A new view of axon growth and guidance grounded in the stochastic dynamics of actin networks

Abstract

The mechanism of axon growth and guidance is a core, unsolved problem in neuroscience and cell biology. For nearly three decades, our view of this process has largely been based on deterministic models of motility derived from studies of neurons cultured in vitro on rigid substrates. Here, we suggest a fundamentally different, inherently probabilistic model of axon growth, one that is grounded in the stochastic dynamics of actin networks. This perspective is motivated and supported by a synthesis of results from live imaging of a specific axon growing in its native tissue in vivo , together with single-molecule computational simulations of actin dynamics. In particular, we show how axon growth arises from a small spatial bias in the intrinsic fluctuations of the axonal actin cytoskeleton, one that produces net translocation of the axonal actin network by differentially modulating local probabilities of network expansion versus compaction. We discuss the relationship between this model and current views of axon growth and guidance mechanism and demonstrate how it offers explanations for various longstanding puzzles in this field. We further point out the implications of the probabilistic nature of actin dynamics for many other processes of cell morphology and motility.

The geometry of photopolymerized topography influences neurite pathfinding by directing growth cone morphology and migration

“…By using the precision and reproducibility enabled by topographically engineered cues, we can accurately define neurite turning behavior in response to a range of angles, as well as various amplitudes of these angled microfeatures. This reproducible system is essential for studying neurite turning since neurite outgrowth and growth cone migration exhibit a wide variation of behavior across a population of neurons [39,40]. Clarifying the consistency of how regenerating neurites can be effectively guided and determining what is the innate variation for this behavior are essential for informing the design of neural growth [41].…”