Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Coupling phenotypic persistence to DNA damage increases genetic diversity in severe stress

Abstract

Mutation rate balances the need to protect genome integrity with the advantage of evolutionary innovations. Microorganisms increase their mutation rate when stressed, perhaps addressing the growing need for evolutionary innovation. Such a strategy, however, is only beneficial under moderate stresses that allow cells to divide and realize their mutagenic potential. In contrast, severe stresses rapidly kill the majority of the population with the exception of a small minority of cells that are in a phenotypically distinct state termed persistence. Although persisters were discovered many decades ago, the stochastic event triggering persistence is poorly understood. We report that spontaneous DNA damage triggers persistence in Saccharomyces cerevisiae by activating the general stress response, providing protection against a range of harsh stress and drug environments. We further show that the persister subpopulation carries an increased load of genetic variants in the form of insertions, deletions or large structural variations, which are unrelated to their stress survival. This coupling of DNA damage to phenotypic persistence may increase genetic diversity specifically in severe stress conditions, where diversity is beneficial but the ability to generate de novo mutations is limited.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Hsp12 is a marker of budding yeast persisters.
Figure 2: DNA damage leads to yeast persisters.
Figure 3: Drug persistence depends on an intact DNA damage checkpoint.
Figure 4: Activation of the general stress response is important for yeast persistence.
Figure 5: Extreme cells are enriched for genetic mutations.

Similar content being viewed by others

References

  1. Bigger, J. Treatment of staphylococcal infections with penicillin by intermittent sterilisation. Lancet 244, 497–500 (1944).

    Article  Google Scholar 

  2. Maisonneuve, E. & Gerdes, K. Molecular mechanisms underlying bacterial persisters. Cell 157, 539–548 (2014).

    Article  CAS  PubMed  Google Scholar 

  3. Lewis, K. Persister cells. Annu. Rev. Microbiol. 64, 357–372 (2010).

    Article  CAS  PubMed  Google Scholar 

  4. Dhar, N. & McKinney, J. D. Microbial phenotypic heterogeneity and antibiotic tolerance. Curr. Opin. Microbiol. 10, 30–38 (2007).

    Article  CAS  PubMed  Google Scholar 

  5. Gefen, O. & Balaban, N. Q. The importance of being persistent: heterogeneity of bacterial populations under antibiotic stress. FEMS Microbiol. Rev. 33, 704–717 (2009).

    Article  CAS  PubMed  Google Scholar 

  6. Jayaraman, R. Bacterial persistence: some new insights into an old phenomenon. J. Biosci. 33, 795–805 (2008).

    Article  CAS  PubMed  Google Scholar 

  7. Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L. & Leibler, S. Bacterial persistence as a phenotypic switch. Science 305, 1622–1625 (2004).

    Article  CAS  PubMed  Google Scholar 

  8. Balaban, N. Q. Persistence: mechanisms for triggering and enhancing phenotypic variability. Curr. Opin. Genet. Dev. 21, 768–775 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Allison, K. R., Brynildsen, M. P. & Collins, J. J. Heterogeneous bacterial persisters and engineering approaches to eliminate them. Curr. Opin. Microbiol. 14, 593–598 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Nathan, C. Fresh approaches to anti-infective therapies. Sci. Trans. Med. 4, 140sr142 (2012).

    Article  Google Scholar 

  11. Lewis, K. Persister cells, dormancy and infectious disease. Nat. Rev. Microbiol. 5, 48–56 (2007).

    Article  CAS  PubMed  Google Scholar 

  12. Glickman, M. S. & Sawyers, C. L. Converting cancer therapies into cures: lessons from infectious diseases. Cell 148, 1089–1098 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Knoechel, B. et al. An epigenetic mechanism of resistance to targeted therapy in T cell acute lymphoblastic leukemia. Nat. Genet. 46, 364–370 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Welch, A. Z., Gibney, P. A., Botstein, D. & Koshland, D. E. TOR and RAS pathways regulate desiccation tolerance in Saccharomyces cerevisiae . Mol. Biol. Cell 24, 115–128 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Levy, S. F., Ziv, N. & Siegal, M. L. Bet hedging in yeast by heterogeneous, age-correlated expression of a stress protectant. PLoS Biol. 10, e1001325 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Stewart-Ornstein, J., Weissman, J. S. & El-Samad, H. Cellular noise regulons underlie fluctuations in Saccharomyces cerevisiae . Mol. Cell 45, 483–493 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Gasch, A. P. et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241–4257 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Weinert, T. & Hartwell, L. Control of G2 delay by the RAD9 gene of Saccharomyces cerevisiae . J. Cell Sci. Suppl. 12, 145–148 (1989).

    Article  CAS  PubMed  Google Scholar 

  19. Weinert, T. A. & Hartwell, L. H. The RAD9 gene controls the cell cycle response to DNA damage in Saccharomyces cerevisiae . Science 241, 317–322 (1988).

    Article  CAS  PubMed  Google Scholar 

  20. Lisby, M., Rothstein, R. & Mortensen, U. H. Rad52 forms DNA repair and recombination centers during S phase. Proc. Natl Acad. Sci. USA 98, 8276–8282 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Lisby, M., Mortensen, U. H. & Rothstein, R. Colocalization of multiple DNA double-strand breaks at a single Rad52 repair centre. Nat. Cell Biol. 5, 572–577 (2003).

