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      The amphibian microbiome exhibits poor resilience following pathogen-induced disturbance

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          Abstract

          Infectious pathogens can disrupt the microbiome in addition to directly affecting the host. Impacts of disease may be dependent on the ability of the microbiome to recover from such disturbance, yet remarkably little is known about microbiome recovery after disease, particularly in nonhuman animals. We assessed the resilience of the amphibian skin microbial community after disturbance by the pathogen, Batrachochytrium dendrobatidis (Bd). Skin microbial communities of laboratory-reared mountain yellow-legged frogs were tracked through three experimental phases: prior to Bd infection, after Bd infection (disturbance), and after clearing Bd infection (recovery period). Bd infection disturbed microbiome composition and altered the relative abundances of several dominant bacterial taxa. After Bd infection, frogs were treated with an antifungal drug that cleared Bd infection, but this did not lead to recovery of microbiome composition (measured as Unifrac distance) or relative abundances of dominant bacterial groups. These results indicate that Bd infection can lead to an alternate stable state in the microbiome of sensitive amphibians, or that microbiome recovery is extremely slow—in either case resilience is low. Furthermore, antifungal treatment and clearance of Bd infection had the additional effect of reducing microbial community variability, which we hypothesize results from similarity across frogs in the taxa that colonize community vacancies resulting from the removal of Bd. Our results indicate that the skin microbiota of mountain yellow-legged frogs has low resilience following Bd-induced disturbance and is further altered by the process of clearing Bd infection, which may have implications for the conservation of this endangered amphibian.

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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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            The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

            SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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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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                Author and article information

                Contributors
                jania@hawaii.edu
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                9 February 2021
                9 February 2021
                June 2021
                : 15
                : 6
                : 1628-1640
                Affiliations
                [1 ]GRID grid.410445.0, ISNI 0000 0001 2188 0957, Department of Oceanography, Center for Microbial Oceanography: Research and Education (CMORE), , University of Hawai’i at Mànoa, ; Honolulu, HI USA
                [2 ]GRID grid.410445.0, ISNI 0000 0001 2188 0957, Pacific Biosciences Research Center, University of Hawai’i at Mànoa, ; Honolulu, HI USA
                [3 ]GRID grid.487732.d, ISNI 0000 0001 2202 7018, San Francisco Zoological Society, ; San Francisco, CA USA
                [4 ]GRID grid.410445.0, ISNI 0000 0001 2188 0957, Information and Computer Sciences, , University of Hawai’i at Mànoa, ; Honolulu, HI USA
                [5 ]GRID grid.454846.f, ISNI 0000 0001 2331 3972, Sequoia and Kings Canyon National Parks, , National Park Service, ; Three Rivers, CA USA
                [6 ]USDA Forest Service, Stanislaus National Forest, Sonora, CA USA
                [7 ]Sierra Nevada Aquatic Research Laboratory, University of California, Mammoth Lakes, CA USA
                Author information
                http://orcid.org/0000-0001-8719-2962
                http://orcid.org/0000-0001-5255-0942
                http://orcid.org/0000-0002-1954-2745
                Article
                875
                10.1038/s41396-020-00875-w
                8163836
                33564111
                874a09ad-b866-45f3-b887-5c6a86ae53a2
                © 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
                : 18 August 2020
                : 24 November 2020
                : 7 December 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: IOS-1455873
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to International Society for Microbial Ecology 2021

                Microbiology & Virology
                microbial ecology,community ecology
                Microbiology & Virology
                microbial ecology, community ecology

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