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Understanding the limits to generalizability of experimental evolutionary models


Given the difficulty of testing evolutionary and ecological theory in situ, in vitro model systems are attractive alternatives1; however, can we appraise whether an experimental result is particular to the in vitro model, and, if so, characterize the systems likely to behave differently and understand why? Here we examine these issues using the relationship between phenotypic diversity and resource input in the T7–Escherichia coli co-evolving system as a case history. We establish a mathematical model of this interaction, framed as one instance of a super-class of host–parasite co-evolutionary models, and show that it captures experimental results. By tuning this model, we then ask how diversity as a function of resource input could behave for alternative co-evolving partners (for example, E. coli with lambda bacteriophages). In contrast to populations lacking bacteriophages, variation in diversity with differences in resources is always found for co-evolving populations, supporting the geographic mosaic theory of co-evolution2. The form of this variation is not, however, universal. Details of infectivity are pivotal: in T7–E. coli with a modified gene-for-gene interaction, diversity is low at high resource input, whereas, for matching-allele interactions, maximal diversity is found at high resource input. A combination of in vitro systems and appropriately configured mathematical models is an effective means to isolate results particular to the in vitro system, to characterize systems likely to behave differently and to understand the biology underpinning those alternatives.

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Figure 1: Infection mechanisms between bacteria ( B ) and phages ( P).
Figure 2: Bacterial diversity at steady state as a function of resource input, as provided by the mathematical model for different infection mechanisms.
Figure 3: Experimentally derived bacterial diversity and phage abundance as a function of resource input.
Figure 4: Phage diversity at steady state as a function of resource input for different infection mechanisms.


  1. Jessup, C. M. et al. Big questions, small worlds: microbial model systems in ecology. Trends Ecol. Evol. 19, 189–197 (2004)

    Article  Google Scholar 

  2. Thompson, J. The Geographic Mosaic of Coevolution (Chicago Univ. Press, Chicago, 2005)

    Book  Google Scholar 

  3. Kruger, D. H. & Schroeder, C. Bacteriophage T3 and bacteriophage T7 virus–host cell interactions. Microbiol. Rev. 45, 9–51 (1981)

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Wade, M. J. The co-evolutionary genetics of ecological communities. Nature Rev. Genet. 8, 185–195 (2007)

    Article  CAS  Google Scholar 

  5. Buckling, A. & Rainey, P. B. Antagonistic coevolution between a bacterium and a bacteriophage. Proc. R. Soc. Lond. B 269, 931–936 (2002)

    Article  Google Scholar 

  6. Agrawal, A. & Lively, C. M. Infection genetics: gene-for-gene versus matching-alleles models and all points in between. Evol. Ecol. Res. 4, 79–90 (2002)

    Google Scholar 

  7. Morgan, A. D., Gandon, S. & Buckling, A. The effect of migration on local adaptation in a coevolving host–parasite system. Nature 437, 253–256 (2005)

    Article  ADS  CAS  Google Scholar 

  8. Chao, L., Levin, B. R. & Stewart, F. M. Complex community in a simple habitat — experimental-study with bacteria and phage. Ecology 58, 369–378 (1977)

    Article  Google Scholar 

  9. Forde, S. E., Thompson, J. N. & Bohannan, B. J. M. Adaptation varies through space and time in a coevolving host–parasitoid interaction. Nature 431, 841–844 (2004)

    Article  ADS  CAS  Google Scholar 

  10. Qimron, U., Marintcheva, B., Tabor, S. & Richardson, C. C. Genomewide screens for Escherichia coli genes affecting growth of T7 bacteriophage. Proc. Natl Acad. Sci. USA 103, 19039–19044 (2006)

    Article  ADS  CAS  Google Scholar 

  11. Sasaki, A. & Godfray, H. C. J. A model for the coevolution of resistance and virulence in coupled host–parasitoid interactions. Proc. R. Soc. Lond. B 266, 455–463 (1999)

