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A novel approach to reducing multiple-drug resistance in foodborne bacteria: application of CRISPR technology

A novel approach to reducing multiple-drug resistance in foodborne bacteria: application of CRISPR technology
降低食源性细菌多重耐药性的新方法:CRISPR技术的应用
批准号:
2443565
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金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --

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英文摘要
The testable hypothesis is that the CRISPR-Cas systems may be exploited to reduce the burden of drug resistance in bacterial populations in animal production such that (a) the risk of resistance passing into the human food chain is dramatically reduced and (b) that targeted removal of specific resistance will permit use of the antibiotic, thus expanding the potential utility of all antibiotics. The system consists of a sequence-specific nuclease (Cas9) and aguide RNA (gRNA) that provides sequence specificity to its DNA cleavage activity. CRISPR-Cas9 is a versatile and highly specific next-generation antimicrobial that allows targeting of specific pathogenic bacteria while leaving the remaining microbiome intact. Preliminary data generated by the commercial partner, Folium Science, has demonstrated the first in vivo application of CRISPR technology to specifically reduce the burden of Salmonella in poultry (Cogan et al, in press ). Conjugative delivery of CRISPR-Cas9 and target-specific gRNA by a mobilisable plasmid from a donor bacterium (a 'probiotic') to Salmonella caused degradation of the DNA of the targeted bacteriumand subsequent bacterial cell death.Alternative delivery systems such as modified bacteriophages (bacterial viruses) can also be utilised. resistant (MDR) bacteriain animal production. Recent studies demonstrated very high prevalence of MDR bacteria in commercial poultry production. Avian Pathogenic E. coli (APEC) have been identified as a risk factor in Urinary Tract Infection (UTI) in humans and resistance means treatment failure. The overall goal is to devise a CRISPR-Cas system that effectively reduces the incidence of selected test antibiotic resistance genes (e.g. CTX-M 15) for use in poultry in the first instance. Four objectives will be delivered, each a specialism of the two partner Universities. (1) In silico analysis of WGS data from commercial broiler poultry microbiomes will be undertaken to identify antibiotic resistance genes, their prevalence and probable vectors (e.g. plasmid incompatibility (Inc) groups). Targets (guides with relevant PAM motif for Cas activity) will be selected and tested by BLAST searches for specificity to the target gene. This process will also identify suitable gene positive/negative strains for in vitro and in vivo testing and information on the distribution of CRISPR-Cas systems within those strains. (2) Ta r ge t sequences will be synthesised and assembled by Golden Gate cloning into Folium vectors constitutively expressing Cas9 or Type I CRISPR-Cas genes. The testing of the utility of the guide sequences is empirical using gene positive/negative recipients from [1] above. The constructs will be mobilised into test strains and loss of the targeted resistance monitored both phenotypically and genotypically. (3) Prior to in vivo studies, in vitro gut poultry models will be exploited to determine the dynamics of delivery of the CRISPR-Cas system to the poultry gut microbial community and assess reduction of the target resistance gene and its associated vector. Mathematical modelling of rates of transfer and diversity of recipient microbes will be developed to provide information related to enhancing and/or specifying range of conjugation recipients. (4) The CRISPR-Cas probiotic strain developed in 1-3 above will then be used in commercial broiler chicks un-primed and primed with a target strain using appropriate third-party chicken containment facilities e.g. APHA (Weybridge). Detailed microbial molecular profiling will be undertaken to examine dissemination of the CRISPR-Cas system, the loss of the targeted AMR gene and any population shifts in the gut microbiome.
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量化 domain 的拓扑性质
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    2017
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    赖洪亮
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    3.0万元
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  • 资助金额:
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