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      Interpretation of gut microbiota data in the ‘eye of the beholder’: A commentary and re‐evaluation of data from ‘Impacts of radiation exposure on the bacterial and fungal microbiome of small mammals in the Chernobyl Exclusion Zone’

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          Abstract

          1. Evidence that exposure to environmental pollutants can alter the gut microbiota composition of wildlife includes studies of rodents exposed to radionuclides.

          2. Antwis et al. (2021) used amplicon sequencing to characterise the gut microbiota of four species of rodent ( Myodes glareolus, Apodemus agrarius, A. flavicollis and A. sylvaticus) inhabiting the Chernobyl Exclusion Zone (CEZ) to examine possible changes in gut bacteria (microbiota) and gut fungi (mycobiota) associated with exposure to radionuclides and whether the sample type (from caecum or faeces) affected the analysis.

          3. The conclusions derived from the analyses of gut mycobiota are based on data that represent a mixture of ingested fungi (e.g. edible macrofungi, polypores, lichens and ectomycorrhizae) and gut mycobiota (e.g. microfungi and yeasts), which mask the patterns of inter‐ and intraspecific variation in the authentic gut mycobiota.

          4. Implying that ‘faecal samples are not an accurate indicator of gut composition’ creates an unnecessary controversy about faecal sampling because the comparison of samples from the caecum and faeces confounds many other possible drivers (including different animals from different locations, sampled in different years) of variation in gut microbiota.

          5. It is relevant also that Antwis et al.'s (2021) data lack statistical power to detect an effect of exposure to radionuclides on the gut microbiota because (1) all of their samples of Apodemus mice had experienced a medium or high total absorbed dose rate and (2) they did not collect samples of bank voles ( M. glareolus) from replicate contaminated and uncontaminated locations.

          6. Discussion of Antwis et al.'s (2021) analysis, especially the claims presented in the Abstract, is important to prevent controversy about the outcome of research on the biological impacts of wildlife inhabiting the CEZ.

          Abstract

          The authors' work highlights: (1) the need to consider host and fungal ecology when analysing the apparent assemblages of fungi from animal gastrointestinal tracts, and (2) that differences in sampling and laboratory protocols need to be fully considered when making a contrast between separate studies of wildlife gut microbiota. Photo credit: Pinja Rautio.

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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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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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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
                phillip.c.watts@jyu.fi
                Journal
                J Anim Ecol
                J Anim Ecol
                10.1111/(ISSN)1365-2656
                JANE
                The Journal of Animal Ecology
                John Wiley and Sons Inc. (Hoboken )
                0021-8790
                1365-2656
                13 June 2022
                July 2022
                : 91
                : 7 ( doiID: 10.1111/jane.v91.7 )
                : 1535-1545
                Affiliations
                [ 1 ] Department of Biological and Environmental Science University of Jyväskylä Jyväskylä Finland
                [ 2 ] National Research Center for Radiation Medicine of the National Academy of Medical Science Kyiv Ukraine
                [ 3 ] Department of Biological Sciences University of South Carolina Columbia South Carolina USA
                [ 4 ] CIBIO/InBio, Research Centre in Biodiversity and Genetic Resources University of Porto Vairão Portugal
                [ 5 ] Laboratoire d’Ecologie, Systématique et Evolution CNRS UMR 8079, Université Paris‐Sud 11 Orsay Cedex France
                Author notes
                [*] [* ] Correspondence

                Phillip C. Watts

                Email: phillip.c.watts@ 123456jyu.fi

                Author information
                https://orcid.org/0000-0001-7755-187X
                https://orcid.org/0000-0002-2235-4868
                https://orcid.org/0000-0002-9524-8054
                Article
                JANE13667 JAE-2021-00827.R1
                10.1111/1365-2656.13667
                9541917
                35694772
                21b04a1a-ffa1-4a95-9be5-e71d44536ce9
                © 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 October 2021
                : 05 January 2022
                Page count
                Figures: 5, Tables: 2, Pages: 11, Words: 8016
                Funding
                Funded by: Academy of Finland , doi 10.13039/501100002341;
                Award ID: 287153
                Award ID: 324602
                Award ID: 268670
                Award ID: 324604
                Funded by: Oskar Öflund Stiftelse
                Funded by: Samuel Freeman Charitable Trust
                Funded by: Scholarship Fund of the University of Oulu
                Funded by: University of Oulu Graduate School doctoral programme
                Categories
                Forum
                Forum
                Custom metadata
                2.0
                July 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.0 mode:remove_FC converted:07.10.2022

                Ecology
                amplicon sequencing,diet,microbiota,mycobiota,radiation effects
                Ecology
                amplicon sequencing, diet, microbiota, mycobiota, radiation effects

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