Noise in Biomolecular Systems: Modeling, Analysis, and Control Implications

TL;DR

This paper reviews the role of noise in biological and synthetic systems, emphasizing stochastic modeling, stability analysis, and the potential for noise to be both beneficial and problematic in genetic control and cybergenetics.

Contribution

It introduces a comprehensive review of stochastic reaction networks, ergodicity as a stability measure, and recent advances in noise-aware cybergenetics, highlighting new modeling and control strategies.

Findings

Noise can be exploited for biological functions.

Ergodicity effectively characterizes system stability.

Recent results show noise's dual role in cybergenetics.

Abstract

While noise is generally associated with uncertainties and often has a negative connotation in engineering, living organisms have evolved to adapt to (and even exploit) such uncertainty to ensure the survival of a species or implement certain functions that would have been difficult or even impossible otherwise. In this article, we review the role and impact of noise in systems and synthetic biology, with a particular emphasis on its role in the genetic control of biological systems, an area we refer to as Cybergenetics. The main modeling paradigm is that of stochastic reaction networks, whose applicability goes beyond biology, as these networks can represent any population dynamics system, including ecological, epidemiological, and opinion dynamics networks. We review different ways to mathematically represent these systems, and we notably argue that the concept of ergodicity presents a particularly suitable way to characterize their stability. We then discuss noise-induced properties and show that noise can be both an asset and a nuisance in this setting. Finally, we discuss recent results on (stochastic) Cybergenetics and explore their relationships to noise. Along the way, we detail the different technical and biological constraints that need to be respected when designing synthetic biological circuits. Finally, we discuss the concepts, problems, and solutions exposed in the article; raise criticisms and concerns about current ideas and approaches; suggest current (open) problems with potential solutions; and provide some ideas for future research directions.