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 or >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 (r² = 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.

中文翻译：

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应用实验的统计设计来了解生长培养基成分对铜绿细菌H16生长的影响。

作为一种生物技术应用领域中的微生物底盘，Cupriavidus除草剂H16受到了广泛的关注。尽管该细菌是生物塑料的主要生产商，但其自养性和多种代谢能力使其成为使用可再生资源的有前途的微生物燃料和化学品微生物底盘。仍然有必要开发适当的实验资源，以允许对该微生物进行受控的生物工程和系统优化。在这项研究中，我们采用了实验的统计设计来了解特定介质成分对C. necator的影响。生长并建立了一个可以根据培养基成分预测细菌细胞密度的模型。这突出显示了对生长影响最大的培养基成分以及成分之间的相互作用：果糖，氨基酸，微量元素，CaCl ₂和Na ₂ HPO ₄显着促进了生长（t值<-1.65或> 1.65）；铜和组氨酸被发现相互作用，必须保持平衡才能稳定生长。我们的模型经过实验验证，发现相关性很好（r ²= 0.85）。在大型培养规模上进行的模型验证表明，在摇瓶中100 ml（ρ= 0.87）和在生物反应器中1升（ρ= 0.90），我们的模型预测的生长等级与实验确定的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且可量化的见解，并可用于模拟其他C. necator反应，这对于将其部署为微生物底物至关重要。该方法可以扩展到具有医学和工业生物技术重要性的其他非模型微生物。