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      Comparative genomic and transmission analysis of Clostridioides difficile between environmental, animal, and clinical sources in China

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          ABSTRACT

          Clostridioides difficile is the most common pathogen causing antibiotic-associated diarrhea. Previous studies showed that diverse sources, aside from C. difficile infection (CDI) patients, played a major role in C. difficile hospital transmission. This study aimed to investigate relationships and transmission potential of C. difficile strains from different sources. A prospective study was conducted both in the intensive care unit (ICU) and six livestock farms in China in 2018–2019. Ninety-eight strains from CDI patients (10 isolates), asymptomatic hospitalized carriers (55), the ICU environment (12), animals (14), soil (4), and farmers (3) were collected. Sequence type (ST) 3/ribotype (RT) 001, ST35/RT046, and ST48/RT596 were dominant types, distributed widely in multiple sources. Core-genome single-nucleotide polymorphism (cgSNP) analysis showed that hospital and farm strains shared several common clonal groups (CGs, strains separated by ≤ 2 cgSNPs) (CG4/ST3/RT001, CG7/ST35/RT046, CG11/ST48/RT596). CDI patients, asymptomatic carriers, and the ICU environment strains also shared several common CGs. The number of virulence genes was not statistically different between strains from different sources. Multi-source strains in the same CG carried identical virulence gene sequences, including pathogenicity genes at the pathogenicity locus and adhesion-related genes at S-layer cassette. Resistance genes ( ermB, tetM, etc.) were widespread in multiple sources, and multi-source strains in the same CG had similar resistance phenotypes and carried consistent transposons and plasmid types. The study indicated that interspecies and cross-regional transmission of C. difficile occurs between animals, the environment, and humans. Community-associated strains from both farms and asymptomatic hospitalized carriers were important reservoirs of CDI in hospitals.

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          Most cited references49

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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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            Prokka: rapid prokaryotic genome annotation.

            T Seemann (2014)
            The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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              MEGA11: Molecular Evolutionary Genetics Analysis Version 11

              The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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                Author and article information

                Journal
                Emerg Microbes Infect
                Emerg Microbes Infect
                Emerging Microbes & Infections
                Taylor & Francis
                2222-1751
                1 December 2021
                2021
                1 December 2021
                : 10
                : 1
                : 2244-2255
                Affiliations
                [a ]State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital , Zhejiang University School of Medicine , Hangzhou, People’s Republic of China
                [b ]Department of Intensive Care Unit, the First Affiliated Hospital , Zhejiang University School of Medicine , Hangzhou, People’s Republic of China
                [c ]Shenzhen Institute of Respiratory Diseases , the First Affiliated Hospital (Shenzhen People’s Hospital) , Southern University of Science and Technology, and Second Clinical Medical College , Jinan University , Shenzhen, People’s Republic of China
                [d ]Department of Swine Infectious Diseases, Shanghai Veterinary Research Institute , Chinese Academy of Agricultural Sciences, Shanghai, PR People’s Republic of China.
                Author notes
                [CONTACT ] Yonghong Xiao xiaoyonghong@ 123456zju.edu.cn State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital , Zhejiang University School of Medicine , Hangzhou, People’s Republic of China, 310003;
                [†]

                YZZ, WXZ and TTX contributed equally to this work.

                Supplemental data for this article can be accessed https://doi.org/10.1080/22221751.2021.2005453

                Author information
                https://orcid.org/0000-0002-7320-291X
                https://orcid.org/0000-0003-4845-5904
                Article
                2005453
                10.1080/22221751.2021.2005453
                8648027
                34756150
                b2c415b4-374c-4fbe-a29f-07f22297fd4b
                © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 49, Pages: 12
                Categories
                Research Article
                Research Article

                clostridioides difficile infection,asymptomatic carrier,multiple sources,comparative genome,transmission

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