ExoJ: an ImageJ2/Fiji plugin for automated spatiotemporal detection and analysis of exocytosis

Abstract

Exocytosis is a dynamic physiological process that enables the release of biomolecules to the surrounding environment via the fusion of membrane compartments to the plasma membrane. Understanding its mechanisms is crucial, as defects can compromise essential biological functions. The development of pH-sensitive optical reporters alongside fluorescence microscopy enables the assessment of individual vesicle exocytosis events at the cellular level. Manual annotation represents, however, a time-consuming task, prone to selection biases and human operational errors. Here, we introduce ExoJ, an automated plugin based on ImageJ2/Fiji. ExoJ identifies user-defined genuine populations of exocytic events, recording quantitative features including intensity, apparent size and duration. We designed ExoJ to be fully user-configurable, making it suitable to study distinct forms of vesicle exocytosis regardless of the imaging quality. Our plugin demonstrates its capabilities by showcasing distinct exocytic dynamics among tetraspanins and vesicular SNAREs protein reporters. Assessment of performance on synthetic data demonstrated ExoJ is a robust tool, capable to correctly identify exocytosis events independently of signal-to-noise ratio conditions. We propose ExoJ as a standard solution for future comparative and quantitative studies of exocytosis.