Publication
Cells have built-in mechanisms for checking for errors during replication, but these checkpoints can slow down reproduction. A theory accounting for optimal checkpoint strategies is presented and tested against observations in budding yeast. Checkpoints arrest biological processes, allowing time for error correction. The phenomenon of checkpoint override during cellular self-replication is biologically critical, but it currently lacks a quantitative, functional or system-level understanding. To uncover fundamental laws governing error correction systems, we derived a general theory of optimal checkpoint strategies, balancing the trade-off between risk and self-replication speed. Mathematically, the problem maps onto the optimization of an absorbing boundary for a random walk. We applied the theory to the DNA damage checkpoint in budding yeast, an intensively researched model checkpoint. Using novel reporters for double-strand DNA breaks (DSBs), we first quantified the probability distribution of DSB repair in time including rare events; second, we determined the survival probability after override. With these inputs, the optimal theory remarkably accurately predicted override times as a function of DSB numbers, which we precisely measured for the first time. Thus, a first-principles calculation revealed undiscovered patterns underlying highly noisy override processes. Our multi-DSB measurements revise well-known past results and show that override is more general than previously thought.