Rodríguez-López Carlos E, Jiang Yindi, Kamileen Mohamed O, Lichman Benjamin R, Hong Benke, Vaillancourt Brieanne, Buell C Robin, O'Connor Sarah E
Department of Natural Product Biosynthesis, Max Planck Institute for Chemical Ecology, 07745 Jena, Germany.
Department of Biology, University of York, YO10 5DD York, UK.
Mol Biol Evol. 2022 Apr 10;39(4). doi: 10.1093/molbev/msac057.
Countless reports describe the isolation and structural characterization of natural products, yet this information remains disconnected and underutilized. Using a cheminformatics approach, we leverage the reported observations of iridoid glucosides with the known phylogeny of a large iridoid producing plant family (Lamiaceae) to generate a set of biosynthetic pathways that best explain the extant iridoid chemical diversity. We developed a pathway reconstruction algorithm that connects iridoid reports via reactions and prunes this solution space by considering phylogenetic relationships between genera. We formulate a model that emulates the evolution of iridoid glucosides to create a synthetic data set, used to select the parameters that would best reconstruct the pathways, and apply them to the iridoid data set to generate pathway hypotheses. These computationally generated pathways were then used as the basis by which to select and screen biosynthetic enzyme candidates. Our model was successfully applied to discover a cytochrome P450 enzyme from Callicarpa americana that catalyzes the oxidation of bartsioside to aucubin, predicted by our model despite neither molecule having been observed in the genus. We also demonstrate aucubin synthase activity in orthologues of Vitex agnus-castus, and the outgroup Paulownia tomentosa, further strengthening the hypothesis, enabled by our model, that the reaction was present in the ancestral biosynthetic pathway. This is the first systematic hypothesis on the epi-iridoid glucosides biosynthesis in 25 years and sets the stage for streamlined work on the iridoid pathway. This work highlights how curation and computational analysis of widely available structural data can facilitate hypothesis-based gene discovery.
无数报告描述了天然产物的分离和结构表征，但这些信息仍然是孤立的且未得到充分利用。我们采用化学信息学方法，利用已报道的环烯醚萜苷观察结果以及一个大型环烯醚萜生产植物科（唇形科）的已知系统发育关系，生成一组能最佳解释现存环烯醚萜化学多样性的生物合成途径。我们开发了一种途径重建算法，通过反应将环烯醚萜的报告连接起来，并通过考虑属间的系统发育关系来精简这个解决方案空间。我们构建了一个模拟环烯醚萜苷进化的模型，以创建一个合成数据集，用于选择能最佳重建途径的参数，并将其应用于环烯醚萜数据集以生成途径假说。然后，这些通过计算生成的途径被用作选择和筛选生物合成酶候选物的基础。我们的模型成功应用于从美洲紫珠中发现一种细胞色素P450酶，该酶催化巴齐苷氧化为桃叶珊瑚苷，尽管在该属中尚未观察到这两种分子，但我们的模型预测了这一反应。我们还在贞节树的直系同源物以及外类群毛泡桐中证明了桃叶珊瑚苷合酶活性，进一步强化了我们的模型所支持的假说，即该反应存在于祖先生物合成途径中。这是25年来关于表环烯醚萜苷生物合成的首个系统性假说，为环烯醚萜途径的简化研究奠定了基础。这项工作突出了对广泛可用的结构数据进行整理和计算分析如何能够促进基于假说的基因发现。
