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.

Optimality and evolutionary tuning of the expression level of a protein

Abstract

Different proteins have different expression levels. It is unclear to what extent these expression levels are optimized to their environment. Evolutionary theories suggest that protein expression levels maximize fitness1,2,3,4,5,6,7,8,9,10,11, but the fitness as a function of protein level has seldom been directly measured. To address this, we studied the lac system of Escherichia coli, which allows the cell to use the sugar lactose for growth12. We experimentally measured the growth burden13,14 due to production and maintenance of the Lac proteins (cost), as well as the growth advantage (benefit) conferred by the Lac proteins when lactose is present. The fitness function, given by the difference between the benefit and the cost, predicts that for each lactose environment there exists an optimal Lac expression level that maximizes growth rate. We then performed serial dilution evolution experiments at different lactose concentrations. In a few hundred generations, cells evolved to reach the predicted optimal expression levels. Thus, protein expression from the lac operon seems to be a solution of a cost–benefit optimization problem, and can be rapidly tuned by evolution to function optimally in new environments.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: The lac operon of E. coli and the experimental design in the present study.
Figure 2: Cost and benefit functions of lac expression in wild-type E. coli.
Figure 3: 3Predicted relative growth rate of cells (the fitness function) as a function of Lac protein expression.
Figure 4: Experimental evolutionary adaptation of E. coli cells to different concentrations of lactose.

Similar content being viewed by others

References

  1. Elena, S. F. & Lenski, R. E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nature Rev. Genet. 4, 457–469 (2003)

    Article  CAS  Google Scholar 

  2. Orr, H. A. The genetic theory of adaptation: a brief history. Nature Rev. Genet. 6, 119–127 (2005)

    Article  CAS  Google Scholar 

  3. Ibarra, R. U., Edwards, J. S. & Palsson, B. O. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth. Nature 420, 186–189 (2002)

    Article  ADS  CAS  Google Scholar 

  4. Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. From molecular to modular cell biology. Nature 402, C47–C52 (1999)

    Article  CAS  Google Scholar 

  5. Rosen, R. Optimality Principles in Biology (Butterworths, London, 1967)

    Book  Google Scholar 

  6. Savageau, M. A. Biochemical Systems Analysis: a Study of Function and Design in Molecular Biology (Addison-Wesley, Reading, Massachusetts, 1976)

    MATH  Google Scholar 

  7. Hartl, D. L. & Clark, A. G. Principles of Population Genetics (Sinauer, Sunderland, Massachusetts, 1997)

    Google Scholar 

  8. Heinrich, R. & Schuster, S. The Regulation of Cellular Systems (Chapman and Hall, New York, 1996)

    Book  Google Scholar 

  9. Maynard Smith, J. & Szathmary, E. The Major Transitions in Evolution (Oxford Univ. Press, Oxford, 1997)

    Google Scholar 

  10. Hartl, D. L. & Dykhuizen, D. E. The population genetics of Escherichia coli. Annu. Rev. Genet. 18, 31–68 (1984)

    Article  CAS  Google Scholar 

  11. Liebermeister, W., Klipp, E., Schuster, S. & Heinrich, R. A theory of optimal differential gene expression. Biosystems 76, 261–278 (2004)

    Article  CAS  Google Scholar 

  12. Muller-Hill, B. The lac Operon: a Short History of a Genetic Paradigm (Walter de Gruyter, New York, 1996)

    Book  Google Scholar 

  13. Koch, A. L. The protein burden of lac operon products. J. Mol. Evol. 19, 455–462 (1983)

    Article  ADS  CAS  Google Scholar 

  14. Nguyen, T. N., Phan, Q. G., Duong, L. P., Bertrand, K. P. & Lenski, R. E. Effects of carriage and expression of the Tn10 tetracycline-resistance operon on the fitness of Escherichia coli K12. Mol. Biol. Evol. 6, 213–225 (1989)

    CAS  PubMed  Google Scholar 

  15. Fay, J. C., McCullough, H. L., Sniegowski, P. D. & Eisen, M. B. Population genetic variation in gene expression is associated with phenotypic variation in Saccharomyces cerevisiae. Genome Biol. 5, R26 (2004)

