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Secondary Toxicity Mechanisms of Insecticides and Their Metabolism in Pollinators

Secondary Toxicity Mechanisms of Insecticides and Their Metabolism in Pollinators
杀虫剂的次生毒性机制及其在传粉媒介中的代谢
批准号:
2236030
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金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
翻译
杀虫剂是传粉者面临的主要压力之一,其数量在全球范围内呈下降趋势。很少有研究描述它们的次要影响,即不通过主要靶点相互作用介导的反应。酿酒酵母是Baker‘s酵母,由于其基因组缺乏主要的分子靶标,同时与其他真核生物共享基本的细胞过程,因此为表征次生杀虫效果提供了一个理想的模型。基因表达分析将揭示杀虫剂在酵母中对代表五类12种杀虫剂的反应。这些结果将与现有的大黄蜂B.terrestris的类似表达研究相结合,以确定同源的次级反应。全面了解杀虫剂的毒性机制对于评估其对传粉者的风险至关重要。该项目的第二部分将致力于绘制出在B.terrestris中负责杀虫剂代谢的酶的图谱。利用基于酿酒酵母的表达系统,将评估细胞色素P450酶(CYP)驱动的杀虫剂代谢,并确定单个CYP底物的分布。反过来,对新陈代谢很重要的细胞色素P450将成为系统发育比较研究的基础,以评估远缘传粉物种的杀虫剂新陈代谢能力。这是预测戒毒情况的第一步。
英文摘要
Insecticides are one of the main stressors faced by pollinators, whose numbers are in global decline. Few studies have been undertaken to profile their secondary effects, that is responses not mediated through primary target interactions. S.cerevisiae, Baker's yeast, offers an ideal model for characterising secondary insecticide effects as its genome lacks their main molecular targets, whilst at the same time sharing fundamental cellular processes with other eukaryotes. Gene expression analysis will be conducted to reveal insecticide mediated responses in yeast for twelve insecticides, representing five classes. These results will be combined with existing, analogous expression studies in the bumblebee, B.terrestris, to identify homologous secondary responses. Gaining a holistic understanding of insecticide toxicity mechanisms is crucial for assessing their risk to pollinators. The second part of this project will aim to map the enzymes responsible for insecticide metabolism in B.terrestris. Using S.cerevisiae based expression systems, cytochrome p450 enzyme (CYP) driven insecticide metabolism will be evaluated, with individual CYP substrate profiles determined. In turn, CYPs important to metabolism will become the basis for a phylogenetic comparison study, to assess the capability of insecticide metabolism in distantly related pollinator species. This presents the first step to predictive detoxification profiling.
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