Espinel-Ríos, Sebastián ; Morabito, Bruno ; Pohlodek, Johannes ; Bettenbrock, Katja ; Klamt, Steffen ; Findeisen, Rolf (2022)
Optimal control and dynamic modulation of the ATPase gene expression for enforced ATP wasting in batch fermentations.
In: IFAC-PapersOnLine, 55 (7)
doi: 10.1016/j.ifacol.2022.07.440
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Competitive biotechnological processes need to operate over various conditions and adapt to changing economic contexts. Dynamic ATP turnover allows trading off declines in biomass formation and volumetric productivity for enhancements of product yields in fermentations where the product pathway is linked to ATP synthesis. To facilitate its practical implementation, we propose to dynamically manipulate the cellular ATP turnover by putting the ATPase enzyme, which hydrolyzes ATP into ADP, under the control of an optogenetic gene expression system. This allows achieving dynamic control of the ATP wasting online via a tunable external input. While light as control input is promising because it is easily tunable, generally non-invasive/non-toxic, and more affordable than classical chemical inducers, it makes the overall control task challenging. Thus, we derive an expanded version of dynamic enzyme-cost flux balance analysis that takes into account the dynamics of the optogenetic actuator. We then formulate a suitable optimal control problem to find optimal inputs for achieving the desired process performance. We test our approach in simulations using the batch anaerobic lactate fermentation of glucose by Escherichia coli as a case study.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Espinel-Ríos, Sebastián ; Morabito, Bruno ; Pohlodek, Johannes ; Bettenbrock, Katja ; Klamt, Steffen ; Findeisen, Rolf |
| Art des Eintrags: | Bibliographie |
| Titel: | Optimal control and dynamic modulation of the ATPase gene expression for enforced ATP wasting in batch fermentations |
| Sprache: | Englisch |
| Publikationsjahr: | Juli 2022 |
| Verlag: | Elsevier |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IFAC-PapersOnLine |
| Jahrgang/Volume einer Zeitschrift: | 55 |
| (Heft-)Nummer: | 7 |
| DOI: | 10.1016/j.ifacol.2022.07.440 |
| Kurzbeschreibung (Abstract): | Competitive biotechnological processes need to operate over various conditions and adapt to changing economic contexts. Dynamic ATP turnover allows trading off declines in biomass formation and volumetric productivity for enhancements of product yields in fermentations where the product pathway is linked to ATP synthesis. To facilitate its practical implementation, we propose to dynamically manipulate the cellular ATP turnover by putting the ATPase enzyme, which hydrolyzes ATP into ADP, under the control of an optogenetic gene expression system. This allows achieving dynamic control of the ATP wasting online via a tunable external input. While light as control input is promising because it is easily tunable, generally non-invasive/non-toxic, and more affordable than classical chemical inducers, it makes the overall control task challenging. Thus, we derive an expanded version of dynamic enzyme-cost flux balance analysis that takes into account the dynamics of the optogenetic actuator. We then formulate a suitable optimal control problem to find optimal inputs for achieving the desired process performance. We test our approach in simulations using the batch anaerobic lactate fermentation of glucose by Escherichia coli as a case study. |
| Zusätzliche Informationen: | Special Issue to the 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS); Busan, Republic of Korea 14.-17.06.2022 |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Control and Cyber-Physical Systems (CCPS) |
| Hinterlegungsdatum: | 16 Nov 2022 12:38 |
| Letzte Änderung: | 10 Mai 2023 13:41 |
| PPN: | 507667034 |
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