Multi-Channel Colocalization Analysis and Visualization of Viral Proteins in Fluorescence Microscopy Images

Multi-Channel Colocalization Analysis and Visualization of Viral Proteins in Fluorescence Microscopy Images

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Automatic analysis of colocalizing biological structures in multi-channel fluorescence microscopy images is an important task to quantify and understand biological processes at high spatial-temporal resolution.Here, we introduce a software suite for colocalization analysis of spot-like objects in multi-channel fluorescence microscopy images.The software suite consists of ColocQuant and ColocJ, and is easy to use for biologists.

ColocQuant is a Python-based software with graphical user interface to quantify colocalization of particles in two or three channels.Object-based colocalization is performed by an efficient multi-dimensional graph-based $k$ -d-tree approach, which determines nearest neighbors involved in double BLACK CAVIAR 12 IN 1 MULTI ACTION HAIR C or triple colocalization.ColocJ enables efficient and intuitive visualization of the color composition of colocalizations by a Maxwell color triangle and a color ribbon.

Colocalization information can be visualized for an entire image or a selected region-of-interest.In addition, global statistics of the particle intensity, particle size, and the number of colocalizations over time are provided.The colocalization Hoodies/Fleece analysis results can be exported and used in other software.

We illustrate the application of our software suite for multi-channel live cell fluorescence microscopy image sequences of viral proteins in hepatitis C virus infected cells.We performed two-channel and three-channel colocalization analysis.