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The optimal strategy balancing risk and speed predicts DNA damage checkpoint override times

Nature Physics volume 18, pages 832–839 (2022)Cite this article

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Abstract

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.

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Fig. 1: Scenarios for the self-replication dynamics of a checkpoint-arrested cell (magenta circle) in a population of cells (white) with generation time T.
Fig. 2: Pictorial representation of checkpoint strategies.
Fig. 3: A DSB sensor (ADH1pr-HOcs-yEVenus-ADH1) reports the presence of a DSB.
Fig. 4: Measurements of late DSB repair statistics and survival rates after checkpoint override.
Fig. 5: Optimal checkpoint theory predicts DDC override times.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Jain, S. et al. A recombination execution checkpoint regulates the choice of homologous recombination pathway during DNA double-strand break repair. Genes Dev. 23, 291–303 (2009).

    Article  Google Scholar 

  2. Rieder, C. L. & Maiato, H. Stuck in division or passing through: what happens when cells cannot satisfy the spindle assembly checkpoint. Dev. Cell. 7, 637–651 (2004).

    Article  Google Scholar 

  3. Morgan, D. O. The Cell Cycle: Principles of Control (New Science Press, 2007).

  4. Curtis, N. L., Ruda, G. F., Brennan, P. & Bolanos-Garcia, V. M. Deregulation of chromosome segregation and cancer. Annu. Rev. Cancer Biol. 4, 257–278 (2020).

    Article  Google Scholar 

  5. Waterman, D. P., Haber, J. E. & Smolka, M. B. Checkpoint responses to DNA double-strand breaks. Annu. Rev. Biochem. 89, 103–133 (2020).

    Article  Google Scholar 

  6. Galgoczy, D. J. & Toczyski, D. P. Checkpoint adaptation precedes spontaneous and damage-induced genomic instability in yeast. Mol. Cell. Biol. 21, 1710–1718 (2001).

    Article  Google Scholar 

  7. SyljuÅsen, R. G. Checkpoint adaptation in human cells. Oncogene 26, 5833–5839 (2007).

    Article  Google Scholar 

  8. Rossio, V., Galati, E. & Piatti, S. Adapt or die: how eukaryotic cells respond to prolonged activation of the spindle assembly checkpoint. Biochem. Soc. Trans. 38, 1645–1649 (2010).

    Article  Google Scholar 

  9. Coutelier, H. et al. Adaptation to DNA damage checkpoint in senescent telomerase-negative cells promotes genome instability. Genes Dev. 32, 1499–1513 (2018).

    Article  Google Scholar 

  10. Coutelier, H. & Xu, Z. Adaptation in replicative senescence: a risky business. Curr. Genet. 65, 711–716 (2019).

    Article  Google Scholar 

  11. Halme, A., Cheng, M. & Hariharan, I. K. Retinoids regulate a developmental checkpoint for tissue regeneration in drosophila. Curr. Biol. 20, 458–463 (2010).

    Article  Google Scholar 

  12. Hackney, J. F., Zolali-Meybodi, O. & Cherbas, P. Tissue damage disrupts developmental progression and ecdysteroid biosynthesis in Drosophila. PLoS ONE 7, e49105 (2012).

  13. Lee, S. E. et al. Saccharomyces Ku70, Mre11/Rad50, and RPA proteins regulate adaptation to G2/M arrest after DNA damage. Cell 94, 399–409 (1998).

    Article  Google Scholar 

  14. Lee, S. E. et al. Arrest, adaptation, and recovery following a chromosome double-strand break in Saccharomyces cerevisiae. Cold Spring Harb. Symp. Quant. Biol. 65, 303–314 (2000).

    Article  Google Scholar 

  15. Aguda, B. D. A quantitative analysis of the kinetics of the G2 DNA damage checkpoint system. Proc. Natl Acad. Sci. USA 96, 11352–11357 (1999).

    Article  ADS  Google Scholar 

  16. Kesseler, K. J., Blinov, M. L., Elston, T. C., Kaufmann, W. K. & Simpson, D. A. A predictive mathematical model of the DNA damage G2 checkpoint. J. Theor. Biol. 320, 159–169 (2013).

    Article  ADS  MATH  Google Scholar 

  17. Bonaiuti, P. et al. Cells escape an operational mitotic checkpoint through a stochastic process. Curr. Biol. 28, 28–37 (2018).

    Article  Google Scholar 

  18. Hopfield, J. J. Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity. Proc. Natl Acad. Sci. USA 71, 4135–4139 (1974).

    Article  ADS  Google Scholar 

  19. Ninio, J. Kinetic amplification of enzyme discrimination. Biochimie 57, 587–595 (1975).

    Article  Google Scholar 

  20. Berg, H. & Purcell, E. Physics of chemoreception. Biophys. J. 20, 193–219 (1977).

    Article  ADS  Google Scholar 

  21. Ehrenberg, M. & Blomberg, C. Thermodynamic constraints on kinetic proofreading in biosynthetic pathways. Biophys. J. 31, 333–358 (1980).

