A modular approach to achieve multistationarity using AND-gates

TL;DR

This paper introduces a modular method using AND-gates in differential equation systems to design biological networks with any desired number of stable steady states, aiding in phenotype control.

Contribution

It presents a combinatorial approach to predict stable states from network structure and demonstrates the practical engineering of AND gates in gene networks.

Findings

Predicts number of stable steady states from wiring diagram structure.

Provides a modular design framework for gene networks with arbitrary phenotypes.

Validates the approach with experimental gene network engineering.

Abstract

Systems of differential equations have been used to model biological systems such as gene and neural networks. A problem of particular interest is to understand the number of stable steady states. Here we propose conjunctive networks (systems of differential equations equations created using AND gates) to achieve any desired number of stable steady states. Our approach uses combinatorial tools to predict the number of stable steady states from the structure of the wiring diagram. Furthermore, AND gates have been successfully engineered by experimentalists for gene networks, so our results provide a modular approach to design gene networks that achieve arbitrary number of phenotypes.