A model‐driven approach towards rational microbial bioprocess optimization

Abstract

Due to sustainability concerns, bio-based production capitalizing on microbes as cell factories is in demand to synthesize valuable products. Nevertheless, the nonhomogenous variations of the extracellular environment in bioprocesses often challenge the biomass growth and the bioproduction yield. To enable a more rational bioprocess optimization, we have established a model-driven approach that systematically integrates experiments with modeling, executed from flask to bioreactor scale, and using ferulic acid to vanillin bioconversion as a case study. The impacts of mass transfer and aeration on the biomass growth and bioproduction performances were examined using minimal small-scale experiments. An integrated model coupling the cell factory kinetics with the three-dimensional computational hydrodynamics of bioreactor was developed to better capture the spatiotemporal distributions of bioproduction. Full-factorial predictions were then performed to identify the desired operating conditions. A bioconversion yield of 94% was achieved, which is one of the highest for recombinant Escherichia coli using ferulic acid as the precursor.

Optimization and Scale-Up of Fermentation Processes Driven by Models

“…Du et al used the EEM to establish a CFD model coupled with an unstructured kinetic model to explore the effect of bioreactor size and operating conditions on the fermentation process, and they were able to scale-up DHA fermentation from a 5 L bioreactor to a 35 m 3 bioreactor [ 49 ]. Jing et al also built a coupling model to fine-tune the biological production process to a reasonable extent, and they were able to scale-up the production of ferulic acid into vanillin, from shaker to bioreactor, with a conversion rate up to 94% [ 147 ].…”

Future trends in synthetic biology in Asia

“…Moreover, the complexity of biological systems and the vast differences of industrial vs small‐scale bioreactor conditions often make the outcome of scaled production unpredictable 101 . Further development of predictive models and better integration of modelling with experiments are important in making the scale up process more rational and predictable 102,103 . There are also companies such as Amyris that specialize in optimizing the scale‐up production of commodity molecules 104…”

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“…To further emphasize merging of KMs, the simplified vanillin producing cell factory KM by Yeoh et al 34 was implemented in totality (Supplementary material S28) and simulated. The original model was split into two constituent models of cell growth model (Supplementary material S29) and vanillin producing model (Supplementary material S30).…”

“…In addition, this also demonstrate an important usage of AdvanceSyn Toolkit where cloned gene cassette(s), vanillin producing pathway in this case, can be merged with cell host model. Moreover, Yeoh et al 34 use Hill equation, 35 which is different to that in Use Case #1; this further emphasizes that AdvanceSyn Toolkit does not assume any specific type of rate expression.…”