Neuromuscular junction (NMJ) structural integrity is crucial for transducing motor neuron signals that initiate skeletal muscle contraction. Zebrafish has emerged as a simple and efficient model to study NMJ structural morphology and function in the context of developmental neurobiology and neuromuscular diseases. However, methods to quantify NMJ morphology from voluminous data of NMJ confocal images accurately, rapidly, and reproducibly are lacking. We developed an ImageJ macro called "NMJ Analyser" to automatically and unbiasedly analyse NMJ morphology in zebrafish. From the Z-stack of a zebrafish hemisomite, both presynaptic and postsynaptic fluorescently labeled termini at NMJs are extracted from background signal, with larger clusters of termini being segmented into individual termini using an unbiased algorithm. The program then determines whether each presynaptic terminus is co-localized with a postsynaptic terminus and vice versa, or whether it is orphaned, and tabulates the number of orphan and co-localized pre- and postsynaptic termini. The usefulness of this ImageJ macro plugin will be helpful to quantify NMJ parameters in zebrafish, particularly during development and in disease models of neuromuscular diseases. It can enable high-throughput NMJ phenotypic screens in the drug discovery process for neuromuscular diseases. It could also be further applied to the investigation of NMJ of other developmental systems. NMJ Analyser is available for download at https://github.com/PattenLab/NMJ-Analyser.git.
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