Transition paths across the EMT landscape are dictated by network logic

Area of Science:

• Cell biology
• Systems biology
• Computational biology

Background:

• Epithelial-mesenchymal transition (EMT) is crucial for development and cancer metastasis.
• Gene regulatory networks (GRNs) control EMT, often exhibiting tristable dynamics.
• The specific logic (e.g., additive vs. multiplicative) governing these GRNs remains unclear.

Purpose of the Study:

• To investigate how different network logic types affect EMT phenotypes in a tristable GRN model.
• To determine which network logic aligns best with experimental observations of EMT regulation.

Main Methods:

• Exploration of additive versus multiplicative logic in a three-node EMT GRN model.
• Stochastic simulations and perturbation analysis.
• Comparison with experimental single-cell data, particularly miR-200 regulation.

Main Results:

• Network logic significantly influences EMT phenotypes and transition paths.
• Multiplicative (AND) logic, unlike additive (OR) logic, predicts miR-200 inhibition destabilizes the epithelial state, aligning with experimental data.
• The choice of logic impacts predictions for factors controlling EMT.

Conclusions:

• Network logic is critical for accurately modeling GRNs with multistability and biological noise.
• Understanding network logic can guide experimental design to infer GRN mechanisms.
• This work provides insights into stabilizing/destabilizing EMT hybrid states relevant to cancer progression.