded by: Ministero dell’Istruzione, dell’Università e della Ricerca 10.13039/501100003407
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                breeding site,water,larvae,16s rrna gene,wolbachia
                Microbiology & Virology
                breeding site, water, larvae, 16s rrna gene, wolbachia

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