Biology subjects

Fiore, D.

Publications and source records attributed to Fiore, D..

16 recordsLinked to original sources

bioRxiv2025

Root Contours Guided Design of a Multicellular PID Controller

Ensuring a stable and robust phenotype expression is a key challenge for the correct operation of synthetically engineered cells, and feedback has been highlighted as a key mechanism to achieve this goal. Biomolecular PID controllers have been extensively leveraged at a single cell level to regulate gene expression. However, single-cell architectures suffer from limited modularity and might pose a significant challenge for their in vivo implementation due to high metabolic load and possible incompatible reactions. To overcome these limitations, it has been proposed to distribute the control actions over different cell populations realizing a multicellular feedback control architecture. In this paper we provide design guidelines derived by means of the root contours method to tune the control gains of a multicellular PID controller. We then validate performance, robustness and modularity of the multicellular PID controller through in silico simulations in BSim.

synthetic biology↗

bioRxiv2025

Regulating population density through antithetic feedback control of cell growth

We present a genetic feedback control strategy enabling engineered microorganisms to self-regulate their population density. Our approach leverages a quorum sensing mechanism for the production of a growth inhibitor protein, whose activation is regulated by an embedded antithetic controller. Through mathematical modeling and steady-state analysis, we provide design guidelines to tune the control parameters. Finally, we validate the control architecture performance and robustness via realistic agent-based simulations in BSim. The proposed control architecture guarantees robust regulation of the cell density while relying on fewer constraints on the biological parameters with respect to other solutions presented in the literature.

synthetic biology↗

bioRxiv2024

In silico analysis of metabolic burden effects on a multicellular integral controller

Metabolic burden is a critical limiting factor in the design of synthetic circuits, affecting both their reliability and performance. To mitigate its effects, distributing control functions across different cell populations within a multicellular control architecture offers a promising solution, while simultaneously enhancing modularity and re-usability of the circuits. We first present a model that explicitly accounts for limited ribosome availability within cells. Using this framework, we then derive a mathematical model of a multicellular antithetic integral controller that incorporates these shared resources. Through numerical bifurcation analysis and in silico agent-based experiments in BSim, we compare the multicellular controller against its traditional single-cell (embedded) implementation, evaluating both resource utilization and stability.

synthetic biology↗

bioRxiv2024

Multicellular Proportional-Integral-Derivative Control for Robust Regulation of Biological Processes

This paper presents the first implementation of a Proportional-Integral-Derivative (PID) biomolecular controller within a consortium of different cell populations, aimed at robust regulation of biological processes. By leveraging the modularity and cooperative dynamics of multiple engineered cell populations, we develop a comprehensive in silico analysis of the performance and robustness of P, PD, PI, and PID control architectures. Our theoretical findings, validated through in silico experiments using the BSim agent-based simulation platform, demonstrate the robustness and effectiveness of our multicellular PID control strategy. This innovative approach addresses critical limitations in current control methods, offering significant potential for applications in metabolic engineering, therapeutic contexts, and industrial biotechnology. Future work will focus on experimental validation in vivo and further refinement of the control models.

synthetic biology↗

bioRxiv2024

Ratiometric control of two microbial populations in a dual chamber bioreactor

Maintaining stable coexistence in microbial consortia, particularly when one species grows faster than another (i.e. the species are non-complementary), poses significant challenges. We introduce a novel control architecture that employs two bioreactors. In this system, the slower-growing species is cultivated separately before being introduced into the main mixing chamber. We analyze the open-loop dynamics of this setup and propose a switching feedback mechanism that controls the dilution rates to ensure robust regulation of population density and composition within the microbial consortium. Validated in silico using parameters from real experiments, our approach demonstrates effective and robust maintenance of microbial balance across various strains without requiring genetic modifications.

synthetic biology↗

bioRxiv2023

Multicellular PD Control in Microbial Consortia

We propose a multicellular implementation of a biomolecular PD feedback controller to regulate gene expression in a microbial consortium. The implementation involves distributing the proportional and derivative control actions between two different cellular populations that can communicate with each other and regulate the output of a third target cellular population. We derive analytical conditions on biological parameters and control gains to adjust the systems static and dynamical properties. We then validate the strategys performance and robustness through extensive in silico experiments.

