Back

Optogenetic tripwires resolve models of how cells count DNA breaks

Labagnara, M.; Gligorovski, V.; Rahi, S. J.

2025-11-01 molecular biology
10.1101/2025.10.31.685943 bioRxiv
Show abstract

DNA end resection is a critical step in DNA damage repair and activation of the DNA damage checkpoint (DDC). To date, resection has been studied primarily in bulk cell populations. However, single-cell analyses are essential for uncovering cell-to-cell variability and can powerfully support or contradict system-level models where traditional genetic perturbations face limitations. We present a single-cell method to quantify resection by integrating an optogenetic expression system at defined distances from an inducible double-strand DNA break (DSB) site in the budding yeast genome. Using this system, we test competing, unresolved models of how the DDC counts DSBs and determines when to override the checkpoint. Current models propose that the extent of DNA damage is signaled by resection, either through liberated single-stranded DNA (ssDNA) or proteins bound along the non-resected strand. Although mechanistically plausible and widely known, these models rely on inconclusive evidence from gene knockout studies. An alternative hypothesis is that the DDC counts DSBs digitally, using factors located at 3 break ends or at ss/dsDNA junctions. Here, we leverage natural cell-to-cell variability in resection rates as an intrinsic perturbation, avoiding the limitations of prior genetic approaches. Our single-cell data challenge models in which DNA damage is inferred from the extent or rate of resection or from proteins bound along resected DNA. To explore alternative mechanisms, we investigated DDC proteins localized at 3 DSB ends or ss/dsDNA boundaries. By dynamically depleting candidate proteins after checkpoint arrest, we identified ss/dsDNA boundary proteins Ddc1, Dpb11, and Rad9 as essential for DDC maintenance and promising candidates for a cascade that acts as a digital DSB counter. Our findings demonstrate that quantitative, system-level single-cell approaches, coupled with dynamic perturbations, can resolve fundamental questions in DNA repair and checkpoint signaling.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.