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      Large-Scale Studies on Antimicrobial Resistance and Molecular Characterization of Escherichia coli from Food Animals in Developed Areas of Eastern China

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          ABSTRACT

          Widely distributed multidrug-resistant (MDR) bacteria threaten animals and human health. Nevertheless, few antimicrobial resistance (AMR) surveys of large-scale animal-derived bacteria have been explored. Here, 1,468 (97.54%) Escherichia coli strains were isolated from 1,505 pig (1,060) and chicken (445) anal swab samples from 11 cities in Zhejiang Province, China, in 2020. These isolates had a high resistance to tetracycline (92.92%), sulfisoxazole (93.05%), florfenicol (83.11%), and ampicillin (78.27%). More than 88.68% of the strains were MDR bacteria. A low AMR ratio to the “last-resort” antimicrobials tigecycline (0.75%), colistin (1.36%), and meropenem (0.75%) were found. The AMR of E. coli from pigs was higher than that of chickens. Eighteen strains among 31 MDR strains that were resistant to “last-resort” antimicrobials could transfer the AMR genes ( mcr-1, tet(X), and bla NDM) to the recipient strain J53, which confer colistin, tigecycline, and carbapenem resistance, respectively. The homology among mcr-1-carrying isolates was relatively high, and the sequence types were mainly ST5529, ST101, and ST354, while the homology of isolates harboring tet(X4) and bla NDM-5 genes were different. The mcr-1, bla NDM-5, and tet(X4) genes in strains LS45, JH51, and TZ118 were identified on the Incl2, IncHI2, and IncX1 plasmids, respectively. Moreover, tet(A), sul2, floR, and bla TEM-1B were the most common ARGs in 31 strains. Additionally, the heavy metals copper and zinc had a significant correlation with amoxicillin/clavulanate and tetracycline resistance. Controlling the movement of animals between cities and reducing the use of antimicrobials are effective methods to reduce the threat of AMR bacteria.

          IMPORTANCE Pigs and chickens are the most common food animals that are the important vectors for spreading antimicrobial-resistant pathogens among animals and humans. Limited systematic AMR monitoring of these food animal origin bacteria had been reported, especially in developed areas of China. Our study provides a comprehensive and systematic study of AMR in Escherichia coli from eastern China. The AMR of E. coli strains among the animals or cities has statistically significant differences. Moreover, the mcr-1, tet(X4), and bla NDM-5 genes, considered resistant to the last line of AMR, were identified in part of farms. The transferability and the prevalence of these AMR strains were intensively studied. Our monitoring is comparable to human clinical research and has an essential reference for public health safety. These findings will provide early warning for AMR strains and guide the clinical use of antibiotics to control the spread of antibiotic resistance.

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          Most cited references42

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          TBtools - an integrative toolkit developed for interactive analyses of big biological data

          The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.
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            Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis

            (2022)
            Summary Background Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. Methods We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. Findings On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. Interpretation To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
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              Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study.

              Until now, polymyxin resistance has involved chromosomal mutations but has never been reported via horizontal gene transfer. During a routine surveillance project on antimicrobial resistance in commensal Escherichia coli from food animals in China, a major increase of colistin resistance was observed. When an E coli strain, SHP45, possessing colistin resistance that could be transferred to another strain, was isolated from a pig, we conducted further analysis of possible plasmid-mediated polymyxin resistance. Herein, we report the emergence of the first plasmid-mediated polymyxin resistance mechanism, MCR-1, in Enterobacteriaceae.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                Microbiol Spectr
                Microbiol Spectr
                spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                11 August 2022
                Jul-Aug 2022
                11 August 2022
                : 10
                : 4
                : e02015-22
                Affiliations
                [a ] State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Institute of Agro-product Safety and Nutrition, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, China
                [b ] Zhejiang Provincial Center for Animal Disease Prevention and Control, Hangzhou Zhejiang, China
                [c ] College of Food Science and Technology, Zhejiang University of Technologygrid.469325.f, , Hangzhou, Zhejiang, China
                [d ] Key Laboratory of Marine Food Quality and Hazard Controlling Technology of Zhejiang Province, China Jiliang University, Hangzhou, Zhejiang, China
                [e ] School of Marine Science, Ningbo University, Ningbo, Zhejiang, China
                [f ] CAS Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciencesgrid.419092.7, , Chinese Academy of Sciences, Shanghai, China
                University of Maryland Eastern Shore
                Author notes

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-3605-4022
                Article
                02015-22 spectrum.02015-22
                10.1128/spectrum.02015-22
                9430128
                35950758
                9c6e01d4-6d1b-4544-ada2-22c0463bcc1a
                Copyright © 2022 Ma et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 30 May 2022
                : 22 July 2022
                Page count
                supplementary-material: 1, Figures: 8, Tables: 1, Equations: 0, References: 42, Pages: 15, Words: 6974
                Funding
                Funded by: State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products;
                Award ID: 2010DS700124-ZZ2008, ZZ2102
                Award Recipient :
                Funded by: Key Research and Development Program of Zhejiang Province;
                Award ID: 2020C02031
                Award Recipient :
                Funded by: Collaborative Extension Plan of Major Agricultural Technologies in Zhejiang Province;
                Award ID: 2021XTTGXM03
                Award Recipient :
                Funded by: MOST | National Key Research and Development Program of China (NKPs), FundRef https://doi.org/10.13039/501100012166;
                Award ID: 2019YFE0103900
                Award Recipient :
                Categories
                Research Article
                public-health, Public Health
                Custom metadata
                July/August 2022

                escherichia coli,antimicrobial resistance,antimicrobial resistance gene,food animal,heavy metal

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