    Article  Google Scholar 

  12. Tamaki, S., Sato, T. & Matsuhas, M. Role of lipopolysaccharides in antibiotic resistance and bacteriophage adsorption of Escherichia coli K-12 . J. Bact. 105, 968–975 (1971)

    CAS  PubMed  Google Scholar 

  13. Sen, K. & Nikaido, H. Lipopolysaccharide structure required for in vitro trimerization of Escherichia coli Ompf porin. J. Bact. 173, 926–928 (1991)

    Article  CAS  Google Scholar 

  14. Poullain, V., Gandon, S., Brockhurst, M. A., Buckling, A. & Hochberg, M. E. The evolution of specificity in evolving and coevolving antagonistic interactions between a bacteria and its phage. Evolution 62, 1–11 (2008)

    PubMed  Google Scholar 

  15. Bohannan, B. J. M., Kerr, B., Jessup, C. M., Hughes, J. B. & Sandvik, G. Trade-offs and coexistence in microbial microcosms. Anton Leeuw. Int. J. G. 81, 107–115 (2002)

    Article  CAS  Google Scholar 

  16. Yoshida, T., Hairston, N. G. & Ellner, S. P. Evolutionary trade-off between defence against grazing and competitive ability in a simple unicellular alga, Chlorelia vulgaris . Proc. R. Soc. Lond. B 271, 1947–1953 (2004)

    Article  Google Scholar 

  17. Ferris, M. T., Joyce, P. & Burch, C. L. High frequency of mutations that expand the host range of an RNA virus. Genetics 176, 1013–1022 (2007)

    Article  CAS  Google Scholar 

  18. Weitz, J. S., Hartman, H. & Levin, S. A. Coevolutionary arms races between bacteria and bacteriophage. Proc. Natl Acad. Sci. USA 102, 9535–9540 (2005)

    Article  ADS  CAS  Google Scholar 

  19. Spanakis, E. & Horne, M. T. Co-adaptation of Escherichia coli and coliphage lambda vir in continuous culture. J. Gen. Microbiol. 133, 353–360 (1987)

    CAS  PubMed  Google Scholar 

  20. Lenski, R. E. & Levin, B. R. Constraints on the coevolution of bacteria and virulent phage — a model, some experiments, and predictions for natural communities. Am. Nat. 125, 585–602 (1985)

    Article  Google Scholar 

  21. Forde, S. E., Thompson, J. N. & Bohannan, B. J. Gene flow reverses an adaptive cline in a coevolving host-parasitoid interaction. Am. Nat. 169, 794–801 (2007)

    PubMed  Google Scholar 

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We thank A. Buckling, S. Nuismer, K. Rich, J. Hoeksema and C. Jessup for their comments on an earlier version of this manuscript. L.D.H. is a Royal Society Wolfson Research Merit Award Holder. I.G. is supported by a NERC Advanced Fellowship. S.S.A. is funded by an ORS award and a studentship for the Department of Mathematics at Imperial College London. S.E.F. and J.N.T. are supported by the National Science Foundation DEB 0515598.

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Correspondence to Laurence D. Hurst.

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This file contains Supplementary Discussion and Supplementary Figures 1-11. The file contains the following sections: 1. Introduction; 2. The mathematical model; 3. Measuring diversity generated by the model: a rationale; 4. Equilibrium structure of the model; 5. E.coli-T7 case study; 6. Alternative diversity curves; 7. Comments. The Supplementary Information defines the class of mathematical models of bacteria-page co-evolution and shows that there is at least one system that fits the mean experimental data. It then asks, within the entire class of models proposed, which features of E.coli-T7 interaction are universal to all models and which are system specific. (PDF 676 kb)

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Forde, S., Beardmore, R., Gudelj, I. et al. Understanding the limits to generalizability of experimental evolutionary models. Nature 455, 220–223 (2008).

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