APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022;
Chicago
Session S14: Optimal Trade-Offs Determining Quantitative Biological Parameters
8:00 AM–11:00 AM,
Thursday, March 17, 2022
Room: McCormick Place W-183B
Sponsoring
Unit:
DBIO
Chair: Massimo Vergassola
Abstract: S14.00005 : The optimal checkpoint strategy predicts experimental checkpoint override times
10:24 AM–11:00 AM
Abstract
Presenter:
Sahand Rahi
(Ecole Polytechnique Federale de Lausanne)
Author:
Sahand Rahi
(Ecole Polytechnique Federale de Lausanne)
Why biological quality-control systems fail is often mysterious. Specifically, checkpoints in yeast and animals are overridden after prolonged arrests allowing self-replication to proceed despite the continued presence of errors. Although critical for the organism, checkpoint override is not understood quantitatively by experiment or theory. To uncover laws governing the dynamics of error-correction systems, we derived a general theory of optimal checkpoint strategies, balancing the trade-off between risk and self-replication opportunity. We show that the mathematical problem of finding the optimal strategy maps onto the question of calculating the optimal absorbing boundary for a random walk, which we show can be solved efficiently recursively. The theory predicts the optimal override time without free parameters based on the statistics i) of error correction and ii) of survival. We applied the theory experimentally to the DNA damage checkpoint in budding yeast, an intensively researched model for eukaryotic checkpoints, whose override is nevertheless not understood quantitatively, functionally, or at the system level. Using a novel fluorescent construct which allowed cells with DNA breaks to be isolated by flow cytometry, we quantified i) the probability distribution of repair for a double-strand DNA break (DSB), including for the critically important, rare events deep in the tail of the distribution and ii) the survival probability after override. Based on these two measurements, the optimal checkpoint theory predicted remarkably accurately the DNA damage checkpoint override times as a function of DSB numbers, which we also measured for the first time precisely. Thus, a first-principles calculation uncovered hitherto hidden patterns underlying the highly noisy checkpoint override process. The universal nature of the balance between risk and self-replication opportunity is in principle relevant to many other systems, suggesting further applications.