How Mixing and Light Heterogeneity Impact the Overall Growth Rate in Photobioreactors

Gernigon, Vincent; Chekroun, Mohammed Arezki; Cockx, Arnaud; Guiraud, Pascal; Morchain, Jérôme

doi:10.1002/ceat.201900102

Cited by 9 publications

(3 citation statements)

References 36 publications

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“…The growth of microalgae can be better predicted by tracking the light changes experienced by each cell, which can also be achieved using the ELM [ 142 ]. Gernigon et al used the ELM to simulate the light distribution in two photobioreactors with different structures to analyze the influence of light on microalgae culture [ 143 ]. The results show that different light distributions can lead to different growth rates in microalgae, even when using the same light intensity; however, the ELM is computationally expensive and difficult to be applied on an industrial scale because it requires calculating change in each particle.…”

Section: Coupling Biological Models With Computational Fluid Dynamics...mentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

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Section: Coupling Biological Models With Computational Fluid Dynamics...mentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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Section: Scale-up Instrumentsmentioning

confidence: 99%

“…Finally, it is worth noting that modeling light distribution given bioreactor design [62], together with the optogenetic system, metabolic pathways and the bioprocess, will be key to optimizing bioproduction [63,64]. [57] used as mini-bioreactors allows larger scale (30 mL) cultures and dynamic real-time control, as well as culture and illumination conditions screening thanks to its 16-unit array.…”

Section: Industrial Settings and Photobioreactorsmentioning

confidence: 99%

The Promise of Optogenetics for Bioproduction: Dynamic Control Strategies and Scale-Up Instruments

et al. 2020

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Progress in metabolic engineering and synthetic and systems biology has made bioproduction an increasingly attractive and competitive strategy for synthesizing biomolecules, recombinant proteins and biofuels from renewable feedstocks. Yet, due to poor productivity, it remains difficult to make a bioproduction process economically viable at large scale. Achieving dynamic control of cellular processes could lead to even better yields by balancing the two characteristic phases of bioproduction, namely, growth versus production, which lie at the heart of a trade-off that substantially impacts productivity. The versatility and controllability offered by light will be a key element in attaining the level of control desired. The popularity of light-mediated control is increasing, with an expanding repertoire of optogenetic systems for novel applications, and many optogenetic devices have been designed to test optogenetic strains at various culture scales for bioproduction objectives. In this review, we aim to highlight the most important advances in this direction. We discuss how optogenetics is currently applied to control metabolism in the context of bioproduction, describe the optogenetic instruments and devices used at the laboratory scale for strain development, and explore how current industrial-scale bioproduction processes could be adapted for optogenetics or could benefit from existing photobioreactor designs. We then draw attention to the steps that must be undertaken to further optimize the control of biological systems in order to take full advantage of the potential offered by microbial factories.

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