Dual-stressor selection alters eco-evolutionary dynamics in experimental communities

Abstract

Recognizing when and how rapid evolution drives ecological change is fundamental for our understanding of almost all ecological and evolutionary processes such as community assembly, genetic diversification and the stability of communities and ecosystems. Generally, rapid evolutionary change is driven through selection on genetic variation and is affected by evolutionary constraints, such as tradeoffs and pleiotropic effects, all contributing to the overall rate of evolutionary change. Each of these processes can be influenced by the presence of multiple environmental stressors reducing a population’s reproductive output. Potential consequences of multistressor selection for the occurrence and strength of the link from rapid evolution to ecological change are unclear. However, understanding these is necessary for predicting when rapid evolution might drive ecological change. Here we investigate how the presence of two stressors affects this link using experimental evolution with the bacterium Pseudomonas fluorescens and its predator Tetrahymena thermophila. We show that the combination of predation and sublethal antibiotic concentrations delays the evolution of anti-predator defence and antibiotic resistance compared with the presence of only one of the two stressors. Rapid defence evolution drives stabilization of the predator–prey dynamics but this link between evolution and ecology is weaker in the two-stressor environment, where defence evolution is slower, leading to less stable population dynamics. Tracking the molecular evolution of whole populations over time shows further that mutations in different genes are favoured under multistressor selection. Overall, we show that selection by multiple stressors can significantly alter eco-evolutionary dynamics and their predictability.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Eco-evolutionary dynamics of P. fluorescens populations exposed to sub-MIC levels of streptomycin and ciliates.
Fig. 2: Stability of bacteria–ciliate populations exposed to 0 × or 0.1 × MIC sub-MIC levels of streptomycin and the correlation of stability with defence levels of the bacteria populations.
Fig. 3: Trait correlations of clonal isolates from P. fluorescens populations exposed to 0.1 × MIC streptomycin and the ciliate T. thermophila from the end of the experiment (day 66).
Fig. 4: Molecular evolution of P. fluorescens populations exposed to 0.1 × MIC streptomycin and the ciliate T. thermophila in a factorial design.

Data availability

Data reported in the paper will be archived in a community archive. Raw sequence reads from genomic analyses have been deposited in the NCBI Sequence Read Archive under the BioProject accession number PRJNA476204. Count and trait data have been deposited at PANGAEA: https://doi.pangaea.de/10.1594/PANGAEA.895614.

References

  1. 1.

    Gullberg, E. et al. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Path. 7, e1002158 (2011).

    Article  CAS  Google Scholar 

  2. 2.

    Andersson, D. I. & Hughes, D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nat. Rev. Microbiol. 8, 260–271 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Frickel, J., Theodosiu, L. & Becks, L. Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity. Proc. Natl Acad. Sci. USA 114, 11193–11198 (2017).

    Article  CAS  PubMed  Google Scholar 

  4. 4.

    Cairns, J., Becks, L., Jalasvuori, M. & Hiltunen, T. Sublethal streptomycin concentrations and lytic bacteriophage interactively promote resistance evolution. Phil. Trans. R. Soc. B 9, 20160040 (2017).

    Article  CAS  Google Scholar 

  5. 5.

    Frickel, J., Sieber, M. & Becks, L. Eco-evolutionary dynamics in a coevolving host–virus system. Ecol. Lett. 19, 450–459 (2016).

    Article  PubMed  Google Scholar 

  6. 6.

    Yoshida, T. et al. Rapid evolution drives ecological dynamics in a predator–prey system. Nature 424, 303–306 (2003).

    Article  CAS  Google Scholar 

  7. 7.

    Koch, H., Frickel, J., Valiadi, M. & Becks, L. Why rapid, adaptive evolution matters for community dynamics. Front. Ecol. Evol. 2, 17 (2014).

    Article  Google Scholar 

  8. 8.

    Rudman, S. M. et al. What genomic data can reveal about eco-evolutionary dynamics. Nat. Ecol. Evol. 2, 9–15 (2018).

    Article  PubMed  Google Scholar 

  9. 9.

    Madigan, M. T., Martinko, J. M., Bender, K. S., Buckley, D. H. & Stahl, D. A. Brock Biology of Microorganisms 14th edn (Pearson, Harlow, 2014).

  10. 10.

    Paerl, H. W. & Huisman, J. Climate – blooms like it hot. Science 320, 57–58 (2008).

    Article  CAS  PubMed  Google Scholar 

  11. 11.

    Bordenstein, S. R. & Theis, K. R. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. PLoS Biol. 13, e1002226 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Hiltunen, T., Kaitala, V., Laakso, J. & Becks, L. Evolutionary contribution to coexistence of competitors in microbial food webs. Proc. R. Soc. B 284, 20170415 (2017).

    Article  CAS  PubMed  Google Scholar 

  13. 13.

