基于多组学与代谢建模的雷帕霉素生物合成代谢调控机制解析

Rapamycin is a 31-membered polyketide macrolide compound, with various biological activities, such as immunosuppressant, anti-cancer and anti-aging. As a typical secondary metabolite, its biosynthesis is not only affected by the primary and secondary metabolic pathways, but also restricted by the complex intracellular metabolic regulatory systems. Based on the idea of “Omics analysis - Model prediction - Genetic modification”, this work intends to activate the intracellular metabolic regulation system of rapamycin biosynthesis by screening different types of chemical elicitors. Combining with metabolomics and transcriptomics technologies, the intracellular metabolites and genes expression profiles will be detected and analyzed dynamically in the different stage of rapamycin synthesis. Meanwhile, a genome-scale dynamic metabolic network model integrated with metabolomics and transcriptomics datasets would be constructed. The dynamic changes of intracellular metabolism would be simulated in the process of rapamycin synthesis. And the key limited steps/nodes, target genes would be also predicted by the dynamic model, which would be further manipulated and verified by genetic modification. Finally, the intracellular metabolic regulatory mechanism of rapamycin synthesis would be illustrated systematically. And the rational engineering modification strategy of rapamycin-produced strain would be constructed by the above analysis.

雷帕霉素是由吸水链霉菌发酵产生的一种31元大环内酯类化合物，具有免疫抑制、抗癌和抗衰老等多种生物学活性。作为一种典型的次级代谢产物，其生物合成不仅受到初级/次级代谢合成途径的影响，还受到复杂的胞内代谢调控体系的制约。本研究基于“组学分析-模型预测-分子改造”的思路，拟通过筛选不同类型的化学激发剂，激活雷帕霉素生物合成胞内代谢调控体系，并针对雷帕霉素的不同合成阶段，通过联合代谢组学与转录组学技术，对雷帕霉素合成过程中的胞内代谢物与基因表达谱进行动态检测与分析，构建整合代谢组-转录组数据的基因组尺度动态代谢网络模型，模拟雷帕霉素合成过程中胞内代谢的动态变化，预测影响雷帕霉素合成的关键限速步骤/节点及靶基因，通过对多组学分析与动态模型预测识别的关键限速节点和靶基因进行分子改造验证，阐明雷帕霉素生物合成过程中的胞内代谢调控机制，并建立雷帕霉素生产菌株的理性工程改造策略。

雷帕霉素是由吸水链霉菌发酵产生的一种31元大环内酯类抗生素，因其具有低毒高效等特点而广泛应用于器官移植等临床疾病的治疗之中，展现出了广阔的临床应用前景和经济价值。为了提升雷帕霉素发酵产量，本项目采用“先激活-再解析”的策略，并基于“组学分析-模型预测-分子改造”的思路开展了相关研究，取得的主要结论如下：（1）成功筛选获得能显著提升雷帕霉素产量的3种不同类型的化学激发剂（丁酸钠、氯化镧和二甲基亚砜），并优化获得其最佳添加策略，在其最优添加处理条件下雷帕霉素产量可提升1.35倍以上；（2）联合代谢组学、转录组学和化学计量学分析技术对上述三种化学激发剂处理后雷帕霉素产量提升的潜在作用机制进行了解析。其结果表明，增强菌体细胞膜通透性和强化关键前体派克酸的合成的是二甲基亚砜添加提升雷帕霉素产量的关键；在氯化镧处理后可激活雷帕霉素合成前体（(4R,5R)-4,5-二羟基环己-1-烯羧酸和NADPH）形成相关代谢途径的代谢通量；外源添加丁酸钠后可有效提升雷帕霉素合成前体甲基丙二酰辅酶A和NADPH的胞内水平；（3）采用基因组尺度代谢网络模型对三种化学激发剂处理后识别的潜在关键代谢途径进行了模拟预测，成功识别出多个潜在影响雷帕霉素合成的关键限速靶点，进一步对模拟预测识别排序靠前的4点靶基因进行了基因工程改造。结果发现，所有单基因/多基因联合改造工程菌株的雷帕霉素发酵产量均显著提升，且有2株工程菌株（HT-aroA/tktB和HT-△gdhA/aroA）的雷帕霉素产量较出发菌株提升1.5倍以上。本项目的实施可为进一步构建雷帕霉素高效合成细胞工厂提供理论依据和技术策略。