Nanometer resolution tracking and modeling of bidirectional axonal cargo transport

Survival and function of neurons depend critically on bidirectional transport of essential cargoes within their axons. To study related molecular mechanisms, we developed an automated single particle tracking method that combines nanometer resolution detection of cargo positions with kymograph-based multiple hypothesis tracking of cargo motion for precise and complete recovery of cargo trajectories. Experiments confirmed that the method can precisely track vesicles in dense axonal traffic of Drosophila motor neurons at 10~20 nm resolution and reliably resolve their trajectories in events of crossing, merging, and splitting. Recovered cargo trajectories were statistically analyzed to identify motion patterns and computationally represented using hidden Markov models to characterize behavior changes. Together, these tools allowed us to reliably detect and measure subtle changes in dynamics of axonal transport and to discover previously unknown axonal transport properties.