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      Gut microbial community in proboscis monkeys ( Nasalis larvatus): implications for effects of geographical and social factors

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          Abstract

          Recent technological advances have enabled comprehensive analyses of the previously uncharacterized microbial community in the gastrointestinal tracts of numerous animal species; however, the gut microbiota of several species, such as the endangered proboscis monkey ( Nasalis larvatus) examined in this study, remains poorly understood. Our study sought to establish the first comprehensive data on the gut microbiota of free-ranging foregut-fermenting proboscis monkeys and to determine how their microbiota are affected locally by environmental factors, i.e. geographical distance, and social factors, i.e. the number of adult females within harem groups and the number of adults and subadults within non-harem groups, in a riverine forest in Sabah, Malaysian Borneo. Using 16S rRNA gene sequencing of 264 faecal samples collected from free-ranging proboscis monkeys, we demonstrated the trend that their microbial community composition is not particularly distinctive compared with other foregut- and hindgut-fermenting primates. The microbial alpha diversity was higher in larger groups and individuals inhabiting diverse vegetation (i.e. presumed to have a diverse diet). For microbial beta diversity, some measures were significant, showing higher values with larger geographical distances between samples. These results suggest that social factors such as increased inter-individual interactions, which can occur with larger groups, as well as physical distances between individuals or differences in dietary patterns, may affect the gut microbial communities.

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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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              Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies

              16S ribosomal RNA gene (rDNA) amplicon analysis remains the standard approach for the cultivation-independent investigation of microbial diversity. The accuracy of these analyses depends strongly on the choice of primers. The overall coverage and phylum spectrum of 175 primers and 512 primer pairs were evaluated in silico with respect to the SILVA 16S/18S rDNA non-redundant reference dataset (SSURef 108 NR). Based on this evaluation a selection of ‘best available’ primer pairs for Bacteria and Archaea for three amplicon size classes (100–400, 400–1000, ≥1000 bp) is provided. The most promising bacterial primer pair (S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21), with an amplicon size of 464 bp, was experimentally evaluated by comparing the taxonomic distribution of the 16S rDNA amplicons with 16S rDNA fragments from directly sequenced metagenomes. The results of this study may be used as a guideline for selecting primer pairs with the best overall coverage and phylum spectrum for specific applications, therefore reducing the bias in PCR-based microbial diversity studies.

                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: MethodologyRole: Writing – review and editing
                Role: MethodologyRole: ResourcesRole: Writing – review and editing
                Role: ResourcesRole: Writing – review and editing
                Role: MethodologyRole: ResourcesRole: Writing – review and editing
                Role: ResourcesRole: Writing – review and editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draft
                Journal
                R Soc Open Sci
                R Soc Open Sci
                RSOS
                royopensci
                Royal Society Open Science
                The Royal Society
                2054-5703
                July 2024
                July 24, 2024
                July 24, 2024
                : 11
                : 7
                : 231756
                Affiliations
                [ 1 ]Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS; , Kota Kinabalu, Sabah 88400, Malaysia
                [ 2 ]National Taiwan University; , Taipei 10617, Taiwan
                [ 3 ]Center for Ecological Research, Kyoto University; , Inuyama 484-8506, Japan
                [ 4 ]Sabah Wildlife Department, Wisma Muis; , Kota Kinabalu, Sabah 88100, Malaysia
                [ 5 ]Danau Girang Field Centre, Sabah Wildlife Department, Wisma Muis; , Kota Kinabalu, Sabah 88100, Malaysia
                [ 6 ]Organisms and Environment Division, Cardiff School of Biosciences, Cardiff University; , Cardiff CF10 3AX, UK
                [ 7 ]Sabah Forestry Department, Forest Research Centre; , Sandakan, Sabah, Malaysia
                [ 8 ]Wildlife Research Center of Kyoto University, 2-24 Tanaka-Sekiden-cho, Sakyo; , Kyoto 606-8203, Japan
                [ 9 ]Chubu Institute for Advanced Studies, Chubu University, 1200, Matsumoto-cho; , Kasugai-shi, Aichi 487-8501, Japan
                [ 10 ]Chubu University Academy of Emerging Sciences; , 1200, Matsumoto-cho, Kasugai-shi, Aichi 487-8501, Japan
                [ 11 ]Institute for Tropical Biology and Conservation, Universiti Malaysia Sabah, Jalan UMS; , Kota Kinabalu, Sabah 88400, Malaysia
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.7349579.

                Author information
                https://orcid.org/0000-0002-0861-7801
                https://orcid.org/0000-0002-0384-1580
                Article
                rsos231756
                10.1098/rsos.231756
                11265907
                39050721
                00247900-9f0a-4680-b354-440f8252c3bd
                © 2024 The Author(s).

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : November 16, 2023
                : April 23, 2024
                : May 22, 2024
                Funding
                Funded by: Japan Science and Technology Agency Core Research for Evolutional Science and Technology;
                Funded by: Japan Society for the Promotion of Science KAKENHI;
                Categories
                1001
                1001
                60
                200
                Ecology, Conservation, and Global Change Biology
                Research Articles

                borneo,colobines,foregut-fermenters,gut microbiota,primate
                borneo, colobines, foregut-fermenters, gut microbiota, primate

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