Modeling material transport regulation and traffic jam in neurons using PDE-constrained optimization

Area of Science:

• Computational neuroscience
• Cell biology
• Biophysics

Background:

• Intracellular transport is vital for neuronal survival and function.
• Disruptions in neuronal transport are linked to neurodegenerative diseases.
• Understanding neuronal transport regulation is crucial.

Purpose of the Study:

• To develop a novel optimization model simulating intracellular material transport in complex neuronal geometries.
• To investigate the traffic regulation mechanisms that prevent transport jams.
• To analyze how neurons manage transport issues.

Main Methods:

• Developed a partial differential equation (PDE)-constrained optimization model for molecular-motor-assisted transport.
• Utilized isogeometric analysis (IGA) to solve the model in complex neuronal structures.
• Simulated traffic jams by varying parameters like microtubule (MT) density and structure.

Main Results:

• Successfully modeled and explained traffic jam formation caused by reduced MTs and MT swirls.
• Demonstrated the model's effectiveness in simulating transport in both healthy and abnormal neurons.
• Identified geometry and MT structure as critical factors for optimal intracellular transport.

Conclusions:

• The developed optimization model accurately simulates neuronal intracellular transport.
• The model provides insights into the causes of traffic jams in neurodegenerative conditions.
• Neuronal geometry and microtubule organization are key determinants of efficient transport.