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      To culture or not to culture: careful assessment of metabarcoding data is necessary when evaluating the microbiota of a modified-atmosphere-packaged vegetarian meat alternative throughout its shelf-life period

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          Abstract

          Background

          As the increased consumption of ready-to-eat meat alternatives is a fairly recent trend, little is known about the composition and dynamics of the microbiota present on such products. Such information is nonetheless valuable in view of spoilage and food safety prevention. Even though refrigeration and modified-atmosphere-packaging (MAP) can extend the shelf-life period, microbial spoilage can still occur in these products. In the present study, the microbiota of a vegetarian alternative to poultry-based charcuterie was investigated during storage, contrasting the use of a culture-dependent method to a culture-independent metagenetic method.

          Results

          The former revealed that lactic acid bacteria (LAB) were the most abundant microbial group, specifically at the end of the shelf-life period, whereby Latilactobacillus sakei was the most abundant species. Metabarcoding analysis, in contrast, revealed that DNA of Xanthomonas was most prominently present, which likely was an artifact due to the presence of xanthan gum as an ingredient, followed by Streptococcus and Weissella.

          Conclusions

          Taken together, these results indicated that Lb. sakei was likely the most prominent specific spoilage organisms (SSO) and, additionally, that the use of metagenetic analysis needs to be interpreted with care in this specific type of product. In order to improve the performance of metagenetics in food samples with a high DNA matrix but a low bacterial DNA load, selective depletion techniques for matrix DNA could be explored.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12866-022-02446-9.

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          Most cited references49

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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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            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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              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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                Author and article information

                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                1471-2180
                25 January 2022
                25 January 2022
                2022
                : 22
                : 34
                Affiliations
                [1 ]Flanders Research Institute for Agriculture, Fisheries and Food (ILVO)– Technology and Food Science Unit, 9090 Melle, Belgium
                [2 ]GRID grid.8767.e, ISNI 0000 0001 2290 8069, Research Group of Industrial Microbiology and Food Biotechnology (IMDO), Faculty of Sciences and Bioengineering Sciences, , Vrije Universiteit Brussel, ; Brussels, Belgium
                [3 ]GRID grid.5342.0, ISNI 0000 0001 2069 7798, Department of Pathology, Bacteriology and Avian Diseases, , Ghent University, ; B-9820 Merelbeke, Belgium
                Article
                2446
                10.1186/s12866-022-02446-9
                8788083
                35078415
                97cae3e0-08a7-4e9b-9ebb-251823d5b7e6
                © The Author(s) 2022

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 25 June 2021
                : 10 January 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Microbiology & Virology
                vegetarian charcuterie,microbial ecology,spoilage
                Microbiology & Virology
                vegetarian charcuterie, microbial ecology, spoilage

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