    Lawrence, D. et al. Species interactions alter evolutionary responses to a novel environment. PLoS Biol. 10, e1001330 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Hoffmann, A. A. & Hercus, M. J. Environmental stress as an evolutionary force. Bioscience 50, 217–226 (2000).

    Article  Google Scholar 

  15. 15.

    Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).

    Article  PubMed  Google Scholar 

  16. 16.

    Meyer, J. R. & Kassen, R. The effects of competition and predation on diversification in a model adaptive radiation. Nature 446, 432–435 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. 17.

    Hiltunen, T. & Becks, L. Consumer co-evolution as an important component of the eco-evolutionary feedback. Nat. Commun. 5, 5226 (2014).

    Article  CAS  PubMed  Google Scholar 

  18. 18.

    Murdoch, W. W., Nisbet, R. M., McCauley, E., deRoos, A. M. & Gurney, W. S. C. Plankton abundance and dynamics across nutrient levels: tests of hypotheses. Ecology 79, 1339–1356 (1998).

    Article  Google Scholar 

  19. 19.

    McCauley, E., Nisbet, R. M., Murdoch, W. W., de Roos, A. M. & Gurney, W. S. C. Large-amplitude cycles of Daphnia and its algal prey in enriched environments. Nature 402, 653–656 (1999).

    Article  CAS  Google Scholar 

  20. 20.

    Abrams, P. A. & Matsuda, H. Prey adaptation as a cause of predator–prey cycles. Evolution 51, 1742–1750 (1997).

    Article  PubMed  Google Scholar 

  21. 21.

    Fussmann, G. F., Ellner, S. P., Shertzer, K. W. & Hairston, N. G. Jr Crossing the Hopf bifurcation in a live predator–prey system. Science 290, 1358–1360 (2000).

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Jones, L. E. & Ellner, S. P. Effects of rapid prey evolution on predator–prey cycles. J. Math. Biol. 55, 541–573 (2007).

    Article  PubMed  Google Scholar 

  23. 23.

    Becks, L., Ellner, S. P., Jones, L. E. & Hairston, N. G. Jr Reduction of adaptive genetic diversity radically alters eco-evolutionary community dynamics. Ecol. Lett. 13, 989–997 (2010).

    Google Scholar 

  24. 24.

    Friman, V.-P., Guzman, L. M., Reuman, D. C. & Bell, T. Bacterial adaptation to sublethal antibiotic gradients can change the ecological properties of multitrophic microbial communities. Proc. R. Soc. Lond. B. 282, 20142920 (2015).

    Article  Google Scholar 

  25. 25.

    Lang, G. I. et al. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500, 571–574 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Ostman, B., Hintze, A. & Adami, C. Impact of epistasis and pleiotropy on evolutionary adaptation. Proc. R. Soc. B 279, 247–256 (2012).

    Article  PubMed  Google Scholar 

  27. 27.

    Hansen, T. F. Why epistasis is important for selection and adaptation. Evolution 67, 3501–3511 (2013).

    Article  PubMed  Google Scholar 

  28. 28.

    Rosenthal, J. P. & Dirzo, R. Effects of life history, domestication and agronomic selection on plant defence against insects: Evidence from maizes and wild relatives. Evol. Ecol. 11, 337–355 (1997).

    Article  Google Scholar 

  29. 29.

    Barton, N. & Partridge, L. Limits to natural selection. Bioessays 22, 1075–1084 (2000).

    Article  CAS  PubMed  Google Scholar 

  30. 30.

    Gerrish, P. J. & Lenski, R. E. The fate of competing beneficial mutations in an asexual population. Genetica 102-3, 127–144 (1998).

    Article  Google Scholar 

  31. 31.

    Ferriere, R. & Legendre, S. Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory. Phil. Trans. R. Soc. B 368, 20120081 (2013).

    Article  PubMed  Google Scholar 

  32. 32.

    Fogle, C. A., Nagle, J. L. & Desai, M. M. Clonal interference, multiple mutations and adaptation in large asexual populations. Genetics 180, 2163–2173 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Park, S. C. & Krug, J. Clonal interference in large populations. Proc. Natl Acad. Sci. USA 104, 18135–18140 (2007).

    Article  PubMed  Google Scholar 

  34. 34.

    Osmond, M. M., Otto, S. P. & Klausmeier, C. A. When predators help prey adapt and persist in a changing environment. Am. Nat. 190, 83–98 (2017).

    Article  PubMed  Google Scholar 

  35. 35.

    Cortez, M. H. How the magnitude of prey genetic variation alters predator–prey eco-evolutionary dynamics. Am. Nat. 188, 329–341 (2016).

    Article  PubMed  Google Scholar 

  36. 36.

    Hairston, N. G. et al. Rapid evolution and the convergence of ecological and evolutionary time. Ecol. Lett. 8, 1114–1127 (2005).

