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Precise control of endosome-lysosome trafficking is indispensable for regulating neuronal function. Notably, the dynamic movements of these vesicles are a key factor underlying the regulation of neuronal morphology, development, and survival. Defects in this system cause severe neuronal disorders1,2. The molecular mechanisms that link vesicle trafficking to neuronal diseases are considered complicated, and several groups have sought to examine this relevance. For instance, it has been reported that perturbed late endosome motility is significantly associated with Niemann-Pick C disease3, an inherited neurodegenerative disorder caused by lysosome defects. Another example is a mutation in a lysosomal Ca2+ channel, trpml1, which impairs lysosomal motility, resulting in lysosomal storage diseases4,5,6. Our group has reported that dysregulation of PtdIns(3,5)P2 turnover suppresses endosome and lysosome motility in neurons, leading to an increase in vulnerability to the stress response7,8. The metabolic regulation of PtdIns(3,5)P2, which mostly localizes on late endosomes and lysosomes, plays an important role in a wide variety of cellular functions, including vesicle trafficking and fusion-fission processes9,10. Since impaired PtdIns(3,5)P2 turnover causes severe neurodegeneration11,12, the aberrant regulation of endosome-lysosome motility could be a key factor for understanding the pathogenesis of neurodegeneration. An investigation of the molecular mechanisms that underlie vesicle motility may thus provide promising clues that can deepen our understanding of several neuronal disorders.
In this paper, we introduce a valuable method to quantify vesicle motility in neurons using a free software package called Manual Tracking. The aim was to develop a fast quantification method to analyze vesicle motility. This quantification is directed through a standard approach of clicking on a reference point in each frame of a time-lapse movie. The use of the Manual Tracking software makes this approach quite simple and of broad utility, unlike other applications. Furthermore, this approach is also applicable to other cells, such as glial cells. Although this method is primitive, it can be applied to various analyses, including of cellular motility and morphological change. For instance, after defining a reference point across a sequence of images, information on the positions of the reference points and the time at each position can be extracted from sequential images using data analysis and image-processing software. Taken together, this method is simple but powerful and contributes to the development of improved efficiency in studies based on membrane trafficking, such as those examining endosome-lysosome function.