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Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth

机译:应用实验统计设计,了解生长培养基组分对Cupriavidus Necator H16生长的影响

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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, CaCl_(2), and Na_(2)HPO_(4) 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 (ρ = 0.87) and 1 liter in a bioreactor (ρ = 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.
机译:Cupriavidus Necator H16是作为生物技术应用范围的微生物底盘的显着关注。虽然细菌是生物塑料的主要生产者,但它的型术和通用代谢能力使得细菌成为使用可再生资源的生物燃料和化学品的有希望的微生物底盘。仍然有必要制定适当的实验资源,以允许受控生物工程和系统优化这种微生物。在这项研究中,我们采用了实验的统计设计,以了解定义培养基组分对C. Necator生长的影响,并建造了一种可以预测基于培养基组分的细菌细胞密度的模型。这种突出的培养基组分和组分之间的相互作用,对生长产生最大:果糖,氨基酸,微量元素,CaCl_(2)和Na_(2)HPO_(4)显着促进生长(T值为1.65);发现铜和组氨酸相互作用,必须均衡稳健生长。我们的模型是通过实验验证的,发现良好(R〜(2)= 0.85)。大型培养尺度的模型验证显示了我们的模型预测的生长等级与实验确定在100?ml的摇瓶(ρ= 0.87)和生物反应器中的1升(ρ= 0.90)中的相应的相关性。我们的方法提供了有价值的和可量化的关于中等成分对细胞生长的影响,并且可以应用于模型,这是对其部署至微生物底盘至关重要的型号。这种方法可以扩展到其他非典型微生物的医学和工业生物技术重要性。分为化学定义的培养基(CDM),用于培养C. Necator在组分和组合物中变化。这种缺乏共识使得难以优化细菌的新方法。本研究采用了实验统计设计(DOE)以了解定义介质的基本组分如何影响C. Necator Grower。我们的生长模型预测,C.碳酸酯可以与以低浓度保持的组分培养至高细胞密度,认为CDM用于大规模培养工业目的的细菌将是经济上竞争的。尽管存在的细菌的现有CDM没有氨基酸,但向生长培养基中加入几个氨基酸缩短滞后阶段生长。我们的增长模型突出显示的交互展示了因素在一个过程中可以在积极或负面影响过程输出期间彼此相互作用。这种方法是有效的,依靠很少结构的实验运行,以获得有关生物过程的最大信息,生长。

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