    Article  ADS  Google Scholar 

  22. Freter, R. R. & Savageau, M. A. Proofreading systems of multiple stages for improved accuracy of biological discrimination. J. Theor. Biol. 85, 99–123 (1980).

    Article  ADS  Google Scholar 

  23. Savageau, M. A. & Lapointe, D. S. Optimization of kinetic proofreading: a general method for derivation of the constraint relations and an exploration of a specific case. J. Theor. Biol. 93, 157–177 (1981).

    Article  ADS  MathSciNet  Google Scholar 

  24. McKeithan, T. W. Kinetic proofreading in T-cell receptor signal transduction. Proc. Natl Acad. Sci. USA 92, 5042–5046 (1995).

    Article  ADS  Google Scholar 

  25. Perkins, T. J. & Swain, P. S. Strategies for cellular decision-making. Mol. Syst. Biol. 5, 326 (2009).

    Article  Google Scholar 

  26. Murugan, A., Huse, D. A. & Leibler, S. Speed, dissipation, and error in kinetic proofreading. Proc. Natl Acad. Sci. USA 109, 12034–12039 (2012).

    Article  ADS  Google Scholar 

  27. Lan, G., Sartori, P., Neumann, S., Sourjik, V. & Tu, Y. The energy–speed–accuracy trade-off in sensory adaptation. Nat. Phys. 8, 422–428 (2012).

    Article  Google Scholar 

  28. Sartori, P., Granger, L., Lee, C. F. & Horowitz, J. M. Thermodynamic costs of information processing in sensory adaptation. PLoS Comput. Biol. 10, e1003974 (2014).

  29. Rao, R. & Peliti, L. Thermodynamics of accuracy in kinetic proofreading: dissipation and efficiency trade-offs. J. Stat. Mech. 2015, P06001 (2015).

    Article  MathSciNet  MATH  Google Scholar 

  30. tenWolde, P. R., Becker, N. B., Ouldridge, T. E. & Mugler, A. Fundamental limits to cellular sensing. J. Stat. Phys. 162, 1395–1424 (2016).

    Article  ADS  MathSciNet  MATH  Google Scholar 

  31. Banerjee, K., Kolomeisky, A. B. & Igoshin, O. A. Elucidating interplay of speed and accuracy in biological error correction. Proc. Natl Acad. Sci. USA 114, 5183–5188 (2017).

    Article  ADS  Google Scholar 

  32. Cui, W. & Mehta, P. Identifying feasible operating regimes for early T-cell recognition: the speed, energy, accuracy trade-off in kinetic proofreading and adaptive sorting. PLoS ONE 13, e0202331 (2018).

  33. Wong, F., Amir, A. & Gunawardena, J. Energy-speed-accuracy relation in complex networks for biological discrimination. Phys. Rev. E 98, 012420 (2018).

    Article  ADS  Google Scholar 

  34. Mallory, J. D., Kolomeisky, A. B. & Igoshin, O. A. Trade-offs between error, speed, noise, and energy dissipation in biological processes with proofreading. J. Phys. Chem. B 123, 4718–4725 (2019).

    Article  Google Scholar 

  35. Lee, S. E., Pâques, F., Sylvan, J. & Haber, J. E. Role of yeast SIR genes and mating type in directing DNA double-strand breaks to homologous and non-homologous repair paths. Curr. Biol. 9, 767–770 (1999).

    Article  Google Scholar 

  36. Sandell, L. L. & Zakian, V. A. Loss of a yeast telomere: arrest, recovery, and chromosome loss. Cell 75, 729–739 (1993).

    Article  Google Scholar 

  37. Toczyski, D. P., Galgoczy, D. J. & Hartwell, L. H. CDC5 and CKII control adaptation to the yeast DNA damage checkpoint. Cell 90, 1097–1106 (1997).

    Article  Google Scholar 

  38. Leroy, C. et al. PP2C phosphatases Ptc2 and Ptc3 are required for DNA checkpoint inactivation after a double-strand break. Mol. Cell. 11, 827–835 (2003).

    Article  Google Scholar 

  39. Haber, J. E. A life investigating pathways that repair broken chromosomes. Annu. Rev. Genet. 50, 1–28 (2016).

    Article  Google Scholar 

  40. Chiruvella, K. K., Liang, Z. & Wilson, T. E. Repair of double-strand breaks by end joining. Cold Spring Harb. Perspect. Biol. 5, a012757 (2013).

    Article  Google Scholar 

  41. Wu, D., Topper, L. M. & Wilson, T. E. Recruitment and dissociation of nonhomologous end joining proteins at a DNA double-strand break in Saccharomyces cerevisiae. Genetics 178, 1237–1249 (2008).

    Article  Google Scholar 

  42. Muñoz-Galván, S. et al. Competing roles of DNA end resection and non-homologous end joining functions in the repair of replication-born double-strand breaks by sister-chromatid recombination. Nucleic Acids Res. 41, 1669–1683 (2012).

