通过酿酒酵母厌氧联合生产 2,3-丁二醇和甘油的代谢工程评估酶约束基因组规模模型

IF 6.8 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Metabolic engineering Pub Date : 2024-02-01 DOI:10.1016/j.ymben.2024.01.007
Gustav Sjöberg , Alīna Reķēna , Matilda Fornstad , Petri-Jaan Lahtvee , Antonius J.A. van Maris
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引用次数: 0

摘要

酶约束基因组尺度模型(ecGEMs)可预测生长速率或碳源等各种条件下的表型。这项研究探讨了 ecGEM 是否能指导代谢工程工作,将酵母中的厌氧氧化还原中性 ATP 提供途径从酒精发酵转换为等摩尔 2,3 丁二醇和甘油的联合生产。ecGEM方案具有成熟的途径和较低的产品毒性,与观察到的表型非常吻合。由于这种分解代谢途径提供的 ATP 仅为酒精发酵的三分之一(2/3 对 2 ATP/每葡萄糖),ecGEM 预测生长速度将从参考菌株的 0.36 h-1 降至工程菌株的 0.175 h-1。然而,这种 3 倍的下降需要特定葡萄糖消耗率的增加。令人惊讶的是,在路径交换后,工程菌株立即以 0.15 h-1 的速度生长,葡萄糖消耗率为 29 mmol (g CDW)-1 h-1,确实高于参考菌株(23 mmol (g CDW)-1 h-1),也是已报道的 S. cerevisiae 最高消耗率之一。同时,2,3-丁二醇(15.8 毫摩尔(克 CDW)-1 小时-1)和甘油(19.6 毫摩尔(克 CDW)-1 小时-1)的生产率接近预测值。蛋白质组学证实,酶从核糖体(从 25.5% 到 18.5%)向糖酵解(从 28.7% 到 43.5%)的重新分配促进了消耗率的提高。随后,200 代的连续转移并没有改善工程菌株的生长,这表明 ecGEMs 可用于预测实验室进化的机会空间。本研究的观察结果说明了 ecGEMs 作为代谢工程和实验室进化工具的当前潜力和未来改进。
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Evaluation of enzyme-constrained genome-scale model through metabolic engineering of anaerobic co-production of 2,3-butanediol and glycerol by Saccharomyces cerevisiae

Enzyme-constrained genome-scale models (ecGEMs) have potential to predict phenotypes in a variety of conditions, such as growth rates or carbon sources. This study investigated if ecGEMs can guide metabolic engineering efforts to swap anaerobic redox-neutral ATP-providing pathways in yeast from alcoholic fermentation to equimolar co-production of 2,3-butanediol and glycerol. With proven pathways and low product toxicity, the ecGEM solution space aligned well with observed phenotypes. Since this catabolic pathway provides only one-third of the ATP of alcoholic fermentation (2/3 versus 2 ATP per glucose), the ecGEM predicted a growth decrease from 0.36 h−1 in the reference to 0.175 h−1 in the engineered strain. However, this <3-fold decrease would require the specific glucose consumption rate to increase. Surprisingly, after the pathway swap the engineered strain immediately grew at 0.15 h−1 with a glucose consumption rate of 29 mmol (g CDW)−1 h−1, which was indeed higher than reference (23 mmol (g CDW)−1 h−1) and one of the highest reported for S. cerevisiae. The accompanying 2,3-butanediol- (15.8 mmol (g CDW)−1 h−1) and glycerol (19.6 mmol (g CDW)−1 h−1) production rates were close to predicted values. Proteomics confirmed that this increased consumption rate was facilitated by enzyme reallocation from especially ribosomes (from 25.5 to 18.5 %) towards glycolysis (from 28.7 to 43.5 %). Subsequently, 200 generations of sequential transfer did not improve growth of the engineered strain, showing the use of ecGEMs in predicting opportunity space for laboratory evolution. The observations in this study illustrate both the current potential, as well as future improvements, of ecGEMs as a tool for both metabolic engineering and laboratory evolution.

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来源期刊
Metabolic engineering
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.
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