FocAn

FocAn performs automated three-dimensional analysis of γH2AX (phosphorylated histone H2AX) foci to quantify DNA double-strand breaks (DSBs) from confocal fluorescence microscopy z-stacks.

Key Features:

• 3D γH2AX foci analysis: Detects and quantifies γH2AX nuclear foci in three dimensions to assess DSBs.
• Z-image stack processing: Operates on confocal fluorescence microscopy z-image stacks as input data.
• Nucleus identification: Automatically recognizes individual cell nuclei in 3D and evaluates total foci per nucleus.
• Foci detection and separation: Detects γH2AX foci in three dimensions and identifies overlapping foci.
• Segmentation algorithm: Uses sequences of auto local thresholding combined with watershed segmentation for nucleus and foci recognition.
• High-density quantification: Provides accurate recognition and quantification at high DSB densities up to approximately 200 DSBs per nucleus.
• No additional nuclear staining required: Capable of performing nucleus and foci analysis without supplementary nuclei staining.
• ImageJ implementation: Implemented as an ImageJ-based plugin for image processing and analysis.
• Validation: Results were validated against FoCo and manual counting in fluorescence-labeled γH2AX experiments on glioblastoma cell lines irradiated with 2 Gy and allowed up to 24 hours for repair.

Scientific Applications:

• Quantification of DNA-DSBs: Quantifies DNA double-strand breaks using γH2AX immunofluorescence foci counts.
• Assessment of DSB induction and repair kinetics: Enables analysis of DSB induction and repair dynamics after ionizing radiation or genotoxic agents, including time-course analysis up to 24 hours post-irradiation.
• Large-scale fluorescence image analysis: Facilitates automated detection and quantification across large datasets of fluorescence images from confocal microscopy.
• Method validation and benchmarking: Supports comparison and benchmarking of image-based DSB quantification methods against FoCo and manual counting.

Methodology:

Processes confocal fluorescence microscopy z-image stacks and performs nucleus identification and foci detection using sequences of auto local thresholding combined with watershed segmentation; implemented as an ImageJ-based plugin.