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Related Experiment Video

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Updated Protocol for the Assembly and Use of the Minibioreactor Array (MBRA)
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A mechanistic Individual-based Model of microbial communities.

Pahala Gedara Jayathilake1, Prashant Gupta2, Bowen Li3

  • 1School of Mechanical & Systems Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom.

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|August 4, 2017
PubMed
Summary

This study introduces a new computational model for predicting bacterial community growth by integrating biological, chemical, and mechanical processes. The model accurately simulates biofilm formation and behavior under various conditions, advancing predictive microbiology.

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Area of Science:

  • Microbial Ecology
  • Computational Biology
  • Biophysics

Background:

  • Accurate microbial community growth prediction necessitates integrating biological, chemical, and mechanical processes.
  • Existing Individual-based Models (IbMs) often lack comprehensive integration of these factors, with limitations in representing mechanical interactions or detailed biological/chemical processes.
  • A gap exists in flexible models capable of robustly combining diverse processes for predicting bacterial community emergent properties.

Purpose of the Study:

  • To develop a flexible Individual-based Model (IbM) that integrates biological, chemical, and physical processes for predicting bacterial community behavior.
  • To address limitations in current models by incorporating mechanical interactions alongside detailed biological and chemical processes.
  • To provide a "bottom-up" predictive framework for the emergent behavior of diverse bacterial communities.

Main Methods:

  • Development of a microbiological adaptation of the open-source Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS).
  • Incorporation of bacterial growth, division, decay, cell-cell mechanical contact, and adhesion to extracellular polymeric substances.
  • Implementation of fluid-bacteria interaction to simulate biofilm deformation and erosion.

Main Results:

  • The model predicts smoother biofilm morphology with increased nutrient concentration, consistent with existing literature.
  • Increased shear rate leads to smoother and more compact biofilms.
  • The model successfully predicts shear rate-dependent biofilm deformation, erosion, streamer formation, and breakup.

Conclusions:

  • The developed Individual-based Model (IbM) offers a robust framework for integrating diverse processes in bacterial communities.
  • This approach enables "bottom-up" prediction of emergent behaviors in microbial systems.
  • The model's predictions align with experimental observations, validating its utility in microbial ecology and biophysics.