synthetic biology↗

bioRxiv2022

Multicellular PI control for gene regulation in microbial consortia

We describe two multicellular implementations of the classical P and PI feedback controllers for the regulation of gene expression in a target cell population. Specifically, we propose to distribute the proportional and integral actions over two different cellular populations in a microbial consortium comprising a third target population whose output needs to be regulated. By engineering communication among the different cellular populations via appropriate orthogonal quorum sensing molecules, we are able to close the feedback loop across the consortium. We derive analytical conditions on the biological parameters guaranteeing the regulation of the output of the target population and we validate the robustness and modularity of proposed control schemes via in silico experiments in BSim, a realistic agent-based simulator of bacterial populations.

synthetic biology↗

bioRxiv2021

Controlling reversible cell differentiation for labor division in microbial consortia

We address the problem of regulating and keeping at a desired balance the relative numbers between cells exhibiting a different phenotype within a monostrain microbial consortium. We propose a strategy based on the use of external control inputs, assuming each cell in the community is endowed with a reversible, bistable memory mechanism. Specifically, we provide a general analytical framework to guide the design of external feedback control strategies aimed at balancing the ratio between cells whose memory is stabilized at either one of two equilibria associated to different cell phenotypes. We demonstrate the stability and robustness properties of the control laws proposed and validate them in silico by means of a realistic agent-based implementation enabling cooperative bioproduction in microbial consortia. The proposed control framework may be used to allow long term coexistence of different populations, with both industrial and biotechnological applications.

synthetic biology↗

bioRxiv2021

Embedded control of cell growth using tunable genetic systems

We present an embedded feedback control strategy to control the density of a bacterial population, 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 on 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.

synthetic biology↗

bioRxiv2021

Feedback ratiometric control of two microbial populations in a single chemostat

We address the problem of controlling the dilution rate in a chemostat to regulate the ratio between the concentrations of two microbial populations growing in continuous culture. After analyzing the open-loop dynamics of this multicellular system, we present two alternative feedback control strategies, one based on a gain-scheduled state feedback controller, the other on a switching control strategy. We show that both strategies are effective in solving the problem and illustrate the results by a set of representative numerical simulation.

synthetic biology↗

bioRxiv2020

Cyber-yeast: Automatic synchronisation of the cell cycle in budding yeast through closed-loop feedback control

The cell cycle is the process by which eukaryotic cells replicate. Yeast cells cycle asynchronously with each cell in the population budding at a different time. Although there are several experimental approaches to "synchronise" cells, these work only in the short-term. Here, we built a cyber-genetic system to achieve long-term synchronisation of the cell population, by interfacing genetically modified yeast cells with a computer by means of microfluidics to dynamically change medium, and a microscope to estimate cell cycle phases of individual cells. The computer implements a "controller" algorithm to decide when, and for how long, to change the growth medium to synchronise the cell-cycle across the population. Our work builds upon solid theoretical foundations provided by Control Engineering. In addition to providing a new avenue for yeast cell cycle synchronisation, our work shows that computers can automatically steer complex biological processes towards desired behaviours similarly to what is currently done with robots and autonomous vehicles.

synthetic biology↗

bioRxiv2020

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

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 Togglers, 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 agent-based simulator of bacterial populations.Competing Interest StatementThe authors have declared no competing interest.View Full Text

synthetic biology↗

bioRxiv2019

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

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 real-time 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.

synthetic biology↗

bioRxiv2019

Feedback control promotes synchronisation of the cell-cycle across a population of yeast cells

