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      Comprehensive survey of kombucha microbial communities of diverse origins and fermentation practices

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          Abstract

          Kombucha is a unique, naturally fermented sweetened tea produced for thousands of years, relying on a symbiotic microbiota in a floating biofilm, used for successive fermentations. The microbial communities consist of yeast and bacteria species, distributed across two phases: the liquid and the biofilm fractions. In the fermentation of kombucha, various starters of different shapes and origins are used, and there are multiple brewing practices. By metabarcoding, we explored here the consortia and their evolution from a collection of 23 starters coming from various origins summarizing the diversity of kombucha fermentation processes. A core microbiota of yeast and bacteria has been identified in these diverse kombucha symbiotic consortia, revealing consistent core taxa across symbiotic consortium of bacteria and yeasts from different starters. The common core consists of five taxa: two yeast species from the Brettanomyces genus ( B. bruxellensis and B. anomalus) and bacterial taxa Komagataeibacter, Lactobacillus, and Acetobacteraceae, including the Acetobacter genus. The distribution of yeast and bacteria core taxa differs between the liquid and biofilm fractions, as well as between the “mother” and “daughter” biofilms used in successive fermentations. In terms of microbial composition, the diversity is relatively low, with only a few accessory taxa identified. Overall, our study provides a deeper understanding of the core and accessory taxa involved in kombucha fermentation.

          Abstract

          This study provides valuable insights into the microbial composition of kombucha, highlighting the stable core microbiota and the dynamics of accessory taxa across fermentation cycles.

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          Most cited references37

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          Cutadapt removes adapter sequences from high-throughput sequencing reads

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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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              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
                Journal
                FEMS Yeast Res
                FEMS Yeast Res
                femsyr
                FEMS Yeast Research
                Oxford University Press
                1567-1356
                1567-1364
                2025
                04 February 2025
                04 February 2025
                : 25
                : foaf005
                Affiliations
                Université de Strasbourg , CNRS, GMGM UMR 7156, 67000 Strasbourg, France
                Bio Brasseurs , Strasbourg 67000, France
                Université de Strasbourg , CNRS, GMGM UMR 7156, 67000 Strasbourg, France
                Bio Brasseurs , Strasbourg 67000, France
                Bio Brasseurs , Strasbourg 67000, France
                Université de Strasbourg , CNRS, GMGM UMR 7156, 67000 Strasbourg, France
                Institut Universitaire de France (IUF) , Paris 75231, France
                Université de Strasbourg , CNRS, GMGM UMR 7156, 67000 Strasbourg, France
                Author notes
                Corresponding author. Université de Strasbourg, CNRS, GMGM UMR 7156, 67000 Strasbourg, France. E-mail: schacherer@ 123456unistra.fr
                Corresponding author. bleykasten@ 123456unistra.fr
                Author information
                https://orcid.org/0000-0002-6606-6884
                Article
                foaf005
                10.1093/femsyr/foaf005
                11851468
                39904552
                90cffc89-7fe5-4ac0-a228-29c8ab9243fc
                © The Author(s) 2025. Published by Oxford University Press on behalf of FEMS.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License ( https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 25 November 2024
                : 29 January 2025
                : 03 February 2025
                : 25 February 2025
                Page count
                Pages: 10
                Funding
                Funded by: CIFRE;
                Award ID: 2018/1442
                Categories
                Research Article
                Population Genomics and Ecology
                AcademicSubjects/SCI01150

                Molecular biology
                taxa,cores,yeasts,fermentations,bacteria,symbiotic
                Molecular biology
                taxa, cores, yeasts, fermentations, bacteria, symbiotic

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