    Article  Google Scholar 

  37. 37.

    Bell, G. Evolutionary rescue and the limits of adaptation. Phil. Trans. R. Soc. B 368, 20120080 (2013).

    Article  PubMed  Google Scholar 

  38. 38.

    Orr, A. H. & Unckless, R. L. The population genetics of evolutionary rescue. PLoS Genet. 10, e1004551 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Buskirk, S. W., Peace, R. E. & Lang, G. I. Hitchhiking and epistasis give rise to cohort dynamics in adapting populations. Proc. Natl Acad. Sci. USA 114, 8330–8335 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. 40.

    Rainey, P. B. & Travisano, M. Adaptive radiation in a heterogeneous environment. Nature 394, 69–72 (1998).

    Article  CAS  Google Scholar 

  41. 41.

    Workentine, M. L., Wang, S. Y., Ceri, H. & Turner, R. J. Spatial distributions of Pseudomonas fluorescens colony variants in mixed-culture biofilms. BMC Microbiol. 13, 175 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Bantinaki, E. et al. Adaptive divergence in experimental populations of Pseudomonas fluorescens. III. Mutational origins of wrinkly spreader diversity. Genetics 176, 441–453 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Mavrodi, O. V., Mavrodi, D. V., Weller, D. M. & Thomashow, L. S. Role of ptsP, orfT, and sss recombinase genes in root colonization by Pseudomonas fluorescens Q8r1-96. Appl. Environ. Microbiol. 72, 7111–7122 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Naeem, S., Duffy, J. E. & Zavaleta, E. The functions of biological diversity in an age of extinction. Science 336, 1401–1406 (2012).

    Article  CAS  PubMed  Google Scholar 

  45. 45.

    Ellner, S. P. & Becks, L. Rapid prey evolution and the dynamics of two-predator food webs. Theor. Ecol. 4, 133–152 (2011).

    Article  Google Scholar 

  46. 46.

    Rainey, P. B. & Bailey, M. J. Physical and genetic map of the Pseudomonas fluorescens SBW25 chromosome. Mol. Microbiol. 19, 521–533 (1996).

    Article  CAS  PubMed  Google Scholar 

  47. 47.

    Kassen, R., Buckling, A., Bell, G. & Rainey, P. B. Diversity peaks at intermediate productivity in a laboratory microcosm. Nature 406, 508–512 (2000).

    Article  CAS  PubMed  Google Scholar 

  48. 48.

    Duetz, W. A. et al. Methods for intense aeration, growth, storage, and replication of bacterial strains in microtiter plates. Appl. Environ. Microbiol. 66, 2641–2646 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014).

  50. 50.

    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  51. 51.

    Halekoh, U., Hojsgaard, S. & Yan, J. The R package geepack for generalized estimating equations. J. Stat. Softw. 15, 1–11 (2006).

    Google Scholar 

  52. 52.

    Borchers, H. W. pracma: Practical Numerical Math Functions R Package Version 2.1.5 (2018); https://CRAN.R-project.org/package=pracma

  53. 53.

    Silby, M. W. et al. Genomic and genetic analyses of diversity and plant interactions of Pseudomonas fluorescens. Genome Biol. 10, R51 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w(1118); iso-2; iso-3. Fly 6, 80–92 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    McDonald, M. J., Rice, D. P. & Desai, M. M. Sex speeds adaptation by altering the dynamics of molecular evolution. Nature 531, 233–239 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Abyzov, A., Urban, A. E., Snyder, M. & Gerstein, M. CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing. Genome Res. 21, 974–984 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are grateful to T. Niska, S. Suomalainen, T. Virolainen and J. Haafke for helping with data collection. This work was supported by an Emmy Noether Grant and Heisenberg Stipend from the German Research Foundation (DFG) to L.B. (grant nos. BE 4135/3-1 and 4135/9), and received support from the Academy of Finland to T.H. (project no. 106993), to J.L. (project no. 1255572) and to V.K. (project no. 1267541) and the Finnish Cultural Foundation to J.C. (grant no. 160149).

Author information

Affiliations

Authors

Contributions

T.H., M.J. and L.B. conceived and designed the study. J.C., J.F., E.K. and L.B. analysed the sequence data. S.K. performed the sequencing. T.H. and J.C. collected the data. L.B. and T.H. analysed the data. J.F., T.H. and L.B. wrote the manuscript. All authors contributed to the final version of the manuscript.

Corresponding author

Correspondence to Lutz Becks.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figures 1–10 and Supplementary Tables 1–6

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hiltunen, T., Cairns, J., Frickel, J. et al. Dual-stressor selection alters eco-evolutionary dynamics in experimental communities. Nat Ecol Evol 2, 1974–1981 (2018). https://doi.org/10.1038/s41559-018-0701-5

Download citation

Further reading

Search

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