Optimal control and dynamic modulation of the ATPase gene expression for enforced ATP wasting in batch fermentations

Espinel-Ríos, Sebastián; Morabito, Bruno; Pohlodek, Johannes; Bettenbrock, Katja; Klamt, Steffen; Findeisen, Rolf

doi:10.1016/j.ifacol.2022.07.440

Cited by 6 publications

(5 citation statements)

References 22 publications

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“…As foreseeable, the higher the induction capacity strength of the CcaS/CcaR system, the higher the net ATPase enzyme expression, and therefore the higher the net increase in product yield. In previous works dealing with dynamic ATP turnover in one-stage batch fermentations, the increase in product yield was correlated with a loss in volumetric productivity Espinel-Ríos, Morabito, Pohlodek, et al 2022). Here we show that with a fed-batch system it is possible to increase both the product yield via the ATP turnover mechanism and the volumetric productivity via the introduction of a feeding rate.…”

Section: Open-loop Optimal Optogenetic Controlmentioning

confidence: 98%

See 1 more Smart Citation

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics

Espinel-Ríos¹,

Bruno²,

Pohlodek³

et al. 2023

Preprint

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Biotechnology offers many opportunities for the sustainable manufacturing of valuable products. The toolbox to optimize bioprocesses includes extracellular process elements such as the bioreactor design and mode of operation, medium formulation, culture conditions, feeding rates, etc. However, these elements are frequently insufficient for achieving optimal process performance or precise product composition. One can use metabolic and genetic engineering methods for optimization at the intracellular level. Nevertheless, those are often of static nature, failing when applied to dynamic processes or if disturbances occur. Furthermore, many bioprocesses are optimized empirically and implemented with little-to-no feedback control to counteract disturbances. The concept of cybergenetics has opened new possibilities to optimize bioprocesses by enabling online modulation of the gene expression of metabolism-relevant proteins via external inputs (e.g., light intensity in optogenetics). Here, we fuse cybergenetics with model-based optimization and predictive control for optimizing dynamic bioprocesses. To do so, we propose to use dynamic constraint-based models that integrate the dynamics of metabolic reactions, resource allocation, and inducible gene expression. We formulate a model-based optimal control problem to find the optimal process inputs. Furthermore, we propose using model predictive control to address uncertainties via online feedback. We focus on fed-batch processes, where the substrate feeding rate is an additional optimization variable. As a simulation example, we show the optogenetic control of the ATPase enzyme complex for dynamic modulation of enforced ATP wasting to adjust product yield and productivity.

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Section: Open-loop Optimal Optogenetic Controlmentioning

confidence: 98%

“…Boecker et al (2021); Hädicke et al (2015); Zahoor et al (2020)). Dynamic manipulation of the ATPase expression, and thereby the ATPase flux, can thus be exploited to modulate the product yield and volumetric productivity in bioprocesses Espinel-Ríos, Morabito, Pohlodek, et al 2022).…”

Section: Example: Optogenetic Control Of Atpase For Anaerobic Lactate...mentioning

confidence: 99%

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics

Espinel-Ríos¹,

Bruno²,

Pohlodek³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…As foreseeable, the higher the induction capacity strength of the CcaS/CcaR system, the higher the net ATPase enzyme expression, and therefore the higher the net increase in product yield. In previous works dealing with dynamic ATP turnover in one‐stage batch fermentations, the increase in product yield was correlated with a loss in volumetric productivity (Espinel‐Ríos, Bettenbrock, et al, 2022; Espinel‐Ríos, Morabito, Bettenbrock, et al, 2022b). Here, we show that with a fed‐batch system, it is possible to increase both the product yield via the ATP turnover mechanism and the volumetric productivity via the introduction of a feeding rate.…”

Section: Example: Optogenetic Control Of Atpase In Anaerobic Lactate ...mentioning

confidence: 98%

“…e.g., Boecker et al, 2021; Hädicke et al, 2015; Zahoor et al, 2020). Dynamic manipulation of the ATPase expression, and thereby the ATPase flux, can thus be exploited to modulate the product yield and volumetric productivity in bioprocesses (Espinel‐Ríos, Bettenbrock, et al, 2022; Espinel‐Ríos, Morabito, Bettenbrock, et al 2022).…”

Section: Example: Optogenetic Control Of Atpase In Anaerobic Lactate ...mentioning

confidence: 99%

See 1 more Smart Citation

Toward a modeling, optimization, and predictive control framework for fed‐batch metabolic cybergenetics

Espinel‐Ríos,

Morabito,

Pohlodek

et al. 2023

Biotech & Bioengineering

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Biotechnology offers many opportunities for the sustainable manufacturing of valuable products. The toolbox to optimize bioprocesses includes extracellular process elements such as the bioreactor design and mode of operation, medium formulation, culture conditions, feeding rates, and so on. However, these elements are frequently insufficient for achieving optimal process performance or precise product composition. One can use metabolic and genetic engineering methods for optimization at the intracellular level. Nevertheless, those are often of static nature, failing when applied to dynamic processes or if disturbances occur. Furthermore, many bioprocesses are optimized empirically and implemented with little‐to‐no feedback control to counteract disturbances. The concept of cybergenetics has opened new possibilities to optimize bioprocesses by enabling online modulation of the gene expression of metabolism‐relevant proteins via external inputs (e.g., light intensity in optogenetics). Here, we fuse cybergenetics with model‐based optimization and predictive control for optimizing dynamic bioprocesses. To do so, we propose to use dynamic constraint‐based models that integrate the dynamics of metabolic reactions, resource allocation, and inducible gene expression. We formulate a model‐based optimal control problem to find the optimal process inputs. Furthermore, we propose using model predictive control to address uncertainties via online feedback. We focus on fed‐batch processes, where the substrate feeding rate is an additional optimization variable. As a simulation example, we show the optogenetic control of the ATPase enzyme complex for dynamic modulation of enforced ATP wasting to adjust product yield and productivity.

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Soft sensor for monitoring dynamic changes in cell composition

et al. 2022

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Optimal control and dynamic modulation of the ATPase gene expression for enforced ATP wasting in batch fermentations

Cited by 6 publications

References 22 publications

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics

Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics

Toward a modeling, optimization, and predictive control framework for fed‐batch metabolic cybergenetics

Soft sensor for monitoring dynamic changes in cell composition

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