Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth
Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth
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DOI：
10.1128/aem.00705-20
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发表时间：
2020-09-01
影响因子：
4.4
通讯作者：
Howard, Thomas P.
中科院分区：
文献类型：
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作者：
Azubuike, Christopher C.;Edwards, Martin G.;Howard, Thomas P.
Cupriavidus necator H16作为一种生物技术应用的微生物基础，正受到广泛的关注。虽然这种细菌是生物塑料的主要生产者，但其自养和多种代谢能力使这种细菌成为利用可再生资源生产生物燃料和化学品的有前途的微生物底盘。有必要开发适当的实验资源，以便对这种微生物进行控制生物工程和系统优化。在本研究中，我们采用实验统计设计的方法来了解所定义的培养基成分对C. necator生长的影响，并建立了一个基于培养基成分预测细菌细胞密度的模型。这突出了对生长影响最大的培养基成分和成分之间的相互作用：果糖、氨基酸、微量元素、CaCl2和Na2HPO4对生长有显著影响（t值为1.65）；发现铜和组氨酸相互作用，必须保持平衡才能强劲生长。我们的模型经过实验验证，发现相关性很好（r(2) = 0.85）。在大型培养规模上的模型验证表明，我们的模型预测的生长等级与实验确定的摇瓶中100毫升（p = 0.87）和生物反应器中1升（p = 0.90）的生长等级之间存在相关性。我们的方法为培养基成分对细胞生长的影响提供了有价值的和可量化的见解，并且可以应用于模拟其他C. necator反应，这些反应对于其作为微生物底盘的部署至关重要。这种方法可以扩展到医学和工业生物技术重要性的其他非模式微生物。重要性：用于培养乳酸菌的化学定义培养基（CDM）的成分和组成各不相同。这种共识的缺乏使得优化细菌的新工艺变得困难。本研究采用实验统计设计（DOE）来了解所定义培养基的基本成分对C. necator生长的影响。我们的生长模型预测，C. necator可以用低浓度的成分培养到高细胞密度，并认为用于工业目的的大规模培养细菌的CDM在经济上具有竞争力。虽然现有细菌的CDM不含氨基酸，但在生长培养基中添加少量氨基酸可缩短生长滞后期。我们的增长模型强调的相互作用表明，在一个过程中，因素如何相互作用，对过程产出产生积极或消极的影响。这种方法是有效的，依靠少量结构良好的实验运行来获得关于生物过程和生长的最大信息。
Cupriavidus necator H16 is gaining significant attention as a microbial chassis for range of biotechnological applications. While the bacterium is a major producer of bioplastics, its lithoautotrophic and versatile metabolic capabilities make the bacterium a promising microbial chassis for biofuels and chemicals using renewable resources. It remains necessary to develop appropriate experimental resources to permit controlled bioengineering and system optimization of this microbe. In this study, we employed statistical design of experiments to gain understanding of the impact of components of defined media on C. necator growth and built a model that can predict the bacterium's cell density based on medium components. This highlighted medium components, and interaction between components, having the most effect on growth: fructose, amino acids, trace elements, CaCl2, and Na2HPO4 contributed significantly to growth (t values of 1.65); copper and histidine were found to interact and must be balanced for robust growth. Our model was experimentally validated and found to correlate well (r(2) = 0.85). Model validation at large culture scales showed correlations between our model-predicted growth ranks and experimentally determined ranks at 100 ml in shake flasks (p = 0.87) and 1 liter in a bioreactor (p = 0.90). Our approach provides valuable and quantifiable insights on the impact of medium components on cell growth and can be applied to model other C. necator responses that are crucial for its deployment as a microbial chassis. This approach can be extended to other nonmodel microbes of medical and industrial biotechnological importance.IMPORTANCE Chemically defined media (CDM) for cultivation of C. necator vary in components and compositions. This lack of consensus makes it difficult to optimize new processes for the bacterium. This study employed statistical design of experiments (DOE) to understand how basic components of defined media affect C. necator growth. Our growth model predicts that C. necator can be cultivated to high cell density with components held at low concentrations, arguing that CDM for large-scale cultivation of the bacterium for industrial purposes will be economically competitive. Although existing CDM for the bacterium are without amino acids, addition of a few amino acids to growth medium shortened lag phase of growth. The interactions highlighted by our growth model show how factors can interact with each other during a process to positively or negatively affect process output. This approach is efficient, relying on few well-structured experimental runs to gain maximum information on a biological process, growth.