Biology subjects

Cardelli, L.

Publications and source records attributed to Cardelli, L..

6 recordsLinked to original sources

bioRxiv2026

Noise analysis of derivative-action biomolecular topologies

Temporal gradient sensing is a fundamental capability observed across diverse natural biological systems, contributing to the coordination of their functions. Harnessing this ability is also of significant interest in synthetic biology, particularly for sensing and control applications. In this work, we focus on a biomolecular topology that exemplifies a broader class of signal-differentiating architectures, while introducing a structural variant of it. We examine their behavior under both nominal and non-ideal conditions, accounting for stochastic noise arising from different sources. Our investigation includes scenarios where these topologies operate independently, as well as when embedded within minimal regulatory architectures based on negative as well as positive feedback. We analyze the stability of the resulting macroscopic dynamics--a prerequisite for practical deployment--and quantify stochastic fluctuations in system output, providing comparisons with the corresponding input/unregulated process. Importantly, our results demonstrate that signal differentiation can be effectively implemented in a biomolecular setting without incurring deleterious noise amplification--a major concern in the utilization of derivative action across disciplines.

synthetic biology↗

bioRxiv2024

AC-BioSD : A biomolecular signal differentiator module with enhanced performance

Temporal gradient estimation is a pervasive phenomenon in natural biological systems and holds great promise for synthetic counterparts with broad-reaching applications. Here, we advance the concept of BioSD (Biomolecular Signal Differentiators) by introducing a novel biomolecular topology, termed Autocatalytic-BioSD or AC-BioSD. Its structure allows for insensitivity to input signal changes and high precision in terms of signal differentiation, even when operating far from nominal conditions. Concurrently, disruptive high-frequency signal components are effectively attenuated. In addition, the usefulness of our topology in biological regulation is highlighted via a PID (Proportional-Integral-Derivative) bio-control scheme with set point weighting and filtered derivative action in both the deterministic and stochastic domains.

synthetic biology↗

bioRxiv2022

On the Design of a PID Bio-controller with Set Point Weighting and Filtered Derivative Action

Effective and robust regulation of biomolecular processes is crucial for designing reliable synthetic bio-devices functioning in uncertain and constantly changing biological environments. Proportional-Integral-Derivative (PID) controllers are undeniably the most common way of implementing feed-back control in modern technological applications. Here, we introduce a highly tunable PID bio-controller with set point weighting and filtered derivative action presented as a chemical reaction network with mass action kinetics. To demonstrate its effectiveness, we apply our PID scheme on a simple biological process of two mutually activated species, one of which is assumed to be the output of interest. To highlight its performance advantages we compare it to PI regulation using numerical simulations in both the deterministic and stochastic setting.

synthetic biology↗

bioRxiv2022

Regulation strategies for two-output biomolecular networks

Feedback control theory facilitates the development of self-regulating systems with desired performance which are predictable and insensitive to disturbances. Feedback regulatory topologies are found in many natural systems and have been of key importance in the design of reliable synthetic bio-devices operating in complex biological environments. Here, we study control schemes for biomolecular processes with two outputs of interest, expanding previous traditional concepts describing one-output systems. Regulation of such processes may unlock new design possibilities but can be challenging due to coupling interactions; also potential disturbances applied on one of the outputs may affect both. We therefore propose architectures for robustly manipulating the ratio and linear combinations of the outputs as well as each of the outputs independently. To demonstrate their characteristics, we apply these architectures to a simple process of two mutually activated biomolecular species. We also highlight the potential for experimental implementation by exploring synthetic realizations both in vivo and in vitro. This work presents an important step forward in building bio-devices capable of sophisticated functions.

synthetic biology↗

bioRxiv2021

Biomolecular mechanisms for signal differentiation

Cells can sense temporal changes of molecular signals, allowing them to predict environmental vari-ations and modulate their behaviour. This paper elucidates the underlying biomolecular mechanisms of time derivative computation, facilitating the design of reliable synthetic differentiator devices for a variety of applications, ultimately expanding our understanding of cell behaviour. In particular, we describe and analyse three alternative biomolecular topologies that work as signal differentiators of high accuracy to arbitrary input signals around their nominal operation. We propose strategies to preserve their performance even in the presence of high-frequency input signal components, which are detrimental to the performance of most differentiators. We found that the core of the proposed topologies appears in natural regulatory networks and we further discuss their biological relevance. The simple structure of our designs makes them promising tools for realizing derivative control action in synthetic biology.

synthetic biology↗

bioRxiv2019

The Beacon Calculus: A formal method for the flexible and concise modelling of biological systems

Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This paper introduces the Beacon Calculus, a process algebra designed to simplify the task of modelling interacting biological components. Its breadth is demonstrated by creating models of DNA replication dynamics, the gene expression dynamics in response to DNA methylation damage, and a multisite phosphorylation switch. The flexibility of these models is shown by adapting the DNA replication model to further include two topics of interest from the literature: cooperative origin firing and replication fork barriers. The Beacon Calculus is supported with the open-source simulator bcs (https://github.com/MBoemo/bcs.git) to allow users to develop and simulate their own models. Author summarySimulating a model of a biological system can suggest ideas for future experiments and help ensure that conclusions about a mechanism are consistent with data. The Beacon Calculus is a new language that makes modelling simple by allowing users to simulate a biological system in only a few lines of code. This simplicity is critical as it allows users the freedom to come up with new ideas and rapidly test them. Models written in the Beacon Calculus are also easy to modify and extend, allowing users to add new features to the model or incorporate it into a larger biological system. We demonstrate the breadth of applications in this paper by applying the Beacon Calculus to DNA replication and DNA damage repair, both of which have implications for genome stability and cancer. We also apply it to multisite phosphorylation, which is important for cellular signalling. To enable users to create their own models, we created the open-source Beacon Calculus simulator bcs (https://github.com/MBoemo/bcs.git) which is easy to install and is well-supported by documentation and examples.

systems biology↗