Understanding the molecular determinants of bee sensitivity to pesticides

蜜蜂是世界上环境和经济上最重要的昆虫群体之一，为各种各样的开花植物授粉，在各种粮食作物和商品作物的生产中发挥着关键作用。然而，在进行这种生态系统服务时，蜜蜂可能会接触到各种潜在的有害毒素。这些化合物既包括天然化合物，如植物产生的防御性化学物质，也包括合成化合物，如杀虫剂。蜜蜂通常被认为对这种毒素高度敏感，然而，它们进化出了复杂的新陈代谢系统来解毒环境中遇到的许多天然毒素。我们最近对四种受管理的蜜蜂物种的研究表明，这些生物转化途径也可以保护蜜蜂免受某些合成杀虫剂的伤害。具体地说，我们证明了属于细胞色素P450超家族的少量蜜蜂酶可以有效地解毒某些杀虫剂。然而，并不是所有的蜜蜂物种都有这样的P450酶，我们已经证明，一种缺乏P450酶的切叶蜜蜂对某些杀虫剂的敏感度比其他有这种酶的受控蜜蜂物种高数千倍。这一发现对杀虫剂的安全使用具有重要意义，因此现在迫切需要了解哪些种类的蜜蜂具有保护某些杀虫剂的P450酶，哪些没有。该项目将利用蜜蜂基因组和转录组序列的急剧增加来解决这一知识差距，以了解这类昆虫中关键的细胞色素P450酶家族的进化和功能。在该项目的第一个目标中，我们将使用比较基因组学方法(比较不同蜜蜂物种中P450的互补和关系)来预测哪些蜜蜂物种具有预先适应某些杀虫剂的P450。这些预测将通过在实验室中对候选蜜蜂P450进行功能性表达并检查它们对杀虫剂的解毒能力来验证。我们对一个受管理的独居蜜蜂物种的初步工作发现，编码某些杀虫剂代谢的P450的基因存在显著的遗传变异，然而，这对蜜蜂对杀虫剂敏感性的影响尚不清楚。因此，该项目的第二个目标将在一个模式的独居和群居蜜蜂物种中识别杀虫剂代谢P450的遗传变异。这种基因变异对编码的P450对杀虫剂解毒能力的影响将使用我们的功能流水线来确定。目标1和目标2中进行的工作将提供有关不同蜜蜂P450酶在代谢杀虫剂方面的效率的广泛数据集。在第三个目标中，这将被用来解释为什么某些P450可以代谢杀虫剂，而不是其他的。我们将确定蜜蜂P450酶中的氨基酸残基，这些氨基酸残基对确定杀虫剂新陈代谢及其与之相互作用的关键杀虫剂化学结构基团至关重要。该项目产生的数据将从根本上促进我们对蜜蜂体内P450酶的进化的了解，并将在保护蜜蜂免受潜在有害农药暴露方面产生重大的应用影响。该项目的一个关键成果将是开发一个强大的框架，可以用来预测蜜蜂物种对现有和未来杀虫剂的敏感性。这是有价值的，因为它可以用来识别对蜜蜂构成高风险的农药使用，并将直接为开发更准确的农药风险评估框架提供信息。最后，该项目产生的知识和工具将大大加快下一代蜜蜂安全杀虫剂的开发。

Bees are among the world's most environmentally and economically important group of insects, pollinating a remarkable diversity of flowering plants and playing a key role in the production of a wide range of food and commodity crops. However, while carrying out this ecosystem service bees can be exposed to a variety of potentially harmful toxins. These include both natural compounds, such as the defensive chemicals produced by plants, and synthetic compounds such as pesticides. Bees are often considered to be highly sensitive to such toxins, however, they have evolved sophisticated metabolic systems to detoxify many of the natural toxins encountered in their environment. Our recent work on four managed bee species has shown that these biotransformation pathways can also protect bees against certain synthetic insecticides. Specifically, we showed that a small number of bee enzymes belonging to the cytochrome P450 superfamily can efficiently detoxify certain insecticides. However, not all bee species have such P450 enzymes, and we have shown that one species of leafcutter bees that lacks them is thousands of times more sensitive to certain insecticides than other managed bee species that have them. This finding has significant implications for the safe use of insecticides, and thus it is now imperative to understand which species of bees have P450 enzymes that provide protection against certain insecticides and which do not.This project will address this knowledge gap by harnessing the dramatic increase in genome and transcriptome sequences available for bees to understand the evolution and function of key cytochrome P450 enzyme families in this group of insects. In the first objective of the project we will use a comparative genomic approach (comparing the complement and relationship of P450s in different bee species) to predict which bee species have P450s that are preadapted to detoxify certain insecticides. These predictions will be tested by functionally expressing candidate bee P450s in the laboratory and examining their capacity to detoxify insecticides. Our preliminary work on a managed solitary bee species has identified significant genetic variation in the genes encoding the P450s that metabolise certain insecticides, however, the consequences of this on bee sensitivity to insecticides is unclear. Thus, the second objective of the project will identify genetic variation in insecticide metabolising P450s in a model solitary and social bee species. The consequences of this genetic variation on the ability of the encoded P450s to detoxify insecticides will be established using our functional pipeline. The work conducted in Objective 1 and 2 will provide an extensive dataset on the efficiency of different bee P450 enzymes in metabolising insecticides. In the third objective this will be leveraged to understand why certain P450s can metabolise insecticides but not others. We will identify amino acid residues in bee P450 enzymes that are critical in determining insecticide metabolism and the key structural groups of insecticide chemistry they interact with. The data generated in this project will fundamentally advance our understanding of the evolution of P450 enzymes in bees, and will have significant applied impact in relation to safeguarding bees from potentially harmful pesticide exposure. A key outcome of the project will be the development of a robust framework that can be used to predict the sensitivity of bee species to existing and future insecticides. This is of value as it can be used to identify pesticide use that poses high risks to bees, and will directly inform the development of more accurate pesticide risk assessment frameworks. Finally, the knowledge and tools generated in the project will greatly accelerate the development of next-generation bee-safe insecticides.