Batch-to-batch optimization with model adaptation leveraging Gaussian processes: the case of optogenetically assisted microbial consortia

Sebastián Espinel-Ríos; Rudolph Kok; Steffen Klamt; José L. Avalos; Rolf Findeisen

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자료유형: 학술대회자료

저자정보: Sebastián Espinel-Ríos (Max Planck Institute for Dynamics of Complex Technical Systems) Rudolph Kok (Otto von Guericke University Magdeburg) Steffen Klamt (Max Planck Institute for Dynamics of Complex Technical Systems) José L. Avalos (Princeton University) Rolf Findeisen (Control and Cyber-Physical Systems Laboratory)

저널정보: 제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2023

발행연도: 2023.10

수록면: 1,292 - 1,297 (6page)

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Microbial consortia are promising biotechnological production systems with the potential to divide complex metabolic pathways into smaller submodules, as well as make products and consume substrates that monocultures cannot. Maintaining optimal cell population levels and preventing monoculture formation challenge bioproduction by microbial consortia. Optogenetics allows for regulating the expression of key growth-regulatory genes through light to modulate cell population levels. Model-based dynamic optimization can determine optimal light trajectories and inoculum sizes that maximize product synthesis while satisfying system constraints, e.g., safety, economic, or technical aspects. Furthermore, closed-loop dynamic optimization can address system uncertainty to a certain extent; however, its implementation is challenging due to limited online sensors. Alternatively, here we propose to perform open-loop optimization with batch-to-batch model adaptation based on Gaussian processes for maximizing bioproduction by optogenetically assisted consortia. The proposed approach enables knowledge transfer from existing to new models, improving predictability and optimization performance in each batch while avoiding costly and time-consuming modeling experiments. Compared to closed-loop optimization, this strategy is easier to implement as it does not rely on online monitoring, contributing to the state of the art in optimizing bioproduction by microbial consortia. We outline the applicability of the approach using simulation experiments of an optogenetically assisted consortium for the biosynthesis of the flavonoid naringenin, considering both parameter and model structure uncertainty.

#Batch-to-batch optimization #optimal control #model adaptation #Gaussian processes #optogenetics #microbial consortia

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