A Predictive Reaction-Diffusion Based Model of E. ColiColony Growth Control

Changhan He, Samat Bayakhmetov, Duane Harris, Yang Kuang, Xiao Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Bacterial colony formations exhibit diverse morphologies and dynamics. A mechanistic understanding of this process has broad implications to ecology and medicine. However, many control factors and their impacts on colony formation remain underexplored. Here we propose a reaction-diffusion based dynamic model to quantitatively describe cell division and colony expansion, where control factors of colony spreading take the form of nonlinear density-dependent function and the intercellular impacts take the form of density-dependent hill function. We validate the model using experimental E. coli colony growth data and our results show that the model is capable of predicting the whole colony expansion process in both time and space under different conditions. Furthermore, the nonlinear control factors can predict colony morphology at both center and edge of the colony.

Original languageEnglish (US)
Article number9305287
Pages (from-to)1952-1957
Number of pages6
JournalIEEE Control Systems Letters
Volume5
Issue number6
DOIs
StatePublished - Dec 2021

Keywords

  • Synthetic biology
  • bacterial colony expansion
  • diffusion
  • partial differential equations

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

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