Two-way Euler-Lagrange simulations are performed to characterize the hydrodynamics in the single-use bioreactor Mobius® CellReady 3 L. The hydrodynamics in stirred tank bioreactors are frequently modeled with the Euler–Euler approach, which cannot capture the trajectories of single bubbles. The present study employs the two-way coupled Euler–Lagrange approach, which accounts for the individual bubble trajectories through Langrangian equations and considers their impact on the Eulerian liquid phase equations. Hydrodynamic process characteristics that are relevant for cell cultivation including the oxygen mass transfer coefficient, the mixing time, and the hydrodynamic stress are evaluated for different working volumes, sparger types, impeller speeds, and sparging rates. A microporous sparger and an open pipe sparger are considered where bubbles of different sizes are generated, which has a pronounced impact on the bubble dispersion and the volumetric oxygen mass transfer coefficient. It is found that only the microporous sparger provides sufficiently high oxygen transfer to support typical suspended mammalian cell lines. The simulated mixing time and the volumetric oxygen mass transfer coefficient are successfully validated with experimental results. Due to the small reactor size, mixing times are below 25 s across all tested conditions. For the highest sparging rate of 100 mL min−1, the mixing time is found to be two seconds shorter than for a sparging rate of 50 mL min−1, which again, is 0.1 s longer than for a sparging rate of 10 mL min−1 at the same impeller speed of 100 rpm and the working volume of 1.7 L. The hydrodynamic stress in this bioreactor is found to be below critical levels for all investigated impeller speeds of up to 150 rpm, where the maximum levels are found in the region where the bubbles pass behind the impeller blades.
Computational methods have enabled the discovery of non-intuitive strategies to enhance the production of a variety of target molecules. In the case of succinate production, reviews covering the topic have not yet analyzed the impact and future potential that such methods may have. In this work, we review the application of computational methods to the production of succinic acid. We found that while a total of 26 theoretical studies were published between 2002 and 2016, only 10 studies reported the successful experimental implementation of any kind of theoretical knowledge. None of the experimental studies reported an exact application of the computational predictions. However, the combination of computational analysis with complementary strategies, such as directed evolution and comparative genome analysis, serves as a proof of concept and demonstrates that successful metabolic engineering can be guided by rational computational methods.
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