Neurofilaments are the intermediate filaments of neurons and are the most abundant structure of the neuronal cytoskeleton. Once synthesized within the cell body they are then transported throughout the axon along microtubule tracks, driven by the molecular motors kinesin and dynein. This movement is characterized by long pauses with no movement interrupted by infrequent bouts of rapid movement, resulting in an aggregate dense cytoskeletal structure, which serves to regulate an axon’s shape and size. Curiously, the modulated kinetics of these polymers produces a very regular, yet non-uniform, morphology in myelinated axons which are composed of discretely spaced myelin-ensheathed segments that are separated by short constricted regions called ”nodes of Ranvier”. This unique design optimizes the conduction velocity of myelinated axons at minimal fiber size. Hence, neurofilaments regulate the axon caliber to optimize neuron function.
The goal of this dissertation is to investigate the motile mechanism of neurofilament transport as well as the resulting electrophysiological eff ects that follow. We start by examining highly time-resolved kymograph images generated from recorded neurofilament movement via epifluorescence microscopy. Using kymograph analysis, edge detection algorithms, and pixel smoothing tactics, neurofilament trajectories are extracted and used to obtain statistical distributions for the characteristics of how these filaments move within cells. The results suggest that the observed intermittent and bidirectional motions of these filaments might be explained by a model in which dynein and kinesin motors attach to a single neurofilament cargo and interact through mechanical forces only (i.e. a ”tug-of-war” model). We test this hypothesis by developing two discrete-state stochastic models for the kinetic cycles of kinesin and dynein, which are then incorporated into a separate stochastic model that represents the posed tug-of-war scenario. We then systematically vary the number of motors in the model and attempt to identify those combinations of motors that show an agreement with the motility characteristic found from the above mentioned kymographs. By pruning the modeled data in accordance with the experimental results, our model can render an estimate of how many motors are attached to the cargo during transport. The model predicts that, on average, the total number of active motors on each neurofilament is relatively small and relatively independent of polymer length, which suggests that the motors may not be distributed uniformly along the filaments. Finally, we develop a model to explore the physiological function of axon morphology sculpted by neurofilament kinetics. Specifically, nodal constrictions are generated by slowing of neurofilaments in the internodal domain (Monsma et al., 2014), but the physiological function of these constrictions is unknown. To address this, we develop a computational model to investigate the eff ect of nodal constrictions on the axonal conduction velocity. For a fixed number of ion channels, we find that there is an optimal extent of nodal constriction which minimizes the internodal axon caliber that is required to achieve a given target conduction velocity, and we show that this is sensitive to the precise geometry of the axon and myelin sheath in the flanking paranodal regions. Thus axonal constrictions appear to be a biological adaptation that serves to minimize axonal volume, thereby maximizing the spatial and metabolic efficiency of these processes.