Context-Dependent Stability and Robustness of Genetic Toggle Switches with Leaky Promoters.

Andras Gyorgy

doi:10.3390/life11111150

Abstract

Multistable switches are ubiquitous building blocks in both systems and synthetic biology. Given their central role, it is thus imperative to understand how their fundamental properties depend not only on the tunable biophysical properties of the switches themselves, but also on their genetic context. To this end, we reveal in this article how these factors shape the essential characteristics of toggle switches implemented using leaky promoters such as their stability and robustness to noise, both at single-cell and population levels. In particular, our results expose the roles that competition for scarce transcriptional and translational resources, promoter leakiness, and cell-to-cell heterogeneity collectively play. For instance, the interplay between protein expression from leaky promoters and the associated cost of relying on shared cellular resources can give rise to tristable dynamics even in the absence of positive feedback. Similarly, we demonstrate that while promoter leakiness always acts against multistability, resource competition can be leveraged to counteract this undesirable phenomenon. Underpinned by a mechanistic model, our results thus enable the context-aware rational design of multistable genetic switches that are directly translatable to experimental considerations, and can be further leveraged during the synthesis of large-scale genetic systems using computer-aided biodesign automation platforms.

Highlights

Living cells function as microscopic factories, converting energy and building blocks into a large array of products [1]
After presenting the mathematical model and the technical tools underpinning our analysis, we reveal the role that promoter leakiness, scarcity of shared transcriptional and translational resources, and cell-to-cell heterogeneity collectively play to establish the fundamental stability and robustness properties of genetic switches
Assuming that the repressors bind as dimers [32,38,55,56] and considering leaky promoters [52], the de-dimensionalized dynamics of the toggle switch are given by the following equations: ẏ = α ν +

Summary

Introduction

Living cells function as microscopic factories, converting energy and building blocks into a large array of products [1]. The vision of synthetic biology is to reliably control these processes by bringing together tools from multiple fields, ranging from biotechnology and genetic engineering to control/systems engineering and machine learning [2,3,4]. Recent breakthroughs highlight that this approach holds the promise of revolutionizing multiple sectors, with examples ranging from biocomputing [5] through biotherapeutics [6] to biofuel production [7]. While modifying the genetic blueprint of living organisms is routine practice via genome editing, designing systems of even modest complexity still requires numerous iterative cycles and vast libraries [8,9] due to context-dependence [10,11], often leading to perplexing behavior [12,13]. Tackling the issue of modularity requires system-level approaches [25] that combine a diverse set of quantitative tools [26,27,28,29,30,31,32,33,34,35,36]

Methods

Results

Conclusion