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      Composition and diversity of gut microbiota in Pomacea canaliculata in sexes and between developmental stages

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          Abstract

          Background

          The apple snail, Pomacea canaliculata, is one of the world’s 100 worst invasive alien species and vector of some pathogens relevant to human health.

          Methods

          On account of the importance of gut microbiota to the host animals, we compared the communities of the intestinal microbiota from P. canaliculata collected at different developmental stages (juvenile and adult) and different sexes by using high-throughput sequencing.

          Results

          The core bacteria phyla of P. canaliculata gut microbiota included Tenericutes (at an average relative abundance of 45.7 %), Firmicutes (27.85 %), Proteobacteria (11.86 %), Actinobacteria (4.45 %), and Cyanobacteria (3.61 %). The female group possessed the highest richness values, whereas the male group possessed the lowest bacterial richness and diversity compared with the female and juvenile group. Both the developmental stages and sexes had important effects on the composition of the intestinal microbiota of P. canaliculata. By LEfSe analysis, microbes from the phyla Proteobacteria and Actinobacteria were enriched in the female group, phylum Bacteroidetes was enriched in the male group, family Mycoplasmataceae and genus Leuconostoc were enriched in the juvenile group. PICRUSt analysis predicted twenty-four metabolic functions in all samples, including general function prediction, amino acid transport and metabolism, transcription, replication, recombination and repair, carbohydrate transport and metabolism, etc.

          Conclusions

          This study provided a general understanding of the diversity characteristics of intestinal microbial communities of P. canaliculata, and indicated that developmental stage and gender could both influence the intestinal microbes of P. canaliculata. Further study may focus on the interaction between the gut microbiota and their host.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12866-021-02259-2.

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          Most cited references69

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          Metagenomic biomarker discovery and explanation

          This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.
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            Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

            The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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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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                Author and article information

                Contributors
                wgghappy@foxmail.com
                njlihong@outlook.com
                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                1471-2180
                2 July 2021
                2 July 2021
                2021
                : 21
                : 200
                Affiliations
                [1 ]GRID grid.410625.4, ISNI 0000 0001 2293 4910, College of Biology and the Environment, , Nanjing Forestry University, ; 210037 Nanjing, China
                [2 ]GRID grid.260474.3, ISNI 0000 0001 0089 5711, Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, , Nanjing Normal University, ; 210023 Nanjing, China
                [3 ]GRID grid.419073.8, ISNI 0000 0004 0644 5721, Shanghai Academy of Agricultural Sciences, ; 201106 Shanghai, China
                Article
                2259
                10.1186/s12866-021-02259-2
                8252327
                34210255
                5f9e8045-f4a7-4a2d-beb0-578ad88529b5
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 9 October 2020
                : 10 June 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31770402 and 31670422
                Award ID: 31770402 and 31670422
                Funded by: FundRef http://dx.doi.org/10.13039/501100004608, Natural Science Foundation of Jiangsu Province;
                Award ID: BK2017140
                Funded by: 333 high level talents project
                Funded by: Qing Lan Project of Jiangsu province
                Funded by: Shanghai Agricultural Science Committee Youth Talents Development Plan
                Award ID: 2018 (1-32)
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Microbiology & Virology
                pomacea canaliculata,gut microbiota,16s rrna gene,high-throughput sequencing

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