Biology subjects

di Bernardo, M.

Publications and source records attributed to di Bernardo, M..

At least 19 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

Data-driven inference of digital twins for high-throughput phenotyping of motile and light-responsive microorganisms

Light can affect the movement of microorganisms. These responses can drive collective behaviours like photoaccumulation and photodispersion, which play a key role in broader biological functions like photosynthesis. Our understanding of these emergent phenomena is severely limited by difficulties in obtaining data needed to establish accurate models that can serve as a basis for multi-scale analyses. Here, we address this issue by developing an integrated experimental and computational platform to collect large temporal imaging datasets that allow for the inference of digital twins -- mathematically precise computational models that accurately mirror the behavior of individual microorganisms -- and show that they can replicate the light response of diverse microorganisms in silico. We show that a generalised phenomenological model of movement can be effectively parameterised from experimental data to capture key behavioural traits of two commonly studied photo-responsive microorganisms (Euglena gracilis and Volvox aureus) and demonstrate our models ability to accurate reproduce patterns of movement for individuals and populations in response to dynamic and spatially varying light patterns. This work takes steps towards the automated phenotyping of multi-scale behaviours in biology and complements high-throughput genome sequencing efforts by allowing for more comprehensive and quantitative genotype-to-phenotype mappings. It also unlocks new opportunities for the design of spatial control algorithms to guide collective microorganism behaviour.

systems biology↗

bioRxiv2025

Visual Influence Networks in Walking Crowds

Collective motion in human crowds has been understood as a self-organizing phenomenon that is generated from local visual interactions between neighboring pedestrians. To analyze these interactions, we introduce an approach that estimates local influences in observational data on moving human crowds and represents them as spatially-embedded dynamic networks (visual influence networks). We analyzed data from a human "swarm" experiment (N = 10, 16, 20) in which participants were instructed to walk about the tracking area while staying together as a group. We reconstructed the network every 0.5 seconds using Time-Dependent Delayed Correlation (TDDC). Using novel network measures of local and global leadership (direct influence and branching influence), we find that both measures strongly depend on an individuals spatial position within the group, yielding similar but distinctive leadership gradients from the front to the back. There was also a strong linear relationship between individual influence and front-back position in the crowd. The results reveal that influence is concentrated in specific positions in a crowd, a fact that could be exploited by individuals seeking to lead collective crowd motion.

animal behavior and cognition↗

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

In-vivo multicellular control of gene expression in microbial consortia

This paper presents an innovative approach in synthetic biology, focusing on the engineering of biomolecular feedback control systems within microbial consortia to achieve robust and precise regulation of desired phenotypes. Traditional biomolecular control strategies, while effective, are predominantly confined to single-cell applications, limiting their complexity and adaptability due to metabolic constraints. We propose a novel methodology that distributes control functionalities across different cell populations within a microbial consortium. This approach leverages the division of labor and cooperative interactions among microbial populations, significantly enhancing flexibility and robustness. We build on the foundation of synthetically engineered microbial consortia, known for their applications in complex compound production and advanced computational processes. However, the challenge of implementing a distributed feedback control loop for precise phenotype regulation in synthetic communities has remained unaddressed. Our work closes this gap by developing and validating an in-vivo feedback control loop distributed across a bacterial consortium, specifically designed using two Escherichia coli strains. These strains are engineered to perform the three essential control functions: computation, sensing, and actuation. We employ orthogonal quorum sensing signaling molecules for communication between the controller and target cell populations. Through in-vivo experiments, we compare closed-loop and open-loop configurations to demonstrate the effectiveness of our approach. The results show that our distributed control system can regulate gene expression levels in target populations with high precision and robustness, even in the presence of consortium composition variations. This feature is particularly vital for practical applications in synthetic biology where stability and adaptability are crucial. Our study not only addresses a significant gap in synthetic biology literature but also opens avenues for more complex and reliable synthetic biology applications.

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

Control-based continuation: a new approach to prototype synthetic gene networks

Control-Based Continuation (CBC) is a general and systematic method to carry out the bifurcation analysis of physical experiments. CBC does not rely on a mathematical model and thus overcomes the uncertainty introduced when identifying bifurcation curves indirectly through modelling and parameter estimation. We demonstrate, in silico, CBC applicability to biochemical processes by tracking the equilibrium curve of a toggle switch which includes additive process noise and exhibits bistability. We compare results obtained when CBC uses a model-free and model-based control strategy and show that both can track stable and unstable solutions, revealing bistability. We then demonstrate CBC in conditions more representative of a real experiment using an agent-based simulator describing cells growth and division, cell-to-cell variability, spatial distribution, and diffusion of chemicals. We further show how the identified curves can be used for parameter estimation and discuss how CBC can significantly accelerate the prototyping of synthetic gene regulatory networks.

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

ChipSeg: an automatic tool to segment bacteria and mammalian cells cultured in microfluidic devices

Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. While such image segmentation applications have been previously reported, there is in the literature a lack of open-source and documented code for the community. We describe ChipSeg, a computational tool to segment bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy. The method is based on thresholding and uses the same core functions for both cell types. It allows to segment individual cells in high cell-density microfluidic devices, to quantify fluorescence protein expression over a time-lapse experiment and to track individual cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customised for other experimental settings and research aims.

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

Tunable genetic devices through simultaneous control of transcription and translation

Synthetic genetic circuits allow us to modify the behavior of living cells. However, changes in environmental conditions and unforeseen interactions with the host cell can cause deviations from a desired function, resulting in the need for time-consuming reassembly to fix these issues. Here, we use a regulatory motif that controls transcription and translation to create genetic devices whose response functions can be dynamically tuned. This allows us, after construction, to shift the on and off states of a sensor by 4.5- and 28-fold, respectively, and modify genetic NOT and NOR logic gates to allow their transitions between states to be varied over a >6-fold range. In all cases, tuning leads to trade-offs in the fold-change and the ability to distinguish cellular states. This work lays the foundation for adaptive genetic circuits that can be tuned after their physical assembly to maintain functionality across diverse environments and design contexts.

synthetic biology↗