Literature DB >> 25785064

Molecular classification and drug resistance analysis of Escherichia coli isolated from poultry in China.

Wenyan Gai1, Junwei Wang1, Juan Wang1, Zhigang Cui2, Zhina Qu1, Jinghua Cui2, Xiaoli Du2, Xiumei Huang1, Jianmei Zhao1.   

Abstract

We aimed to understand the distribution of Escherichia coli in poultry and to reveal the virulence factors, the drug resistance and molecular epidemic regularity and characteristics of isolate strains from 6 provinces in China and to complete the characteristics of E. coli for the risk assessment. A total of 87 E. coli isolates were analyzed with 7 virulence genes by PCR drug sensitivity test in 13 kinds of antimicrobial agents and analyzed with PFGE and MLST genotyping. The PFGE genotyping of 87 isolates yielded 75 PFGE type. MLST analysis of isolates identified the 39 STs, the 7 housekeeping genes had the different variation. The most prevalent virulence genes were iucD (74.7%), followed by iss (55.2%), Irp2 (43.7%), tsh (28.7%), cva (19.5%), papC (9.2%) and vat (8.1%). All isolates were resistant to two or three antimicrobial agents highly resistant to SXT, TE (85.06%), SF (83.91%), AM (66. 67%), to fluoroquinolones (ENR, 63.22%, NOR, 50.57%) and to GM (57.47%). E. coli strains resistant spectrum was wide gene was polymorphism the distribution had a certain timeliness and regional in part region of China. These were a solid foundation for the epidemiological investigation and traceability laid.

Entities:  

Keywords:  Escherichia coli; drug resistance; multilocus sequence analysis; poultry; pulsed-field gel electrophoresis; resistance gene; virulence genes

Year:  2015        PMID: 25785064      PMCID: PMC4358519     

Source DB:  PubMed          Journal:  Int J Clin Exp Med        ISSN: 1940-5901


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1.  Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming.

Authors:  Zixin Peng; Alexandre Maciel-Guerra; Michelle Baker; Xibin Zhang; Yue Hu; Wei Wang; Jia Rong; Jing Zhang; Ning Xue; Paul Barrow; David Renney; Dov Stekel; Paul Williams; Longhai Liu; Junshi Chen; Fengqin Li; Tania Dottorini
Journal:  PLoS Comput Biol       Date:  2022-03-25       Impact factor: 4.475

  1 in total

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