Revealing the role of autotoxicity protection for defense metabolism innovations in Solanaceae using a multiomics approach

许多植物专化代谢产物(PSM)具有防御功能，取消特定的途径步骤可以导致有毒中间体的积累，这表明除了基于防御的功能选择外，自毒避免在PSM生物化学的进化中起着关键作用。然而，我们目前还不知道自身毒性保护机制在多大程度上以及如何与防御功能协同进化。这些具有挑战性的问题需要多物种和器官的方法，整合基因和PSM水平的信息(多组学图谱)，以使用功能和进化研究来检验自毒回避驱动的进化的三个关键预测：1)参与自毒预防的基因应该检测到对PSM途径进行正选择的强烈信号；2)这些基因的表达可能在与细胞生长和/或分化相关的特定细胞类型中得到丰富；以及3)应该在拥有特定PSM创新的密切相关物种中检测到类似的器官水平的选择特征，因为由内在细胞功能引起的选择可能没有生态选择那么动态。在这里，通过我们最近在烟草二萜糖苷(DTG)的生物合成和(自动)毒性机制以及其他小组在类固醇糖苷(SGA)生物合成方面的工作的突破，我们将实施最先进的计算代谢组学、转录组学、单细胞基因组学和遗传操作工具来应对这一挑战。我们的目标是(I)建立8个茄科植物的综合代谢组学-转录组图谱，以精确定位DTG和SGA途径中的生化创新；(Ii)追溯这些途径的分子进化，并表征具有强烈正选择特征的基因；以及(Iii)作为案例研究，结合单细胞基因组学和遗传操作，从功能上破译自毒避免对SGAs进化的贡献。这项工作的结果将使我们能够评估自毒预防是否是推动茄科植物化学多样化的关键选择压力。更广泛地说，EVOMET将解决我们对植物防御进化理解的范式转变，为下一代作物保护战略的设计提供关键见解，并在植物进化生物学中实施新的比较单细胞测序工具。

Many plant specialized metabolites (PSMs) function as defenses and abrogating particular pathway steps can lead to the accumulation of toxic intermediates, indicating that in addition to defense-based functional selection, autotoxicity avoidance plays a key role in the evolution of the PSM biochemistry. However, we currently do not know to which extent and how autotoxicity protection mechanisms evolve in concert with defensive functions. These challenging questions require a multi-species and -organ approach integrating gene -and PSM-level information (multiomics atlases) to test, using both functional and evolutionary studies, three key predictions of autotoxicity avoidance-driven evolution: that 1) strong signatures of positive selection for a PSM pathway should be detected for genes participating in autotoxicity prevention; 2) expression of those genes should likely be enriched in specific cell types associated with cell growth and/or differentiation; and that 3) similar organ-level signatures of selection should be detected among closely-related species harboring a given PSM innovation, since the selection imposed by intrinsic cellular functions is likely to be less dynamic than ecological selections. Here, by building on our recent breakthrough on the biosynthesis and (auto)toxicity mechanisms of diterpene glycosides (DTG) in tobacco as well as on other groups’ work on the biosynthesis of steroidal glycoalkaloids (SGA), two prominent Solaneaceae PSM defenses, we will implement a state-of-the-art integration of computational metabolomics, transcriptomics, single-cell genomics and genetic manipulation tools to address this challenge. We aim to (i) establish integrated metabolomics-transcriptomics atlases for eight solanaceous species to pinpoint on biochemical innovations in the DTG and SGA pathways; (ii) retrace the molecular evolution of these pathways and characterize genes with signatures of strong positive selection; and (iii), as a case-study, functionally decipher the contribution of autotoxicity avoidance for SGAs’ evolution using a combination of single-cell genomics and genetic manipulations. The outcomes of this work will allow us to evaluate whether autotoxicity prevention is a key selection pressure driving the chemodiversification in Solanaceae. More broadly, EVOMET will address a paradigm shift in our understanding of plant defense evolution, provide key insights for the design of next-generation crop protection strategies, and implement new comparative single-cell sequencing tools in plant evolutionary biology.