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      Abundance and diversity of resistomes differ between healthy human oral cavities and gut

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          Abstract

          The global threat of antimicrobial resistance has driven the use of high-throughput sequencing techniques to monitor the profile of resistance genes, known as the resistome, in microbial populations. The human oral cavity contains a poorly explored reservoir of these genes. Here we analyse and compare the resistome profiles of 788 oral cavities worldwide with paired stool metagenomes. We find country and body site-specific differences in the prevalence of antimicrobial resistance genes, classes and mechanisms in oral and stool samples. Within individuals, the highest abundances of antimicrobial resistance genes are found in the oral cavity, but the oral cavity contains a lower diversity of resistance genes compared to the gut. Additionally, co-occurrence analysis shows contrasting ARG-species associations between saliva and stool samples. Maintenance and persistence of antimicrobial resistance is likely to vary across different body sites. Thus, we highlight the importance of characterising the resistome across body sites to uncover the antimicrobial resistance potential in the human body.

          Abstract

          Antimicrobial resistance (AMR) represents a global health threat. Here, the authors analyse the oral and gut resistomes from metagenomes of diverse populations and find that the oral resistome harbours higher abundance but lower diversity of antimicrobial resistance genes than the gut resistome.

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Contributors
                victoria.carr@kcl.ac.uk
                david.moyes@kcl.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                4 February 2020
                4 February 2020
                2020
                : 11
                : 693
                Affiliations
                [1 ]ISNI 0000 0001 2322 6764, GRID grid.13097.3c, Centre for Host-Microbiome Interactions, Faculty of Dentistry, , Oral and Craniofacial Sciences, King’s College London, ; London, UK
                [2 ]ISNI 0000000121581746, GRID grid.5037.1, Science for Life Laboratory, , KTH—Royal Institute of Technology, ; SE-171 21 Stockholm, Sweden
                [3 ]ISNI 0000000121901201, GRID grid.83440.3b, Microbial Diseases, Eastman Dental Institute, , University College London, ; London, UK
                [4 ]Translational Bioinformatics Unit, NavarraBiomed, Departamento de Salud-Universidad Pública de Navarra, Pamplona, 31008 Navarra, Spain
                [5 ]ISNI 0000 0000 9241 5705, GRID grid.24381.3c, Unit for Computational Medicine, , Karolinska Institutet (L8:05). Karolinska University Hospital, ; SE-171 76 Stockholm, Sweden
                Author information
                http://orcid.org/0000-0001-5834-4533
                http://orcid.org/0000-0002-5684-841X
                Article
                14422
                10.1038/s41467-020-14422-w
                7000725
                32019923
                ed162a8b-c566-4080-8fa5-55c4471c77fc
                © The Author(s) 2020

                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
                : 6 April 2019
                : 16 December 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000266, RCUK | Engineering and Physical Sciences Research Council (EPSRC);
                Award ID: EP/S001301/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/M009513/1
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                data processing,bacterial genes
                Uncategorized
                data processing, bacterial genes

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