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.

  • Letter
  • Published:

Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria

Abstract

The extent to which a population diverges from its ancestor through adaptive evolution depends on variation supplied by novel beneficial mutations. Extending earlier work1,2, recent theory makes two predictions that seem to be robust to biological details: the distribution of fitness effects among beneficial mutations before selection should be (i) exponential and (ii) invariant, meaning it is always exponential regardless of the fitness rank of the wild-type allele3,4. Here we test these predictions by assaying the fitness of 665 independently derived single-step mutations in the bacterium Pseudomonas fluorescens across a range of environments. We show that the distribution of fitness effects among beneficial mutations is indistinguishable from an exponential despite marked variation in the fitness rank of the wild type across environments. These results suggest that the initial step in adaptive evolution—the production of novel beneficial mutants from which selection sorts—is very general, being characterized by an approximately exponential distribution with many mutations of small effect and few of large effect. We also document substantial variation in the pleiotropic costs of antibiotic resistance, a result that may have implications for strategies aimed at eliminating resistant pathogens in animal and human populations.

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: Frequency distributions of absolute fitness in selective (a) and permissive (b) environments.
Figure 2: Distribution of fitness effects among 18 beneficial mutants assayed in the permissive environment.
Figure 3: Observed (bars) and expected (dots) distribution of fitness effects among beneficial mutants assayed in (a) LB (fitness rank of wild type, 21); (b) glucose (fitness rank of wild type, 9); (c) mannitol (fitness rank of wild type, 15) and (d) sorbitol (fitness rank of wild-type, 26).
Figure 4: Mean fitness effects among beneficial mutants across environments in experiment 2.

Similar content being viewed by others

References

  1. Fisher, R.A. The Genetical Theory of Natural Selection (Oxford Univ. Press, Oxford, 1930).

    Book  Google Scholar 

  2. Gillespie, J.H. Molecular evolution over the mutational landscape. Evolution Int. J. Org. Evolution 38, 1116–1129 (1984).

    Article  CAS  Google Scholar 

  3. Orr, H.A. The distribution of fitness effects among beneficial mutations. Genetics 163, 1519–1526 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Orr, H.A. The population genetics of adaptation: the adaptation of DNA sequences. Evolution Int. J. Org. Evolution 56, 1317–1330 (2002).

    Article  CAS  Google Scholar 

  5. Maynard Smith, J. Natural selection and the concept of the protein space. Nature 225, 563–564 (1970).

    Article  Google Scholar 

  6. Luria, S.E. & Delbruck, M. Mutations of bacteria from sensitivity to virus resistance. Genetics 28, 491–511 (1943).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Heisig, P. & Tschorney, R. Characterization of fluoroquinolone-resistant mutants of Escherichia coli selected in vitro. Antimicrob. Agents Chemother. 38, 1284–1291 (1994).

    Article  CAS  Google Scholar 

  8. Bagel, S. et al. Impact of gyrA and parC mutations on quinolone resistance, doubling time, and supercoiling degree of Escherichia coli. Antimicrob. Agents Chemother. 43, 868–875 (1999).

    Article  CAS  Google Scholar 

  9. Ruiz, J. Mechanisms of resistance to quinolones: target alterations, decreased accumulation and DNA gyrase protection. J. Antimicrob. Chemother. 51, 1109–1117 (2003).

    Article  CAS  Google Scholar 

  10. Hawkey, P.M. Mechanisms of quinolone action and microbial response. J. Antimicrob. Chemother. 51 (Suppl.), 29–35 (2003).

    Article  CAS  Google Scholar 

  11. Yoshida, H. et al. Proportion of DNA gyrase mutants among quinolone-resistant strains of Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 34, 1273–1275 (1990).

    Article  CAS  Google Scholar 

  12. Lenski, R.E. et al. Long-term experimental evolution in Escherichia coli. I. Adaptation and divergence during 2,000 generations. Am. Nat. 138, 1315–1341 (1991).

    Article  Google Scholar 

  13. Bennett, A.F., Lenski, R.E. & Mittler, J.E. Evolutionary adaptation to temperature. I. Fitness responses of Escherichia coli to changes in its thermal environment. Evolution Int. J. Org. Evolution 46, 16–30 (1993).

    Article  Google Scholar 

  14. Holder, K.K. & Bull, J.J. Profiles of adaptation in two similar viruses. Genetics 159, 1393–1404 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Imhof, M. & Schlötterer, C. Fitness effects of advantageous mutations in evolving Escherichia coli populations. Proc. Natl. Acad. Sci. USA 98, 1113–1117 (2001).

    Article  CAS  Google Scholar 

  16. Rozen, D.E., de Visser, J.A. & Gerrish, P.J. Fitness effects of fixed beneficial mutations in microbial populations. Curr. Biol. 12, 1040–1045 (2002).

    Article  CAS  Google Scholar 

  17. Rokyta, D.R. et al. An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus. Nat. Genet. 37, 441–444 (2005).

    Article  CAS  Google Scholar 

  18. Sanjuan, R., Moya, A. & Elena, S. The distribution of fitness effects caused by single-nucleotide substitutions in an RNA virus. Proc. Natl. Acad. Sci. USA 101, 8396–8401 (2004).

    Article  CAS  Google Scholar 

  19. Schrag, S.J., Perrot, V. & Levin, B.R. Adaptation to the fitness costs of antibiotic resistance in Escherichia coli. Proc. R. Soc. Lond. 264, 1287–1291 (1997).

    Article  CAS  Google Scholar 

  20. Reynolds, M.G. Compensatory evolution in rifampin-resistant Escherichia coli. Genetics 156, 1471–1481 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Andersson, D.I. & Levin, B.R. The biological cost of antibiotic resistance. Curr. Opin. Microbiol. 2, 489–493 (1999).

    Article  CAS  Google Scholar 

  22. Rosche, W.A. & Foster, P.L. Determining mutation rates in bacterial populations. Methods 20, 4–17 (2000).

    Article  CAS  Google Scholar 

  23. Wolfram, S. The Mathematica Book 3rd edn. (Cambridge Univ. Press, Cambridge, 1996).

    Google Scholar 

Download references

Acknowledgements

Thanks to M. Al-Azzabi and E. Drummond for technical assistance in the lab. S. Otto, S. Aris-Brossou, C. Zeyl, F.B. Christiansen and O.F. Christiansen provided comments. This work was supported by a Discovery Grant to R.K. from the Natural Sciences and Education Research Council of Canada.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rees Kassen.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kassen, R., Bataillon, T. Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria. Nat Genet 38, 484–488 (2006). https://doi.org/10.1038/ng1751

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng1751

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