Semi-automated quantification of filopodial dynamics

Abstract

Cellular motility underlies critical physiological processes including embryogenesis, metastasis and wound healing. Nerve cells undergo cellular migration during development and also extend neuronal processes for long distances through a complex microenvironment to appropriately wire the nervous system. The growth cone is a highly dynamic structure that responds to extracellular cues by extending and retracting filopodia and lamellipodia to explore the microenvironment and to dictate the path and speed of process extension. Neuronal responses to a myriad of guidance cues have been studied biochemically, however, these approaches fail to capture critical spatio-temporal elements of growth cone dynamics. Live imaging of growth cones in culture has emerged as a powerful tool to study growth cone responses to guidance cues but the dynamic nature of the growth cone requires careful quantitative analysis. Space time kymographs have been developed as a tool to quantify lamellipodia dynamics in a semi-automated fashion but no such tools exist to analyze filopodial dynamics. In this work we present an algorithm to quantify filopodial dynamics from cultured neurons imaged by time-lapse fluorescence microscopy. The method is based on locating the end tips of filopodia and tracking their locations as if they were free-moving particles. The algorithm is a useful tool and should be broadly applicable to filopodial tracking from multiple cell types.