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      The wasted chewing gum bacteriome

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          Abstract

          Here we show the bacteriome of wasted chewing gums from five different countries and the microbial successions on wasted gums during three months of outdoors exposure. In addition, a collection of bacterial strains from wasted gums was set, and the biodegradation capability of different gum ingredients by the isolates was tested. Our results reveal that the oral microbiota present in gums after being chewed, characterised by the presence of species such as Streptococcus spp. or Corynebacterium spp., evolves in a few weeks to an environmental bacteriome characterised by the presence of Acinetobacter spp., Sphingomonas spp. and Pseudomonas spp. Wasted chewing gums collected worldwide contain a typical sub-aerial biofilm bacteriome, characterised by species such as Sphingomonas spp., Kocuria spp., Deinococcus spp. and Blastococcus spp. Our findings have implications for a wide range of disciplines, including forensics, contagious disease control, or bioremediation of wasted chewing gum residues.

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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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              Double-slit photoelectron interference in strong-field ionization of the neon dimer

              Wave-particle duality is an inherent peculiarity of the quantum world. The double-slit experiment has been frequently used for understanding different aspects of this fundamental concept. The occurrence of interference rests on the lack of which-way information and on the absence of decoherence mechanisms, which could scramble the wave fronts. Here, we report on the observation of two-center interference in the molecular-frame photoelectron momentum distribution upon ionization of the neon dimer by a strong laser field. Postselection of ions, which are measured in coincidence with electrons, allows choosing the symmetry of the residual ion, leading to observation of both, gerade and ungerade, types of interference.
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                Author and article information

                Contributors
                manuel.porcar@uv.es
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 October 2020
                8 October 2020
                2020
                : 10
                : 16846
                Affiliations
                [1 ]GRID grid.5338.d, ISNI 0000 0001 2173 938X, Institute for Integrative Systems Biology I2SysBio, , Universitat de València-CSIC, ; Catedrático José Beltrán 2, 46980 Paterna, Spain
                [2 ]Darwin Bioprospecting Excellence SL, Catedrático Agustín Escardino 9, 46980 Paterna, Spain
                Article
                73913
                10.1038/s41598-020-73913-4
                7545173
                33033386
                e542ce00-0a6d-4a40-9967-8cd29bf000f7
                © The Author(s) 2020

                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 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
                : 17 July 2020
                : 14 September 2020
                Funding
                Funded by: European CSA
                Award ID: 820699
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100014440, Ministerio de Ciencia, Innovación y Universidades;
                Award ID: FPU18/02578.
                Award Recipient :
                Categories
                Article
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                © The Author(s) 2020

                Uncategorized
                environmental microbiology,applied microbiology
                Uncategorized
                environmental microbiology, applied microbiology

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