The periodic process of cell replication by division, known as cell-cycle, is a natural phenomenon occurring asynchronously in any cell population. Here, we consider the problem of synchronising cell-cycles across a population of yeast cells grown in a microfluidics device. Cells were engineered to reset their cell-cycle in response to low methionine levels. Automated syringes enable changing methionine levels (control input) in the microfluidics device. However, the control input resets only those cells that are in a specific phase of the cell-cycle (G1 phase), while the others continue to cycle unperturbed. We devised a simplified dynamical model of the cell-cycle, inferred its parameters from experimental data and then designed two control strategies: (i) an open-loop controller based on the application of periodic stimuli; (ii) a closed-loop model predictive controller (MPC) that selects the sequence of control stimuli which maximises a synchronisation index. Both the proposed control strategies were validated in-silico, together with experimental validation of the open-loop strategy.

synthetic biology↗

bioRxiv2019

Pathogenic potential of Hic1 expressing cardiac stromal progenitors

The cardiac stroma contains multipotent mesenchymal progenitors. However, lineage relationships within cardiac stromal cells are still poorly understood. Here, we identify heart-resident PDGFRa+ Sca-1+ cells as cardiac Fibro/Adipogenic Progenitors (cFAPs) and show that they respond to ischemic damage by generating fibrogenic cells. Pharmacological blockade of this differentiation step with an anti-fibrotic tyrosine kinase inhibitor decreases post-myocardial infarction (MI) remodeling and leads to improvements in heart function. In the undamaged heart, activation of cFAPs through lineage-specific deletion of the quiescence factor Hic1 reveals additional pathogenic potential, causing fibro-fatty infiltration of the myocardium and driving major pathological features of Arrhythmogenic Cardiomyopathy (AC). HighlightsO_LIA subpopulation of PDGFRa+, Sca-1+ cells, previously considered to be a sub-type of cardiac fibroblasts, are multipotent mesenchymal progenitors, C_LIO_LICardiac damage triggers the differentiation of PDGFRa+ Sca-1+ cells into Sca-1- cells expressing a fibrogenic transcriptional programme, C_LIO_LIBlockade of the cFAP-to-fibroblast transition by Nilotinib ameliorated cardiac dysfunction post-MI and modulated cardiac remodelling. C_LIO_LIStudies performed on a model of experimentally-induced AC confirmed that cFAPs are a source of both cardiac fibroblasts and adipocytes in vivo. C_LIO_LIConversely, in the undamaged heart, activation of cFAPs by means of lineage-specific deletion of transcription factor Hic1, resulted in fibro/fatty cardiac degeneration and pathological alterations reminiscent of AC. Collectively, our findings show that a proportion of what are commonly termed "fibroblasts" are actually multipotent mesenchymal progenitors that contribute to different forms of cardiac degeneration depending on the damage setting. C_LI

cell biology↗

bioRxiv2018

Towards feedback control of the cell-cycle across a population of yeast cells

Cells are defined by their unique ability to selfreplicate through cell division. This periodic process is known as the cell-cycle and it happens with a defined period in each cell. The budding yeast divides asymmetrically with a mother cell generating multiple daughter cells. Within the cell population each cell divides with the same period but asynchronously. Here, we investigate the problem of synchronising the cell-cycle across a population of yeast cells through a microfluidics-based feedback control platform. We propose a theoretical and experimental approach for cell-cycle control by considering a yeast strain that can be forced to start the cell-cycle by changing growth medium. The duration of the cell-cycle is strictly linked to the cell volume growth, hence a hard constraint in the controller design is to prevent excessive volume growth. We experimentally characterised the yeast strain and derived a simplified phase-oscillator model of the cell-cycle. We then designed and implemented three impulsive control strategies to achieve maximal synchronisation across the population and assessed their control performance by numerical simulations. The first two controllers are based on event-triggered strategies, while the third uses a model predictive control (MPC) algorithm to select the sequence of control impulses while satisfying built-in constraints on volume growth. We compared the three strategies by computing two cost functions: one quantifying the level of synchronisation across the cell population and the other volume growth during the process. We demonstrated that the proposed control approaches can effectively achieve an acceptable trade-off between two conflicting control objectives: (i) obtaining maximal synchronisation of the cell cycle across the population while (ii) minimizing volume growth. The results can be used to implement effective strategies to unfold the biological mechanisms controlling cell cycle and volume growth in yeast cells.

synthetic biology↗