Bistability and Bimodal Distributions in Gene Regulation
Author Information
Author(s): Shu Che-Chi, Chatterjee Anushree, Dunny Gary, Hu Wei-Shou, Ramkrishna Doraiswami
Primary Institution: Purdue University
Hypothesis
Bistability is neither sufficient nor necessary for bimodal distributions in a population of cells.
Conclusion
The study demonstrates that bimodal distributions can arise from population heterogeneity without requiring bistability.
Supporting Evidence
- Bimodal distributions can arise from cells without bistability.
- Population balance models account for interactions between cells and their environment.
- Stochastic gene regulation can lead to different behaviors in a population of cells.
Takeaway
This study shows that cells in a group can behave differently based on their environment, and that having two stable states isn't needed for different groups of cells to show varied behaviors.
Methodology
The study uses a population balance model to simulate gene expression in a population of cells, incorporating stochastic gene regulation.
Potential Biases
The single-cell model may lead to biased predictions by ignoring interactions between cells and their environment.
Limitations
The model assumes constant extracellular pheromone concentration and does not account for all possible variations in plasmid distribution among daughter cells.
Digital Object Identifier (DOI)
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