    Article  Google Scholar 

  16. Conant, G. C. & Wagner, A. Convergent evolution of gene circuits. Nature Genet. 34, 264–266 (2003)

    Article  CAS  Google Scholar 

  17. Stephanopoulos, G. & Kelleher, J. Biochemistry. How to make a superior cell. Science 292, 2024–2025 (2001)

    Article  CAS  Google Scholar 

  18. Segre, D., Vitkup, D. & Church, G. M. Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl Acad. Sci. USA 99, 15112–15117 (2002)

    Article  ADS  CAS  Google Scholar 

  19. Cooper, T. F., Rosen, D. E. & Lenski, R. E. Parallel changes in gene expression after 20,000 generations of evolution in Escherichia coli. Proc. Natl Acad. Sci. USA 100, 1072–1077 (2003)

    Article  ADS  CAS  Google Scholar 

  20. Dykhuizen, D. E., Dean, A. M. & Hartl, D. L. Metabolic flux and fitness. Genetics 115, 25–31 (1987)

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Honisch, C., Raghunathan, A., Cantor, C. R., Palsson, B. O. & van den Boom, D. High-throughput mutation detection underlying adaptive evolution of Escherichia coli-K12. Genome Res. 14, 2495–2502 (2004)

    Article  CAS  Google Scholar 

  22. Kremling, A. et al. The organization of metabolic reaction networks. III. Application for diauxic growth on glucose and lactose. Metab. Eng. 3, 362–379 (2001)

    Article  CAS  Google Scholar 

  23. Wong, P., Gladney, S. & Keasling, J. D. Mathematical model of the lac operon: inducer exclusion, catabolite repression, and diauxic growth on glucose and lactose. Biotechnol. Prog. 13, 132–143 (1997)

    Article  CAS  Google Scholar 

  24. Yildirim, N., Santillan, M., Horike, D. & Mackey, M. C. Dynamics and bistability in a reduced model of the lac operon. Chaos 14, 279–292 (2004)

    Article  ADS  MathSciNet  CAS  Google Scholar 

  25. Bremer, H. & Dennis, P. P. in Escherichia coli and Salmonella (ed. Neidhardt, F. C.) 1553 (American Society for Microbiology, Washington DC, 1996)

    Google Scholar 

  26. Yokobayashi, Y., Weiss, R. & Arnold, F. H. Directed evolution of a genetic circuit. Proc. Natl Acad. Sci. USA 99, 16587–16591 (2002)

    Article  ADS  CAS  Google Scholar 

  27. Endy, D., You, L., Yin, J. & Molineux, I. J. Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes. Proc. Natl Acad. Sci. USA 97, 5375–5380 (2000)

    Article  ADS  CAS  Google Scholar 

  28. Dekel, E., Mangan, S. & Alon, U. Environmental selection of the feed-forward loop circuit in gene-regulation networks. Phys. Biol. 2, 81–88 (2005)

    Article  ADS  CAS  Google Scholar 

  29. Milo, R. et al. Network motifs: simple building blocks of complex networks. Science 298, 824–827 (2002)

    Article  ADS  CAS  Google Scholar 

  30. Monod, J. The growth of bacterial cultures. Annu. Rev. Microbiol. 3, 371–394 (1949)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank M. Elowitz, R. Kishony, G. Sela, B. Shraiman and all members of our laboratory for discussions. We thank the NIH, ISF and Minerva for support. E.D. thanks the Clore postdoctoral fellowship for support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Uri Alon.

Ethics declarations

Competing interests

Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Supplementary information

Supplementary Data

This details additional data on the experiments and calculation presented in the main text. It also contains Supplementary Figure S1-S8 and Supplementary Tables S1 and S2. (PDF 239 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dekel, E., Alon, U. Optimality and evolutionary tuning of the expression level of a protein. Nature 436, 588–592 (2005). https://doi.org/10.1038/nature03842

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature03842

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

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