Investigating the bacterial response to antimicrobials in kidney organoids.
Investigating the bacterial response to antimicrobials in kidney organoids.
批准号:
2890743
负责人:
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:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
Bacterial urinary tract infections (UTIs) are very common; 50% of catheterized patients develop UTIs, which are 40% of hospital-acquired infections, and 33% of otherwise-healthy women will suffer a UTI by 24. Serious cases of UTIs damage kidneys and can lead to sepsis underscoring the urgent need to better understand and treat these infections. Escherichia coli is the dominant cause, and 30% of UTIs are now resistant to the classic treatment, co-trimoxazole4, leading to increased use of other antibiotics such as ciprofloxacin or trimethoprim.Determining how efficient antibiotic treatments can be used against UTIs, requires a realistic UTI model but there are no good animal models; mice get UTIs only if injected with massive, unrealistic bacterial doses and pigs, the best models, are impractical. The Davies lab pioneered the production of renal organoids and can make them from human iPS cells, and can now make ureters. Therefore, studying the bacterial response to antimicrobials within a stem cell-derived human organoids would be an excellent, accessible, ethical model. The El Karoui lab has shown that in E. coli the response to ciprofloxacin and trimethoprim, called the SOS response, is highly variable between bacteria with a sub-population of cells showing very high SOS induction, probably leading to increased tolerance and resistance to these antibiotics.The project therefore focuses on combining the expertise of both supervisors to develop a clinically relevant model of bacterial infection in kidney organoids and follow the bacterial and kidney cells response to infection and treatment with antibiotics. It will combine cell and molecular biology with cutting-edge quantitative microscopy to image the infection process over time. Quantitative image analysis will make use of newly developed segmentation algorithms based on deep learning. The experimental results will be used to inform mathematical models of bacterial cell growth under combinations of antibiotics exposure in the organoids.
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专著(0)
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国内基金
海外基金
中国棉铃虫核多角体病毒基因组库和分子进化
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批准号:30540076
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项目类别:专项基金项目
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资助金额:8.0万元
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批准年份:2005
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负责人:王汉中
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依托单位:
细菌脂蛋白(BLP)诱导LPS交叉耐受的分子机理研究
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批准号:30471791
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项目类别:面上项目
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资助金额:20.0万元
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批准年份:2004
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负责人:肖南
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依托单位: