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      A glimpse of antimicrobial resistance gene diversity in kefir and yoghurt

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          Abstract

          Antimicrobial resistance (AMR) is a global threat gaining more and more practical significance every year. The main determinants of AMR are the antimicrobial resistance genes (ARGs). Since bacteria can share genetic components via horizontal gene transfer, even non-pathogenic bacteria may provide ARG to any pathogens which they become physically close to (e.g. in the human gut). In addition, fermented food naturally contains bacteria in high amounts. In this study, we examined the diversity of ARG content in various kefir and yoghurt samples (products, grains, bacterial strains) using a unified metagenomic approach. We found numerous ARGs of commonly used fermenting bacteria. Even with the strictest filter restrictions, we identified ARGs undermining the efficacy of aminocoumarins, aminoglycosides, carbapenems, cephalosporins, cephamycins, diaminopyrimidines, elfamycins, fluoroquinolones, fosfomycins, glycylcyclines, lincosamides, macrolides, monobactams, nitrofurans, nitroimidazoles, penams, penems, peptides, phenicols, rifamycins, tetracyclines and triclosan. In the case of gene lmrD, we detected genetic environment providing mobility of this ARG. Our findings support the theory that during the fermentation process, the ARG content of foods can grow due to bacterial multiplication. The results presented suggest that the starting culture strains of fermented foods should be monitored and selected in order to decrease the intake of ARGs via foods.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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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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              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
                solymosi.norbert@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 December 2020
                31 December 2020
                2020
                : 10
                : 22458
                Affiliations
                [1 ]GRID grid.483037.b, ISNI 0000 0001 2226 5083, Centre for Bioinformatics, , University of Veterinary Medicine Budapest, ; Budapest, 1078 Hungary
                [2 ]GRID grid.5591.8, ISNI 0000 0001 2294 6276, Department of Phyisics of Complex Systems, , Eötvös Loránd University, ; Budapest, 1117 Hungary
                [3 ]GRID grid.481816.2, Institute of Plant Biology, Biological Research Center, ; Szeged, 6726 Hungary
                [4 ]Faculty of Water Sciences, University of Public Service, Baja, 6050 Hungary
                [5 ]GRID grid.483037.b, ISNI 0000 0001 2226 5083, Department of Pharmacology and Toxicology, , University of Veterinary Medicine Budapest, ; Budapest, 1078 Hungary
                [6 ]Department of Surgery, Paracelsus Medical University, Nuremberg, 90419 Germany
                [7 ]GRID grid.11804.3c, ISNI 0000 0001 0942 9821, Department of Internal Medicine and Hematology, , Semmelweis University, ; Budapest, 1088 Hungary
                [8 ]GRID grid.11804.3c, ISNI 0000 0001 0942 9821, Interdisciplinary Gastroenterology (IGA) Working Group, , Semmelweis University, ; Budapest, 1085 Hungary
                [9 ]GRID grid.483037.b, ISNI 0000 0001 2226 5083, Department of Microbiology and Infectious Diseases, , University of Veterinary Medicine Budapest, ; Budapest, 1143 Hungary
                [10 ]GRID grid.417756.6, Institute for Veterinary Medical Research, Centre for Agricultural Research, ; Budapest, 1143 Hungary
                [11 ]GRID grid.483037.b, ISNI 0000 0001 2226 5083, Department of Food Hygiene, , University of Veterinary Medicine Budapest, ; Budapest, 1078 Hungary
                Article
                80444
                10.1038/s41598-020-80444-5
                7775456
                33384459
                f7acc5eb-1b8d-4ae2-9ce7-8bed224dc966
                © The Author(s) 2020

                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/.

                History
                : 23 September 2020
                : 21 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004895, European Social Fund;
                Award ID: EFOP-3.6.3-VEKOP-16- 2017-00005
                Award ID: EFOP-3.6.3-VEKOP-16- 2017-00005
                Award ID: EFOP-3.6.3-VEKOP-16- 2017-00005
                Award ID: EFOP-3.6.3-VEKOP-16- 2017-00005
                Funded by: European Union’s Horizon 2020 research and innovation program
                Award ID: 874735 (VEO)
                Award ID: 874735 (VEO)
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                nutrition,risk factors,antimicrobial resistance,bacterial genomics
                Uncategorized
                nutrition, risk factors, antimicrobial resistance, bacterial genomics

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