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.
Original language | English |
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Article number | 7328285 |
Pages (from-to) | 111-121 |
Number of pages | 11 |
Journal | IEEE Transactions on Molecular, Biological, and Multi-Scale Communications |
Volume | 1 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2015 Jun |
Externally published | Yes |
Keywords
- Molecular communication networks
- Stability analysis
- Turing pattern
ASJC Scopus subject areas
- Biotechnology
- Bioengineering
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Modelling and Simulation