Cell factory design with advanced metabolic modelling empowered by artificial intelligence

IF 6.8 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Metabolic engineering Pub Date : 2024-07-20 DOI:10.1016/j.ymben.2024.07.003

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引用次数: 0

Abstract

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.

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利用人工智能的先进代谢模型进行细胞工厂设计。

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遇。高性能细胞工厂是工业生物技术的支柱，最终决定着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就是如何以一致、高效的方式创建高性能细胞工厂。作为所谓的 "白盒模型"，许多代谢网络模型已被开发并用于计算菌株设计。此外，近年来人工智能驱动的菌株工程也取得了巨大进展。这两种方法各有利弊。因此，人工智能与代谢模型的深度整合对于构建具有更高滴度、产量和生产率的卓越细胞工厂至关重要。本综述总结了最新的先进代谢模型和人工智能在计算菌株设计中的详细应用。此外，还讨论了人工智能与代谢模型深度整合的方法。预计未来几年，人工智能驱动的先进机理代谢模型将为高效构建强大的工业底盘菌株铺平道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Metabolic engineering 工程技术-生物工程与应用微生物

CiteScore

15.60

自引率

6.00%

发文量

140

审稿时长

44 days

期刊介绍： Metabolic Engineering (MBE) is a journal that focuses on publishing original research papers on the directed modulation of metabolic pathways for metabolite overproduction or the enhancement of cellular properties. It welcomes papers that describe the engineering of native pathways and the synthesis of heterologous pathways to convert microorganisms into microbial cell factories. The journal covers experimental, computational, and modeling approaches for understanding metabolic pathways and manipulating them through genetic, media, or environmental means. Effective exploration of metabolic pathways necessitates the use of molecular biology and biochemistry methods, as well as engineering techniques for modeling and data analysis. MBE serves as a platform for interdisciplinary research in fields such as biochemistry, molecular biology, applied microbiology, cellular physiology, cellular nutrition in health and disease, and biochemical engineering. The journal publishes various types of papers, including original research papers and review papers. It is indexed and abstracted in databases such as Scopus, Embase, EMBiology, Current Contents - Life Sciences and Clinical Medicine, Science Citation Index, PubMed/Medline, CAS and Biotechnology Citation Index.