A novel method for quantified, superresolved, three-dimensional colocalisation of isotropic, fluorescent particles

Area of Science:

• Bioimage Informatics
• Cell Biology
• Microscopy

Background:

• Colocalisation analysis is crucial for characterizing cellular phenotypes by identifying overlapping subcellular structures.
• Quantifying colocalisation in 3D fluorescence microscopy datasets presents significant challenges.

Purpose of the Study:

• To develop a novel bioimage informatics approach for quantifying colocalisation of round, isotropic structures in 3D fluorescence microscopy.
• To provide a robust and efficient method for analyzing protein-protein interactions and cellular phenotypes.

Main Methods:

• Algorithm identifies isotropic fluorescent particles in 3D datasets based on relative brightness.
• Determines centroids of identified spots and checks for corresponding objects in different colour channels.
• Generates 3D distance maps and histograms to quantify colocalisation distances.

Main Results:

• Successfully quantified sparse colocalisation of human leukocyte antigen receptors in choriocarcinoma cells.
• Demonstrated the method's applicability to various isotropic subcellular structures like vesicles and chloroplasts.
• Achieved super-resolved, object-based colocalisation maps indicating potential protein-protein interactions.

Conclusions:

• The developed method offers a simple, robust, and fast approach for 3D colocalisation analysis.
• Provides valuable insights into protein-protein interactions of fluorescent particles.
• Enables accurate characterization of cellular phenotypes through precise colocalisation quantification.