Organelle landscape analysis using a multi-parametric particle-based method

Abstract

Organelles have unique structures and molecular compositions for their functions and have been classified accordingly. However, many organelles are heterogeneous and in the process of maturation and differentiation. Because traditional methods have a limited number of parameters and spatial resolution, they struggle to capture the heterogeneous landscapes of organelles. Here, we present a method for multi-parametric particle-based analysis of organelles. After disrupting cells, fluorescence microscopy images of organelle particles labeled with six to eight different organelle markers were obtained, and their multi-dimensional data were represented in intuitive two-dimensional UMAP (uniform manifold approximation and projection) spaces. This method enabled visualization of landscapes of seven major organelles as well as the transitional states of endocytic organelles directed to the recycling and degradation pathways. Furthermore, endoplasmic reticulum-mitochondria contact sites were detected in these maps. Our proposed method successfully detects a wide array of organelles simultaneously, enabling the analysis of heterogeneous organelle landscapes.