Antimicrobial resistance in Brazilian pig and poultry production and its contribution to the success of Salmonella serotypes
Antimicrobial resistance in Brazilian pig and poultry production and its contribution to the success of Salmonella serotypes
批准号:
BB/R022682/1
负责人:
Alison Mather
金额:
$10.28万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --
中文摘要
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英文摘要
Antimicrobial resistance (AMR) of bacteria found in livestock represent a grave threat to the health of both animals and humans; resistant infections in livestock also have a significant economic impact. Salmonella enterica is one of the most important bacterial pathogens in pigs and poultry, which are thought to be two of the major reservoirs for human infections. Brazil is one of the world's largest producers and exporters of pig and chicken meat, and these industries are significant contributors to the country's economy. Change in these production systems over the last 10 years, including massive intensification and introduction of a Salmonella Enteritidis vaccine in poultry, have led to dramatic shifts in the Salmonella serotype prevalence observed from pigs and poultry in Brazil. These shifts are probably driven by antimicrobial use and resistance, but this issue has not been fully investigated. The research outlined in our proposal will investigate the diversity and evolution of AMR determinants in Salmonella isolated from Brazilian pigs and poultry over the last 10 years. We will use whole genome sequencing, and state-of-the-art long read sequencing, combined with molecular biology and epidemiology to explore the role of AMR in the success of different Salmonella serotypes in these populations. This proposal represents a new collaboration between Dr Mather at Quadram Institute Bioscience (QIB) in the UK, and Dr Moreno at the University of São Paulo (USP), along with collaborators Dr Terezinha Knöbl and Dr Luisa Moreno at USP. This research will tackle the huge health and economic threat posed by AMR to Brazilian livestock species, which will help identify where suitable control strategies could be applied most effectively.
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财政年份:2022
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