A Predictive Reaction-diffusion Based Model of E. coli Colony Growth Control

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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)
Title of host publication2021 American Control Conference, ACC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1891-1896
Number of pages6
ISBN (Electronic)9781665441971
DOIs
StatePublished - May 25 2021
Event2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States
Duration: May 25 2021May 28 2021

Publication series

NameProceedings of the American Control Conference
Volume2021-May
ISSN (Print)0743-1619

Conference

Conference2021 American Control Conference, ACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans
Period5/25/215/28/21

Keywords

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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