Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Cambrium GmbH, Berlin, Germany.
Nat Commun. 2021 Aug 9;12(1):4790. doi: 10.1038/s41467-021-25158-6.
Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.
真核生物在工业生物技术中扮演着重要的角色，从燃料和大宗商品化学品的生产到治疗性蛋白。为了优化这些工业系统，可以使用数学方法将多个生物网络的描述整合到一个用于细胞分析和工程的单一模型中。最准确的生物系统模型之一包括表达和热力学通量（ETFL），它可以有效地将 RNA 和蛋白质合成与传统的基因组规模代谢模型集成在一起。然而，ETFL 迄今为止仅适用于大肠杆菌。为了使这个模型适用于酿酒酵母，我们开发了 yETFL，在这个模型中，我们在原始公式中增加了更多的考虑因素，包括生物量组成、细胞表达系统的隔室化以及生物过程的能量成本。我们证明了 yETFL 预测最大生长速率、必需基因和代谢溢出表型的能力。我们设想所提出的公式可以扩展到广泛的真核生物，以造福学术和工业研究。
