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Computer Modeling Describes Gravity-Related Adaptation in Cell Cultures

Computer Modeling Describes Gravity-Related Adaptation in Cell Cultures
Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.
- Bryn Mawr College United States
- Beth Israel Deaconess Medical Center United States
- Bryn Mawr College United States
- Harvard University United States
- Beth Israel Deaconess Medical Center United States
Time Factors, Science, Q, R, Colony Count, Microbial, Reproducibility of Results, Sigma Factor, Gene Expression Regulation, Bacterial, Hypergravity, Adaptation, Physiological, Models, Biological, Bacterial Proteins, Flagella, Escherichia coli, Medicine, Computer Simulation, Research Article, Gravitation
Time Factors, Science, Q, R, Colony Count, Microbial, Reproducibility of Results, Sigma Factor, Gene Expression Regulation, Bacterial, Hypergravity, Adaptation, Physiological, Models, Biological, Bacterial Proteins, Flagella, Escherichia coli, Medicine, Computer Simulation, Research Article, Gravitation
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