Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE412 96, Gothenburg, Sweden.
Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Kemivägen 10, SE-412 96, Gothenburg, Sweden.
Nat Commun. 2022 May 27;13(1):2969. doi: 10.1038/s41467-022-30689-7.
Eukaryotic cells are used as cell factories to produce and secrete multitudes of recombinant pharmaceutical proteins, including several of the current top-selling drugs. Due to the essential role and complexity of the secretory pathway, improvement for recombinant protein production through metabolic engineering has traditionally been relatively ad-hoc; and a more systematic approach is required to generate novel design principles. Here, we present the proteome-constrained genome-scale protein secretory model of yeast Saccharomyces cerevisiae (pcSecYeast), which enables us to simulate and explain phenotypes caused by limited secretory capacity. We further apply the pcSecYeast model to predict overexpression targets for the production of several recombinant proteins. We experimentally validate many of the predicted targets for α-amylase production to demonstrate pcSecYeast application as a computational tool in guiding yeast engineering and improving recombinant protein production.
真核细胞被用作细胞工厂来生产和分泌大量的重组药物蛋白，包括一些目前最畅销的药物。由于分泌途径的重要作用和复杂性，通过代谢工程来提高重组蛋白的生产一直以来都是相对特定的；需要更系统的方法来生成新的设计原则。在这里，我们提出了酵母酿酒酵母（pcSecYeast）的蛋白质组约束基因组尺度蛋白分泌模型（pcSecYeast），这使我们能够模拟和解释由于分泌能力有限而导致的表型。我们进一步将 pcSecYeast 模型应用于预测几种重组蛋白生产的过表达靶标。我们通过实验验证了许多预测的用于生产α-淀粉酶的靶标，以证明 pcSecYeast 作为一种计算工具在指导酵母工程和提高重组蛋白生产方面的应用。
