Analysis and Control of Genetic Toggle Switches Subject to Periodic Multi-Input Stimulation

In this paper, we address the system identification problem in the context of biological modelling. We present and demonstrate a methodology for (i) assessing the possibility of inferring the unknown quantities in a dynamic model and (ii) effectively estimating them from output data. We introduce the term Full Input-State-Parameter Observability (FISPO) analysis to refer to the simultaneous assessment of state, input and parameter observability (note that parameter observability is also known as identifiability). This type of analysis has often remained elusive in the presence of unmeasured inputs. The method proposed in this paper can be applied to a general class of nonlinear ordinary differential equations models. We apply this approach to three models from the recent literature. First, we determine whether it is theoretically possible to infer the states, parameters and inputs, taking only the model equations into account. When this analysis detects deficiencies, we reformulate the model to make it fully observable. Then we move to numerical scenarios and apply an optimization-based technique to estimate the states, parameters and inputs. The results demonstrate the feasibility of an integrated strategy for (i) analysing the theoretical possibility of determining the states, parameters and inputs to a system and (ii) solving the practical problem of actually estimating their values.

show abstract

“…The second case study is the genetic toggle switch that was recently presented in [ 51 ] and further analysed in [ 52 ]:

…”

Section: Resultsmentioning

confidence: 99%

Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models

Villaverde¹,

Tsiantis

Banga³

2019

J. R. Soc. Interface.

101

137

View full text Add to dashboard Cite

show abstract

“…Other works in the literature have considered the additional control problem of stabilizing the toggle-switch about some intermediate expression levels of X 1 and X 2 , see e.g. [7]- [9], [12]- [14]; a problem we do not address in this paper.…”

Section: A Target Populationmentioning

confidence: 99%

Multicellular feedback control of a genetic toggle-switch in microbial consortia

Fiore

Salzano

Cristòbal-Cóppulo

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

We describe a multicellular approach to control a target cell population endowed with a bistable toggle-switch. The idea is to engineer a synthetic microbial consortium consisting of three different cell populations. In such a consortium, two populations, the Controllers, responding to some reference input, can induce the switch of a bistable memory mechanism in a third population, the Targets, so as to activate or deactivate some additional functionalities in the cells. Communication among the three populations is established by orthogonal quorum sensing molecules that are used to close a feedback control loop across the populations. The control design is validated via in-silico experiments in BSim, a realistic agentbased simulator of bacterial populations.

show abstract

“…The inputs to the system are modeled by the nonlinear functions w 1 and w 2 whose expression was derived in our previous work (11 ).…”

Section: Average Modelmentioning

confidence: 99%

Balancing cell populations endowed with a synthetic toggle switch via adaptive pulsatile feedback control

Guarino

Fiore

Salzano

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Controlling cells endowed with the genetic toggle switch has been suggested as a benchmark problem in synthetic biology. It has been shown that a carefully selected periodic forcing can balance a population of such cells in an undifferentiated state.The effectiveness of these control strategies, however, can be mined by the presence of stochastic perturbations and uncertainties typically observed in biological systems and is therefore not robust. Here, we propose the use of feedback control strategies to enhance robustness and performance of the balancing action by selecting in realtime both the amplitude and the duty-cycle of the inducer molecular signals affecting the toggle switch behavior. We show, via in-silico experiments and realistic agent-based simulations, the effectiveness of the proposed strategies even in presence of uncertainties and stochastic effects. In so doing, we confirm previous observations made in the literature about coherence of the population when pulsatile forcing inputs are used but, contrary to what proposed in the past, we leverage feedback control techniques to endow the balancing strategy with unprecedented robustness and stability properties. We compare via in-silico experiments different control solutions and show their advantages and limitations from an in-vivo implementation viewpoint. Author ContributionsAG implemented the controllers, carried out the simulations and analyzed the data. DF derived the mathematical model used for control design and contributed to the synthesis of the feedback controllers and the data analysis. DS and AG contributed to the controllers' validation and implemented the agent-based study in BSim. MdB conceived the idea of the study. AG, DF and MdB wrote the paper.

show abstract

Analysis and Control of Genetic Toggle Switches Subject to Periodic Multi-Input Stimulation

Cited by 27 publications

References 12 publications

Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models

Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models

Multicellular feedback control of a genetic toggle-switch in microbial consortia

Balancing cell populations endowed with a synthetic toggle switch via adaptive pulsatile feedback control

Contact Info

Product

Resources

About