Sustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane) and has been produced in several engineered microorganisms. Recently, has gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile host for isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the “IPP-bypass” pathway in to maximize isoprenol production. Altogether, the highest isoprenol production titer from was achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering on for an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.

中文翻译：

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恶臭假单胞菌可持续航空燃料前体异戊二烯醇生产的基因组规模和途径工程

可持续航空燃料（SAF）将对航空业的全球变暖产生重大影响，重要的 SAF 目标正在出现。异戊二烯醇是一种有前景的 SAF 化合物 DMCO（1,4-二甲基环辛烷）的前体，已在多种工程微生物中生产。最近，作为异戊二烯醇生物生产的未来宿主，它引起了人们的兴趣，因为它可以利用廉价植物生物质中的碳源。在这里，我们设计了用于异戊二烯醇生产的代谢多功能宿主。我们采用两种计算建模方法（双层优化和约束最小切割集）来预测基因敲除目标并优化“IPP 旁路”途径以最大化异戊二烯醇产量。总而言之，在分批补料条件下，异戊二烯醇的最高产量达到 3.5 g/L。这种先进生物燃料生产的计算模型和应变工程的结合对于实现可使用可再生碳流的生物生产过程具有至关重要的意义。