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Multi-scale Analysis of Bacterial Growth Under Stress Treatments
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Multiscale simulation of microbe structure and dynamics.

Harshad Joshi1, Abhishek Singharoy, Yuriy V Sereda

  • 1Center for Cell and Virus Theory, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA.

Progress in Biophysics and Molecular Biology
|August 2, 2011
PubMed
Summary

A new multiscale approach models microbes from atoms to whole organisms. This framework enhances understanding of microbial behavior and aids in designing nanostructures for biotech and medicine.

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Area of Science:

  • Multiscale mathematical and computational modeling
  • Bionanoscience and microbial systems

Background:

  • Microbial organization is complex, involving hierarchical structures from atomic to whole-organism levels.
  • Understanding microbial behavior requires integrating information across diverse spatial and temporal scales.

Purpose of the Study:

  • To develop a multiscale mathematical and computational framework for analyzing microbial systems.
  • To rigorously connect atomic-level descriptions with macroscopic properties of microbes.
  • To provide a foundation for understanding microbial behavior and designing nanostructures.

Main Methods:

  • Developed a multiscale approach based on a hierarchy of variables from N-atom descriptions to order parameters.
  • Analyzed the Liouville equation for probability density across scales.
  • Derived coupled equations for order parameters and N-atom state probability density.
  • Utilized the DeductiveMultiscaleSimulator for demonstrations.

Main Results:

  • Established a rigorous method for information transfer between different space-time scales.
  • Elucidated the interplay of equilibrium and far-from-equilibrium processes in microbial behavior.
  • Demonstrated the framework's utility in analyzing nanocharacterization data and guiding simulations.
  • Enabled systematic searches for free-energy minimizing structures.

Conclusions:

  • The multiscale framework offers a fundamental understanding of microbial behavior.
  • It provides a robust method for analyzing nanocharacterization data.
  • It facilitates computer-aided design of nanostructures for biotechnical and medical applications.
  • Validated with examples including viral particles and lactoferrin.