Computer-assisted motion analysis of fluorescent tubulin dynamics in the nerve growth cone

Nerve growth is a complex process whereby neurons extend projections called neurites in an attempt to locate appropriate synaptic partners. The process of neurite outgrowth is mediated by a structure at the neurite's terminus called the growth cone, which senses the local chemical and physical environment and migrates in response to it. A key process underlying growth cone advance is the self-assembly of microtubules from tubulin subunits within the growth cone. Previously, we reported that microtubule and growth cone advance exhibit a close, nonrandom coupling between the two motions. Here, we describe in detail the method used to quantitatively process the digital images obtained by fluorescence videomicroscopy for subsequent statistical analysis by time series methods. The method, a combination of contrast enhancement, convolution, thresholding, and manual tracing from a computer screen, was implemented using NIH image macros and a C language program to quantify the complex morphology characteristic of both growth cones and their microtubule arrays. The approach can be applied more generally to the simultaneous analysis of cellular and subcellular motion as observed by optical videomicroscopy, and quantitatively correlating their dynamics.