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      Pervasive transmission of a carbapenem resistance plasmid in the gut microbiota of hospitalised patients

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          Introductory paragraph

          Infections caused by carbapenemase-producing enterobacteria (CPE) are a major concern in clinical settings worldwide. Two fundamentally different processes shape the epidemiology of CPE in hospitals: the dissemination of CPE clones from patient to patient (between-patient transfer), and the transfer of carbapenemase-encoding plasmids between enterobacteria in the gut microbiota of individual patients (within-patient transfer). The relative contribution of each process to the overall dissemination of carbapenem resistance in hospitals remains poorly understood. Here, we used mechanistic models combining epidemiological data from more than 9,000 patients with whole genome sequence information from 250 enterobacteria clones to characterise the dissemination routes of a pOXA-48-like carbapenemase-encoding plasmid in a hospital setting over a two-year period. Our results revealed frequent between-patient transmission of high-risk pOXA-48-carrying clones, mostly of Klebsiella pneumoniae and sporadically Escherichia coli. The results also identified pOXA-48 dissemination hotspots within the hospital, such as specific wards and individual rooms within wards. Using high-resolution plasmid sequence analysis, we uncovered the pervasive within-patient transfer of pOXA-48, suggesting that horizontal plasmid transfer occurs in the gut of virtually every colonised patient. The complex and multifaceted epidemiological scenario exposed by this study provides insights for the development of intervention strategies to control the in-hospital spread of CPE.

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          Most cited references63

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          Is Open Access

          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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            Is Open Access

            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

              The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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                Author and article information

                Journal
                101674869
                Nat Microbiol
                Nat Microbiol
                Nature microbiology
                2058-5276
                13 February 2021
                01 May 2021
                29 March 2021
                29 September 2021
                : 6
                : 5
                : 606-616
                Affiliations
                [1 ] Servicio de Microbiología. Hospital Universitario Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria. Madrid, Spain
                [2 ] Centro de Investigación Biológica en Red. Epidemiología y Salud Pública, Instituto de Salud Carlos III. Madrid . Spain
                [3 ] Servicio de Medicina Preventiva y Salud Pública, Hospital Universitario Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria. Madrid, Spain
                [4 ]Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
                [5 ]Centre for Tropical Medicine & Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
                [6 ] Red Española de Investigación en Patología Infecciosa. Instituto de Salud Carlos III. Madrid. Spain
                [8 ] Centro Nacional de Biotecnología–CSIC, Madrid, Spain
                Author notes
                [* ]Correspondence: asanmillan@ 123456cnb.csic.es ; Alvaro San Millan is the author to whom correspondence and requests for materials should be addressed

                A full list of members and their affiliations appears in the Supplementary Information.

                Author information
                http://orcid.org/0000-0001-8544-0387
                Article
                EMS116488
                10.1038/s41564-021-00879-y
                7610705
                33782584
                a39834ef-6b18-49ab-a96c-54797d125e1e

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