    Article  Google Scholar 

  43. Balestrini, A. et al. The Ku heterodimer and the metabolism of single-ended DNA double-strand breaks. Cell Rep. 3, 2033–2045 (2013).

    Article  Google Scholar 

  44. Chiruvella, K. K., Liang, Z., Birkeland, S. R., Basrur, V. & Wilson, T. E. Saccharomyces cerevisiae DNA ligase IV supports imprecise end joining independently of its catalytic activity. PLoS Genet. 9, e1003599 (2013).

  45. Liang, Z., Sunder, S., Nallasivam, S. & Wilson, T. E. Overhang polarity of chromosomal double-strand breaks impacts kinetics and fidelity of yeast non-homologous end joining. Nucleic Acids Res. 44, 2769–2781 (2016).

    Article  Google Scholar 

  46. Crow, J. F. & Kimura, M. An Introduction to Population Genetics Theory (The Blackburn Press, 1970).

  47. Orr, H. A. Fitness and its role in evolutionary genetics. Nat. Rev. Genet. 10, 531–539 (2009).

    Article  Google Scholar 

  48. Roux, P., Salort, D. & Xu, Z. Adaptation to DNA damage as a bet-hedging mechanism in a fluctuating environment. R. Soc. Open Sci. 8, 210460 (2021).

    Article  ADS  Google Scholar 

  49. Kelly, J. L. Jr A new interpretation of information rate. Bell Syst. Tech. J. 35, 917–926 (1956).

    Article  MathSciNet  Google Scholar 

  50. Amon, A., Irniger, S. & Nasmyth, K. Closing the cell cycle circle in yeast: G2 cyclin proteolysis initiated at mitosis persists until the activation of G1 cyclins in the next cycle. Cell 77, 1037–1050 (1994).

    Article  Google Scholar 

  51. Kaplun, L., Ivantsiv, Y., Kornitzer, D. & Raveh, D. Functions of the DNA damage response pathway target Ho endonuclease of yeast for degradation via the ubiquitin-26S proteasome system. Proc. Natl Acad. Sci. USA 97, 10077–10082 (2000).

    Article  ADS  Google Scholar 

  52. Dietler, N. et al. A convolutional neural network segments yeast microscopy images with high accuracy. Nat. Commun. 11, 5723 (2020).

    Article  ADS  Google Scholar 

  53. Kaboli, S. et al. Genome-wide mapping of unexplored essential regions in the Saccharomyces cerevisiae genome: evidence for hidden synthetic lethal combinations in a genetic interaction network. Nucleic Acids Res. 42, 9838–9853 (2014).

    Article  Google Scholar 

  54. Haber, J. E. Mating-type genes and MAT switching in Saccharomyces cerevisiae. Genetics 191, 33–64 (2012).

    Article  Google Scholar 

  55. Eapen, V. V., Sugawara, N., Tsabar, M., Wu, W.-H. & Haber, J. E. The Saccharomyces cerevisiae chromatin remodeler Fun30 regulates DNA end resection and checkpoint deactivation. Mol. Cell. Biol. 32, 4727–4740 (2012).

    Article  Google Scholar 

  56. Fudenberg, D. & Tirole, J. Game Theory (MIT Press, 1991).

  57. Bertsekas, D. P. Dynamic Programming and Optimal Control (Athena Scientific, 2017).

  58. Elserafy, M. & El-Khamisy, S. F. Choose your yeast strain carefully: the RAD5 gene matters. Nat. Rev. Mol. Cell Biol. 19, 343–344 (2018).

    Article  Google Scholar 

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Acknowledgements

S.J.R. thanks F. R. Cross, J. E. Haber, F. Zhou and A. Pellicioli for fruitful discussions, as well as E. Alani for the reagents. We thank E. Tenaglia for technical advice and help with strain construction. We thank P. Ehsani for technical advice and reagents. This work was supported by funding from École polytechnique fédérale de Lausanne (EPFL) (S.J.R.) and SNSF Division III project grant 310030_204938 (S.J.R.).

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  1. Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Ahmad Sadeghi, Roxane Dervey, Vojislav Gligorovski, Marco Labagnara & Sahand Jamal Rahi

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Contributions

A.S. performed the FACS and microscopy measurements and was helped with the latter by V.G. and M.L. A.S., R.D. and S.J.R. made the constructs and strains. A.S. analysed the data and was helped by R.D. and S.J.R. A.S. performed the numerical calculations. S.J.R. wrote the manuscript. S.J.R. devised the theory and analytical calculations. All the authors contributed to reviewing and editing the article.

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Correspondence to Sahand Jamal Rahi.

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Sadeghi, A., Dervey, R., Gligorovski, V. et al. The optimal strategy balancing risk and speed predicts DNA damage checkpoint override times. Nat. Phys. 18, 832–839 (2022). https://doi.org/10.1038/s41567-022-01601-3

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