Abstract
We present an embedded feedback control strategy to regulate the density of a microbial population, that is, the number of cells into a given environment, allowing cells to self-regulate their growth rate so as to reach a desired density at steady state. We consider a static culture condition, where cells are provided with a limited amount of space and nutrients. The control strategy is built using a tunable expression system (TES), which controls the production of a growth inhibitor protein, complemented with a quorum sensing mechanism for the sensing of the population density. We show via a simplified population-level model that the TES endows the control system with additional flexibility by allowing the set-point to be changed online. Finally, we validate the effectiveness of the proposed control strategy by means of realistic in silico experiments conducted in BSim, an agent-based simulator explicitly designed to simulate bacterial populations, and we test the robustness of our design to disturbances and parameters' variations due, for instance, to cell-to-cell variability.
Original language | English |
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Number of pages | 15 |
Journal | International Journal of Robust and Nonlinear Control |
DOIs | |
Publication status | Published - 7 Jan 2022 |
Bibliographical note
Funding Information:Mario di Bernardo, Davide Fiore, and Davide Salzano wish to acknowledge support from the European Union's Horizon 2020 research and innovation programme under grant agreement No 766840 (COSY‐BIO). Davide Fiore also wishes to acknowledge support by the research grant “BIOMASS” from the University of Naples Federico II–“Finanziamento della Ricerca di Ateneo (FRA)–Linea B”.
Publisher Copyright:
© 2022 John Wiley & Sons Ltd.
Research Groups and Themes
- Engineering Mathematics Research Group
Keywords
- cell population control
- cybergenetics
- embedded control
- gene regulatory networks
- syntheticbiology
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Dive into the research topics of 'Embedded control of cell growth using tunable genetic systems'. Together they form a unique fingerprint.Student theses
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Development and validation of synthetically engineered microbial consortia
Salzano, D. (Author), Di Bernardo, M. (Supervisor), Savery, N. (Supervisor) & Marucci, L. (Supervisor), 24 Jan 2023Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)
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