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Updated: May 19, 2026

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Visualizing and Quantifying Endonuclease-Based Site-Specific DNA Damage
Published on: August 21, 2021
Imaging Approach to DNA Damage Induction and Quantification.
1Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA. mg2363@rutgers.edu.
Methods in Molecular Biology (Clifton, N.J.)
|May 18, 2026
Summary
This study presents a reliable immunofluorescence workflow for analyzing DNA double-strand breaks (DSBs) in fixed cells. It offers a practical solution for quantifying DNA damage when live-cell methods are insufficient.
Area of Science:
- Cell biology
- Molecular biology
- Microscopy
Background:
- Immunofluorescence microscopy provides superior image quality for fixed cells compared to live-cell imaging.
- Quantifying DNA damage, particularly DNA double-strand breaks (DSBs), is challenging in living cells due to a lack of reliable methods.
Purpose of the Study:
- To describe a comprehensive workflow for inducing DNA damage in cell culture.
- To detail methods for fixation, staining, and analysis of DNA double-strand breaks (DSBs) using immunofluorescence.
- To provide troubleshooting guidance for image segmentation and analysis.
Main Methods:
- Induction of DNA damage in cultured cells.
- Standard cell fixation and immunofluorescence staining protocols.
- Image analysis techniques for quantifying DNA double-strand breaks (DSBs).
- Troubleshooting common issues in image segmentation and analysis.
Main Results:
- A robust workflow for DNA damage induction and analysis was established.
- High signal-to-noise imaging and accurate quantification of DNA double-strand breaks (DSBs) were achieved.
- Common challenges in image segmentation and analysis were addressed with practical solutions.
Conclusions:
- The described immunofluorescence workflow is effective for analyzing DNA double-strand breaks (DSBs) in fixed cells.
- This method offers a reliable alternative for DNA damage quantification when live-cell approaches are limited.
- The provided troubleshooting tips enhance the reproducibility and success rate of image analysis.

