Advances in synthetic biology and artificial intelligence (AI) have provided new opportunities for modern biotechnology. High-performance cell factories, the backbone of industrial biotechnology, are ultimately responsible for determining whether a bio-based product succeeds or fails in the fierce competition with petroleum-based products. To date, one of the greatest challenges in synthetic biology is the creation of high-performance cell factories in a consistent and efficient manner. As so-called white-box models, numerous metabolic network models have been developed and used in computational strain design. Moreover, great progress has been made in AI-powered strain engineering in recent years. Both approaches have advantages and disadvantages. Therefore, the deep integration of AI with metabolic models is crucial for the construction of superior cell factories with higher titres, yields and production rates. The detailed applications of the latest advanced metabolic models and AI in computational strain design are summarized in this review. Additionally, approaches for the deep integration of AI and metabolic models are discussed. It is anticipated that advanced mechanistic metabolic models powered by AI will pave the way for the efficient construction of powerful industrial chassis strains in the coming years.

中文翻译：

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使用人工智能支持的高级代谢建模进行细胞工厂设计


合成生物学和人工智能 （AI） 的进步为现代生物技术提供了新的机会。高性能细胞工厂是工业生物技术的支柱，最终负责决定生物基产品在与石油基产品的激烈竞争中是成功还是失败。迄今为止，合成生物学面临的最大挑战之一是以一致和高效的方式创建高性能细胞工厂。作为所谓的白盒模型，已经开发了许多代谢网络模型并将其用于计算应变设计。此外，近年来，人工智能驱动的应变工程取得了长足的进步。这两种方法都有优点和缺点。因此，AI 与代谢模型的深度集成对于构建具有更高滴度、产量和生产率的优质细胞工厂至关重要。本文总结了最新的高级代谢模型和 AI 在计算菌株设计中的详细应用。此外，还讨论了 AI 和代谢模型深度集成的方法。预计由 AI 提供支持的先进机理代谢模型将为未来几年高效构建强大的工业底盘菌株铺平道路。