Coordinated Spatial Pattern Formation in Biomolecular Communication Networks

TL;DR

This paper introduces a control theoretic framework to analyze and design biomolecular communication networks that self-organize into spatial patterns, with applications in synthetic biology.

Contribution

It develops a feedback model and stability analysis method for reaction-diffusion systems, and proposes a minimal synthetic circuit for pattern formation.

Findings

Derived conditions for Turing pattern formation in biomolecular networks

Introduced a novel activator-repressor-diffuser circuit motif

Validated the minimal circuit's ability to produce self-organized patterns

Abstract

This paper proposes a control theoretic framework to model and analyze the self-organized pattern formation of molecular concentrations in biomolecular communication networks, emerging applications in synthetic biology. In biomolecular communication networks, bionanomachines, or biological cells, communicate with each other using a cell-to-cell communication mechanism mediated by a diffusible signaling molecule, thereby the dynamics of molecular concentrations are approximately modeled as a reaction-diffusion system with a single diffuser. We first introduce a feedback model representation of the reaction-diffusion system and provide a systematic local stability/instability analysis tool using the root locus of the feedback system. The instability analysis then allows us to analytically derive the conditions for the self-organized spatial pattern formation, or Turing pattern formation, of the bionanomachines. We propose a novel synthetic biocircuit motif called activator-repressor-diffuser system and show that it is one of the minimum biomolecular circuits that admit self-organized patterns over cell population.