UC Irvine

Organelles represent the scale of organization immediately below that of the cell itself, and their composition, size, and number are tailored to their function. Monitoring the size and number of organelles in live cells is relevant for many applications but can be challenging due to their highly heterogeneous properties. Image correlation spectroscopy is a well-established analysis method capable of extracting the average size and number of particles in images. However, when image correlation spectroscopy is applied to a highly heterogeneous system, it can fail to retrieve, from a single correlation function, the characteristic size and the relative amount associated to each subspecies. Here, we describe a fast, unbiased, and fit-free algorithm based on the phasor analysis of multiple local image correlation functions, capable of mapping the sizes of elements contained in a heterogeneous system. The method correctly provides the size and number of separate subspecies, which otherwise would be hidden in the average properties of a single correlation function. We apply the method to quantify the spatial and temporal heterogeneity in the size and number of intracellular vesicles formed after endocytosis in live cells.