Agent-Based Models Predict Emergent Behavior of Heterogeneous Cell Populations in Dynamic Microenvironments
Computational models are most impactful when they explain and characterize biological phenomena that are non-intuitive, unexpected, or difficult to study experimentally. Countless equation-based models have been built for these purposes, but we have yet to realize the extent to which rules-based models offer an intuitive framework that encourages computational and experimental collaboration. We develop ARCADE, a multi-scale agent-based model to interrogate emergent behavior of heterogeneous cell agents within dynamic microenvironments and demonstrate how complexity of intracellular metabolism and signaling modules impacts emergent dynamics. We perform in silico case studies on context, competition, and heterogeneity to demonstrate the utility of our model for gaining computational and experimental insight. Notably, there exist (i) differences in emergent behavior between colony and tissue contexts, (ii) linear, non-linear, and multimodal consequences of parameter variation on competition in simulated co-cultures, and (iii) variable impact of cell and population heterogeneity on emergent outcomes. Our extensible framework is easily modified to explore numerous biological systems, from tumor microenvironments to microbiomes.
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AUTHORS (2)
CATEGORIES
- Bioprocessing, Bioproduction and Bioproducts
- Industrial Biotechnology Diagnostics (incl. Biosensors)
- Industrial Microbiology (incl. Biofeedstocks)
- Industrial Molecular Engineering of Nucleic Acids and Proteins
- Industrial Biotechnology not elsewhere classified
- Medical Biotechnology Diagnostics (incl. Biosensors)
- Biological Engineering
- Regenerative Medicine (incl. Stem Cells and Tissue Engineering)
- Medical Biotechnology not elsewhere classified
- Agricultural Marine Biotechnology
- Biomaterials
- Biomechanical Engineering
- Biotechnology
- Biomarkers
- Biomedical Engineering not elsewhere classified
- Genetic Engineering
- Synthetic Biology
- Bioremediation
- Medical Molecular Engineering of Nucleic Acids and Proteins