New techniques allow detailed visualization of DNA repair machinery


Each of the billions of cells that make up the human body suffers from more than 10,000 DNA damage every day. These injuries would be catastrophic if cells were unable to repair them, but very delicate machinery that detects and repairs genetic damage is at work to prevent DNA mutations and diseases such as cancer.

With the help of machine learning applied to high-throughput microscopy, among other techniques, researcher Bárbara Martínez, member of the Metabolism and Cell Signaling group led by Alejo Efeyan at the National Cancer Research Center (CNIO), with Raul Mostoslavsky and his team from Massachusetts General Hospital (Boston, USA), managed to visualize this DNA repair machinery in detail and identified new repair proteins. These results, designed in Boston, developed between Boston and Madrid, and published this week in Cell reports, could help develop new therapies against cancer.

As soon as there is DNA damage, such as a DNA double strand break, the cell activates a mechanism called the DNA damage response which acts like a “call to emergency services,” explains Martinez. Proteins quickly bind to damaged DNA to send alarm signals, which will be recognized by other proteins specializing in repairing damage.

The goal of chemotherapy is to kill tumor cells by inducing DNA damage, which causes cancer cells to collapse and die.

By knowing how DNA damage occurs and how it is repaired, we will learn more about how cancer grows and how we can fight it. Any New Discovery In DNA Repair Will Help Develop Better Cancer Therapies, While Protecting Our Healthy Cells. “

Bárbara Martínez, researcher and member of the Metabolism and Cell Signaling group, Centro Nacional de Investigaciones Oncológicas

The researchers developed a new methodology which, using a machine learning analysis method devised by the Confocal Unit of the CNIO, allowed this process to be analyzed with a level of detail and precision never before achieved. . “Until now, a limiting factor in tracking DNA repair kinetics has been the inability to process and analyze the amount of data generated from images taken by the microscope.”

The researchers used high-throughput microscopy which allows the acquisition of thousands of images of cells after induction of genetic damage. In the first phase, they introduced over 300 different proteins into cells and assessed in a single experiment whether they interfered with DNA repair over time. This technique has led to the discovery of nine new proteins involved in DNA repair.

But the authors decided to take it a step further and visually monitored the 300 proteins after generating genetic damage. To do this, they have adapted a classic technique of micro-irradiation of DNA – which damages DNA with a UV laser – to be used for the first time on a large scale and to analyze the behavior of the 300 proteins studied.

“We saw that many proteins adhered to damaged DNA, and others did the exact opposite: they moved away from DNA damage. It is a common feature of DNA repair proteins that they bind to or pull out of damaged DNA, to enable repair proteins to be recruited to the lesion. Both phenomena are relevant “.

One of the proteins discovered is PHF20. The authors showed that this protein moves away from lesions within seconds of damage to facilitate recruitment of 53BP1, a protein essential for DNA repair. Cells without PHF20 cannot repair their DNA properly and are more sensitive to irradiation than normal cells, indicating that PHF20 is important for DNA repair.

These technologies offer new opportunities to study DNA repair and manipulation. “One advantage is that both platforms are very versatile and can be used to discover new genes or chemical compounds that affect DNA repair. We have evaluated hundreds of proteins in a minimum of time using techniques allowing direct visualization of DNA repair. “


Journal reference:

Martinez-Pastor, B., et al. (2021) Evaluation of the kinetics and recruitment of DNA repair factors using high content screens. Cell reports.


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