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BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology

Author

Listed:
  • Thomas E Gorochowski
  • Antoni Matyjaszkiewicz
  • Thomas Todd
  • Neeraj Oak
  • Kira Kowalska
  • Stephen Reid
  • Krasimira T Tsaneva-Atanasova
  • Nigel J Savery
  • Claire S Grierson
  • Mario di Bernardo

Abstract

Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

Suggested Citation

  • Thomas E Gorochowski & Antoni Matyjaszkiewicz & Thomas Todd & Neeraj Oak & Kira Kowalska & Stephen Reid & Krasimira T Tsaneva-Atanasova & Nigel J Savery & Claire S Grierson & Mario di Bernardo, 2012. "BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-9, August.
    • Handle: RePEc:plo:pone00:0042790
    DOI: 10.1371/journal.pone.0042790
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    References listed on IDEAS

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