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      Metagenomics analysis of bacteriophages and antimicrobial resistance from global urban sewage

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          Abstract

          Bacteriophages, or phages, are ubiquitous bacterial and archaeal viruses with an estimated total global population of 10 31. It is well-known that wherever there are bacteria, their phage counterparts will be found, aiding in shaping the bacterial population. The present study used metagenomic data from global influent sewage in 79 cities in 60 countries to identify phages associated with bacteria and to explore their potential role in antimicrobial resistance gene (ARG) dissemination. The reads were mapped to known databases for bacteriophages and their abundances determined and correlated to geographic origin and the countries socio-economic status, as well as the abundances of bacterial species and ARG. We found that some phages were not equally distributed on a global scale, but their distribution was rather dictated by region and the socioeconomic status of the specific countries. This study provides a preliminary insight into the global and regional distribution of phages and their potential impact on the transmission of ARGs between bacteria. Moreover, the findings may indicate that phages in sewage could have adopted a lytic lifestyle, meaning that most may not be associated with bacteria and instead may be widely distributed as free-living phages, which are known to persist longer in the environment than their hosts. In addition, a significant correlation between phages and ARGs was obtained, indicating that phages may play a role in ARG dissemination. However, further analyses are needed to establish the true relationship between phages and ARGs due to a low abundance of the phages identified.

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          Most cited references34

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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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            New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

            PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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              Interactive Tree Of Life (iTOL) v4: recent updates and new developments

              Abstract The Interactive Tree Of Life (https://itol.embl.de) is an online tool for the display, manipulation and annotation of phylogenetic and other trees. It is freely available and open to everyone. The current version introduces four new dataset types, together with numerous new features. Annotation options have been expanded and new control options added for many display elements. An interactive spreadsheet-like editor has been implemented, providing dataset creation and editing directly in the web interface. Font support has been rewritten with full support for UTF-8 character encoding throughout the user interface. Google Web Fonts are now fully supported in the tree text labels. iTOL v4 is the first tool which supports direct visualization of Qiime 2 trees and associated annotations. The user account system has been streamlined and expanded with new navigation options, and currently handles >700 000 trees from more than 40 000 individual users. Full batch access has been implemented allowing programmatic upload and export of trees and annotations.
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                Author and article information

                Contributors
                pile@food.dtu.dk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 January 2021
                15 January 2021
                2021
                : 11
                : 1600
                Affiliations
                GRID grid.5170.3, ISNI 0000 0001 2181 8870, Research Group for Genomic Epidemiology, National Food Institute, , Technical University of Denmark, ; Building 204, 2800 Kemitorvet, Kgs. Lyngby Denmark
                Article
                80990
                10.1038/s41598-021-80990-6
                7810828
                33452346
                4bf645cc-66e8-4cde-b5a4-b7eb65b4ce4e
                © The Author(s) 2021

                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
                : 21 October 2020
                : 29 December 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100009708, Novo Nordisk Fonden;
                Award ID: NNF16OC0021856
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                antimicrobials,bacteriophages
                Uncategorized
                antimicrobials, bacteriophages

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