Applying statistical design of experiments (DOE) to understanding the effect of growth media components on Cupriavidus necator H16 growth.

Cupriavidus necator H16 is gaining significant attention as a microbial chassis for range of biotechnological applications. Whilst 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. Here 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 media components. This highlighted media components, and interaction between components, having the most effect on growth: fructose, amino acids, trace elements, CaCl2 and Na2HPO4 contributed significantly to growth (t < -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 L in bioreactor (ρ = 0.90). Our approach provides valuable and quantifiable insights on the impact of media 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 non-model 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 optimizing 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 few amino acids to growth medium shortened lag phase of growth. The interactions highlighted by our growth model shows 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.