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Related Experiment Video

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Three-dimensional Imaging of Bacterial Cells for Accurate Cellular Representations and Precise Protein Localization
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Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations.

Jonathan Naylor1, Harold Fellermann1, Yuchun Ding1

  • 1Interdisciplinary Computing and Complex Biosystems (ICOS) research group, School of Computing Science, Newcastle University , Newcastle upon Tyne NE1 7RU, U.K.

ACS Synthetic Biology
|May 6, 2017
PubMed
Summary

Simbiotics is a versatile modeling platform for simulating bacterial populations, from single cells to biofilms. It offers a flexible framework for designing, analyzing, and visualizing complex bacterial systems with a user-friendly interface.

Keywords:
agent-based modelbacterial populationbiofilminteractionmultiscalesimulation

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Area of Science:

  • Microbiology
  • Computational Biology
  • Systems Biology

Background:

  • Bacterial population dynamics are complex, involving interactions from cellular to community levels.
  • Accurate modeling requires platforms that integrate spatial, genetic, metabolic, and physical factors.
  • Existing tools may lack the flexibility or multiscale capabilities needed for comprehensive bacterial system analysis.

Purpose of the Study:

  • To introduce Simbiotics, a spatially explicit multiscale modeling platform for bacterial populations.
  • To provide a flexible and extendable framework for designing, simulating, and analyzing diverse bacterial systems.
  • To demonstrate the platform's utility as a computational tool for both natural and synthetic biology applications.

Main Methods:

  • Spatially explicit multiscale modeling approach.
  • Modular framework with libraries for cell geometries, physical dynamics, genetic circuits, metabolism, diffusion, and interactions.
  • Integration of user-defined processes and support for standards like SBML.
  • Parallel processing for multithread and multi-CPU execution.
  • Virtual lab environment for automated data collection and analysis.
  • Processing of microscopy images for 3D spatial initialization of bacterial consortia.

Main Results:

  • Simbiotics enables modeling of bacterial systems at various scales, including planktonic cells, colonies, and biofilms.
  • The platform supports flexible representation of biological systems and user-defined processes.
  • Demonstrated versatility through case studies focusing on physical properties and synthetic biology applications.
  • Facilitates automated data collection and analysis via a virtual lab environment.

Conclusions:

  • Simbiotics offers a powerful and adaptable platform for the comprehensive modeling and analysis of bacterial populations.
  • Its modular design and user-friendly interface support the development of novel bacterial models and synthetic biology designs.
  • The platform effectively integrates diverse biological and physical aspects, advancing the study of bacterial systems.