    Article  CAS  PubMed  Google Scholar 

  22. Domkin, V., Thelander, L. & Chabes, A. Yeast DNA damage-inducible Rnr3 has a very low catalytic activity strongly stimulated after the formation of a cross-talking Rnr1/Rnr3 complex. J. Biol. Chem. 277, 18574–18578 (2002).

    Article  CAS  PubMed  Google Scholar 

  23. Hendry, J. A., Tan, G., Ou, J., Boone, C. & Brown, G. W. Leveraging DNA damage response signaling to identify yeast genes controlling genome stability. G3 5, 997–1006 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Berry, D. B. & Gasch, A. P. Stress-activated genomic expression changes serve a preparative role for impending stress in yeast. Mol. Biol. Cell 19, 4580–4587 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Lynch, M. et al. A genome-wide view of the spectrum of spontaneous mutations in yeast. Proc. Natl Acad. Sci. USA 105, 9272–9277 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nishant, K. T. et al. The baker’s yeast diploid genome is remarkably stable in vegetative growth and meiosis. PLoS Genet. 6, e1001109 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Serero, A., Jubin, C., Loeillet, S., Legoix-Ne, P. & Nicolas, A. G. Mutational landscape of yeast mutator strains. Proc. Natl Acad. Sci. USA 111, 1897–1902 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Huh, W. K. et al. Global analysis of protein localization in budding yeast. Nature 425, 686–691 (2003).

    Article  CAS  PubMed  Google Scholar 

  29. Janke, C. et al. A versatile toolbox for PCR-based tagging of yeast genes: new fluorescent proteins, more markers and promoter substitution cassettes. Yeast 21, 947–962 (2004).

    Article  CAS  PubMed  Google Scholar 

  30. 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  CAS  PubMed  Google Scholar 

  31. Blecher-Gonen, R. et al. High-throughput chromatin immunoprecipitation for genome-wide mapping of in vivo protein-DNA interactions and epigenomic states. Nat. Protoc. 8, 539–554 (2013).

    Article  PubMed  Google Scholar 

  32. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 1, 10–12 (2011).

    Article  Google Scholar 

  33. Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at http://arXiv.org/abs/1303.3997v2 (2013).

  34. Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–D705 (2012).

    Article  CAS  PubMed  Google Scholar 

  35. McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lawrence, M. et al. Software for computing and annotating genomic ranges. PLoS Computat. Biol. 9, e1003118 (2013).

    Article  CAS  Google Scholar 

  38. Obenchain, V. et al. VariantAnnotation: a Bioconductor package for exploration and annotation of genetic variants. Bioinformatics 30, 2076–2078 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at http://arXiv.org/abs/1207.3907 (2012).

  40. Ye, K., Schulz, M. H., Long, Q., Apweiler, R. & Ning, Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865–2871 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Layer, R. M., Chiang, C., Quinlan, A. R. & Hall, I. M. LUMPY: a probabilistic framework for structural variant discovery. Genome Biol. 15, R84 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Faust, G. G. & Hall, I. M. SAMBLASTER: fast duplicate marking and structural variant read extraction. Bioinformatics 30, 2503–2505 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Boeva, V. et al. Control-FREEC: a tool for assessing copy number and allelic content using next-generation sequencing data. Bioinformatics 28, 423–425 (2012).

    Article  CAS  PubMed  Google Scholar 

  44. Boeva, V. et al. Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization. Bioinformatics 27, 268–269 (2011).

    Article  CAS  PubMed  Google Scholar 

  45. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Koren, A., Soifer, I. & Barkai, N. MRC1-dependent scaling of the budding yeast DNA replication timing program. Genome Res. 20, 781–790 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank our group members for discussions and comments. We thank the Weizmann Institute of Science Flow Cytometry unit for support and O. Golani for help with the cell segmentation macro. This work was supported by the Minerva Center, European Research Council and the Israel Science Foundation. K.B. was supported by the European Molecular Biology Organization long-term fellowship.

Author information

Authors and Affiliations

Authors

Contributions

All authors designed the study and analysed the results. G.Y., D.L. and J.S. performed the experiments; K.B. analysed the whole genome sequencing data. N.B., G.Y., D.L. and K.B. wrote the manuscript.

Corresponding authors

Correspondence to Gilad Yaakov or Naama Barkai.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary figures 1–8, Supplementary note on variant calling. (PDF 14154 kb)

Supplementary Video 1

DNA damage precedes Hsp12 induction. (AVI 616 kb)

Supplementary Video 2

Emergence of drug-tolerant, DANN-damage-induced extreme cells in an unperturbed population A. (AVI 1644 kb)

Supplementary Video 3

Emergence of drug-tolerant, DANN-damage-induced extreme cells in an unperturbed population B. (AVI 5424 kb)

Supplementary Video 4

Emergence of drug-tolerant, DANN-damage-induced extreme cells in an unperturbed population C. (AVI 4773 kb)

Supplementary Video 5

HO-induced DSBs trigger persistence A. (AVI 502 kb)

Supplementary Video 6

HO-induced DSBs trigger persistence B. (AVI 1188 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yaakov, G., Lerner, D., Bentele, K. et al. Coupling phenotypic persistence to DNA damage increases genetic diversity in severe stress. Nat Ecol Evol 1, 0016 (2017). https://doi.org/10.1038/s41559-016-0016

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41559-016-0016

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing