Robust transport by multiple motors with nonlinear force-velocity relations and stochastic load sharing

Area of Science:

• Cell biology
• Biophysics
• Molecular motors

Background:

• Processive molecular motors are crucial for intracellular transport.
• Understanding the mechanics of multiple motors working together is essential for cell biology.
• Previous models have not fully captured nonlinear force-velocity relations and stochastic load sharing.

Purpose of the Study:

• To investigate the effects of nonlinear force-velocity relations and stochastic load sharing on multiple motor transport.
• To determine how these factors influence the mechanical properties and robustness of cargo transport.
• To compare the behavior of multiple motors to single-motor transport and analytical mean-field theories.

Main Methods:

• Computational modeling and simulations were used to study multiple motor transport.
• The models incorporated nonlinear force-velocity relationships and stochastic load sharing.
• Simulations analyzed the effects of varying motor numbers, cargo-motor link compliance, and external loads.

Main Results:

• Nonlinear and stochastic effects provide robustness in transport by 2-3 motors, making it insensitive to cargo-motor link compliance.
• Increasing the number of motors beyond a small amount (2-3) does not improve transport rate against moderate loads.
• For motor numbers greater than 4, motor correlations become negligible, aligning with mean-field theory predictions.
• Effective cargo diffusion under load increases significantly (by an order of magnitude) with multiple motors compared to a single motor.
• Stochastic effects cause substantial velocity dispersion in the 'tug-of-war' dynamics of opposing motors.

Conclusions:

• The interplay of nonlinear forces and stochasticity ensures robust intracellular cargo transport by small teams of molecular motors.
• While increasing motor numbers beyond a few offers diminishing returns for speed, multiple motors dramatically enhance effective diffusion.
• Simulations highlight the significant role of stochasticity in generating velocity variations during motor-driven transport.