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Design of Experiments Methodology to Build a Multifactorial Statistical Model Describing the Metabolic Interactions of Alcohol Dehydrogenase Isozymes in the Ethanol Biosynthetic Pathway of the Yeast Saccharomyces cerevisiae
ACS Synthetic Biology ( IF 3.7 ) Pub Date : 2018-07-06 00:00:00 , DOI: 10.1021/acssynbio.8b00112 Steven R. Brown 1 , Marta Staff 1 , Rob Lee 2 , John Love 1 , David A. Parker 2 , Stephen J. Aves 1 , Thomas P. Howard 3
ACS Synthetic Biology ( IF 3.7 ) Pub Date : 2018-07-06 00:00:00 , DOI: 10.1021/acssynbio.8b00112 Steven R. Brown 1 , Marta Staff 1 , Rob Lee 2 , John Love 1 , David A. Parker 2 , Stephen J. Aves 1 , Thomas P. Howard 3
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Multifactorial approaches can quickly and efficiently model complex, interacting natural or engineered biological systems in a way that traditional one-factor-at-a-time experimentation can fail to do. We applied a Design of Experiments (DOE) approach to model ethanol biosynthesis in yeast, which is well-understood and genetically tractable, yet complex. Six alcohol dehydrogenase (ADH) isozymes catalyze ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localization, and enzyme kinetics. We generated a combinatorial library of all ADH gene deletions and measured the impact of gene deletion(s) and environmental context on ethanol production of a subset of this library. The data were used to build a statistical model that described known behaviors of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behavior without explicit a priori knowledge. The method is therefore highly suited to understanding and optimizing metabolic pathways in less well-understood systems.
中文翻译：
实验方法的设计，以建立描述酵母酿酒酵母乙醇生物合成途径中乙醇脱氢酶同工酶代谢相互作用的多因素统计模型。
多因素方法可以快速而有效地对复杂的，相互作用的自然或工程生物系统进行建模，而传统的一次性一次实验无法做到。我们应用了实验设计（DOE）方法来模拟酵母中乙醇的生物合成，这是众所周知的且在遗传上易处理但又复杂的方法。六种醇脱氢酶（ADH）同工酶催化乙醇合成，它们的转录和翻译后调节，亚细胞定位和酶动力学不同。我们生成了所有ADH基因缺失的组合文库，并测量了基因缺失和环境背景对该文库一部分乙醇生产的影响。该数据用于建立一个统计模型，该模型描述了ADH同工酶的已知行为并确定了新的相互作用。先验知识。因此，该方法非常适合在不太了解的系统中理解和优化代谢途径。
更新日期：2018-07-06
中文翻译：
实验方法的设计，以建立描述酵母酿酒酵母乙醇生物合成途径中乙醇脱氢酶同工酶代谢相互作用的多因素统计模型。
多因素方法可以快速而有效地对复杂的，相互作用的自然或工程生物系统进行建模，而传统的一次性一次实验无法做到。我们应用了实验设计（DOE）方法来模拟酵母中乙醇的生物合成，这是众所周知的且在遗传上易处理但又复杂的方法。六种醇脱氢酶（ADH）同工酶催化乙醇合成，它们的转录和翻译后调节，亚细胞定位和酶动力学不同。我们生成了所有ADH基因缺失的组合文库，并测量了基因缺失和环境背景对该文库一部分乙醇生产的影响。该数据用于建立一个统计模型，该模型描述了ADH同工酶的已知行为并确定了新的相互作用。先验知识。因此，该方法非常适合在不太了解的系统中理解和优化代谢途径。
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