Engineering reliable synthetic circuits in living organisms is very challenging because of molecular fluctuations, cell-to-cell variability and metabolic burden, for instance. Recently, the antithetic integral controller (AIC) has been proposed as an effective strategy to design robust synthetic circuits in living cells. In its canonical form, the AIC acts at the single-cell level to regulate the abundance of a certain intracellular component to a prescribed set-point. In this work, we propose a variant of the AIC that allows the control of collective properties of a dynamic cell population, such as the cell number or the total amount of protein expressed across the population. The resulting controller - which we term shared AIC (sAIC) - uses a single controller network that acts on all cells simultaneously through a shared environment. We describe the sAIC mathematically using a stochastic multiscale formalism, which accounts for noisy cell-internal dynamics as well as cell division and death events. We demonstrate the effectiveness of the sAIC approach using two simulation-based case studies.

Shared antithetic integral control for dynamic cell populations / Duso, L; Bianucci, T; Zechner, C. - (2021), pp. 2053-2058. (Intervento presentato al convegno 60th IEEE Conference on Decision and Control, CDC 2021 tenutosi a Austin, TX, USA nel 14-17 December 2021) [10.1109/CDC45484.2021.9683346].

Shared antithetic integral control for dynamic cell populations

Zechner, C
2021-01-01

Abstract

Engineering reliable synthetic circuits in living organisms is very challenging because of molecular fluctuations, cell-to-cell variability and metabolic burden, for instance. Recently, the antithetic integral controller (AIC) has been proposed as an effective strategy to design robust synthetic circuits in living cells. In its canonical form, the AIC acts at the single-cell level to regulate the abundance of a certain intracellular component to a prescribed set-point. In this work, we propose a variant of the AIC that allows the control of collective properties of a dynamic cell population, such as the cell number or the total amount of protein expressed across the population. The resulting controller - which we term shared AIC (sAIC) - uses a single controller network that acts on all cells simultaneously through a shared environment. We describe the sAIC mathematically using a stochastic multiscale formalism, which accounts for noisy cell-internal dynamics as well as cell division and death events. We demonstrate the effectiveness of the sAIC approach using two simulation-based case studies.
2021
60th IEEE Conference on Decision and Control, CDC 2021
2053
2058
IEEE
Duso, L; Bianucci, T; Zechner, C
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/145864
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 3
social impact