From cartoons to quantitative models in Golgi transport

Area of Science:

• Cell Biology
• Computational Biology
• Biophysics

Background:

• Cell biology increasingly relies on quantitative and formal approaches.
• Existing mathematical models of Golgi self-organization and transport are limited.
• Static diagrams of the Golgi apparatus fail to capture its dynamic nature.

Purpose of the Study:

• To translate static schematic representations of Golgi trafficking into a dynamic, quantitative model.
• To develop a flexible and multiscale framework for analyzing intracellular transport.
• To provide a computational tool for investigating Golgi function and related cellular processes.

Main Methods:

• Development of an agent-based model using the Repast platform.
• Translation of schematic Golgi trafficking diagrams into model rules.
• Integration with COPASI for modeling complex molecular interactions and reactions.

Main Results:

• The agent-based model successfully simulates the dynamic interplay of Golgi cisternae and vesicles.
• Quantitative predictions regarding Golgi stability and the transport of soluble and membrane-associated cargoes are generated.
• The model demonstrates the feasibility of incorporating complex molecular networks and reactions.

Conclusions:

• The described strategy offers a straightforward, adaptable, and multiscale method for analyzing Golgi transport.
• Simulations can elucidate transport mechanisms and integrate trafficking complexity into other dynamic organelle processes.
• Implicit rules in trafficking schematics can be leveraged to build dynamic models with experimentally verifiable quantitative outputs.