SpatTrack: An Imaging Toolbox for Analysis of Vesicle Motility and Distribution in Living Cells

作者：Lund Frederik W; Jensen Maria Louise V; Christensen Tanja; Nielsen Gitte K; Heegaard Christian W; Wustner Daniel^*

来源：Traffic, 2014, 15(12): 1406-1429.

DOI：10.1111/tra.12228

• Bayesian
• cholesterol efflux
• convex hull
• lysosome
• Monte Carlo
• Niemann Pick disease
• particle tracking
• pattern analysis
• radial distribution function
• spatial statistics

The endocytic pathway is a complex network of highly dynamic organelles, which has been traditionally studied by quantitative fluorescence microscopy. The data generated by this method can be overwhelming and its analysis, even for the skilled microscopist, is tedious and error-prone. We developed SpatTrack, an open source, platform-independent program collecting a variety of methods for analysis of vesicle dynamics and distribution in living cells. SpatTrack performs 2D particle tracking, trajectory analysis and fitting of diffusion models to the calculated mean square displacement. It allows for spatial analysis of detected vesicle patterns including calculation of the radial distribution function and particle-based colocalization. Importantly, all analysis tools are supported by Monte Carlo simulations of synthetic images. This allows the user to assess the reliability of the analysis and to study alternative scenarios. We demonstrate the functionality of SpatTrack by performing a detailed imaging study of internalized fluorescence-tagged Niemann Pick C2 (NPC2) protein in human disease fibroblasts. Using SpatTrack, we show that NPC2 rescued the cholesterol-storage phenotype from a subpopulation of late endosomes/lysosomes (LE/LYSs). This was paralleled by repositioning and active transport of NPC2-containing vesicles to the cell surface. The potential of SpatTrack for other applications in intracellular transport studies will be discussed.

• 出版日期2014-12