Abstract
Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.
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References
Jacob, F. & Monod, J. Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3, 318–356 (1961).
Englesberg, E., Irr, J., Power, J. & Lee, N. Positive Control of enzyme synthesis by gene C in the L-Arabinose system. J. Bacteriol. 90, 946–957 (1965).
Whitacre, J. M. Degeneracy: a link between evolvability, robustness and complexity in biological systems. Theor. Biol. Med. Model 7, 6 (2010).
Madan Babu, M., Teichmann, S. A. & Aravind, L. Evolutionary dynamics of prokaryotic transcriptional regulatory networks. J. Mol. Biol. 358, 614–633 (2006).
Lozada-Chavez, I. Bacterial regulatory networks are extremely flexible in evolution. Nucl. Acids Res. 34, 3434–3445 (2006).
Ciliberti, S., Martin, O. C. & Wagner, A. Innovation and robustness in complex regulatory gene networks. PNAS 104, 13591–13596 (2007).
Steinacher, A., Bates, D. G., Akman, O. E. & Soyer, O. S. Nonlinear dynamics in gene regulation promote robustness and evolvability of gene expression levels. PLoS ONE 11, e0153295–21 (2016).
Payne, J. L. & Wagner, A. The robustness and evolvability of transcription factor binding sites. Science 343, 875–877 (2014).
Tuğrul, M., Paixão, T., Barton, N. H. & Tkačik, G. Dynamics of transcription factor binding site evolution. PLoS Genet. 11, e1005639–28 (2015).
Pigliucci, M. Is evolvability evolvable? Nat. Rev. Genet. 9, 75–82 (2008).
Isalan, M. et al. Evolvability and hierarchy in rewired bacterial gene networks. Nature 452, 840–845 (2008).
Prudhomme, B., Gompel, N. & Carroll, S. B. Emerging principles of regulatory evolution. PNAS 104, 8605–8612 (2007).
Ward, J. J. & Thornton, J. M. Evolutionary models for formation of network motifs and modularity in the Saccharomyces Transcription Factor Network. PLoS Comput. Biol. 3, e198–10 (2007).
Nocedal, I. & Johnson, A. D. How transcription networks evolve and produce biological novelty. Cold Spring Harb. Symp. Quant. Biol. 80, 265–274 (2016).
Tuch, B. B., Li, H. & Johnson, A. D. Evolution of eukaryotic transcription circuits. Science 391, 1797–1799 (2008).
Li, H. & Johnson, A. D. Evolution of Transcription networks—lessons from yeasts. Curr. Biol. 20, R746–R753 (2010).
Maerkl, S. J. & Quake, S. R. Experimental determination of the evolvability of a transcription factor. Proc. Natl Acad. Sci., USA 106, 18650–18655 (2009).
Nocedal, I., Mancera, E. & Johnson, A. D. Gene regulatory network plasticity predates a switch in function of a conserved transcription regulator. Elife e23250 (2017). https://doi.org/10.7554/eLife.23250.001
Sayou, C. et al. A promiscuous intermediate underlies the evolution of LEAFY DNA binding specificity. Science 343, 645–648 (2014).
Pougach, K. et al. Duplication of a promiscuous transcription factor drives the emergence of a new regulatory network. Nat. Commun. 5, 1–11 (2014).
Wagner, G. P. & Lynch, V. J. The gene regulatory logic of transcription factor evolution. Trends Ecol. Evol. 23, 377–385 (2008).
Hippel von, P. H. & Berg, O. G. On the specificity of DNA-protein interactions. PNAS 83, 1608–1612 (1986).
Gerland, U., Moroz, D. J. & Hwa, T. Physical constraints and functional characteristics of transcription factor–DNA interaction. PNAS 99, 12015–12020 (2002).
Mustonen, V., Kinney, J. B., Callan, C. G. J. & Lässig, M. Energy-dependent fitness: a quantitative model for the evolution of yeast transcription factor binding sites. PNAS 105, 12376–12381 (2008).
Starr, T. N. & Thornton, J. W. Epistasis in protein evolution. Protein Sci. 25, 1204–1218 (2016).
Eyre-Walker, A. & Keightley, P. D. The distribution of fitness effects of new mutations. Nat. Rev. Genet. 8, 610–618 (2007).
Carroll, S. B. Evolution at two levels: on genes and form. PLOS Biol. 3, e245 (2005).
Ludwig, M. Z. et al. Functional evolution of a cis-regulatory module. PLOS Biol. 3, e93–11 (2005).
Moses, A. M., Chiang, D. Y., Pollard, D. A., Iyer, V. N. & Eisen, M. B. MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model. Genome Biol. 5, R98 (2004).
Berg, J., Willmann, S. & Lässig, M. Adaptive evolution of transcription factor binding sites. BMC Evol. Biol. 4, 42–12 (2004).
Wittkopp, P. J. & Kalay, G. Cis-regulatory elements: molecular mechanisms and evolutionary processes underlying divergence. Nat. Rev. Genet. 13, 59–69 (2012).
Pujato, M., MacCarthy, T., Fiser, A. & Bergman, A. The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks. PLoS Comput. Biol. 9, e1002865–12 (2013).
Sauer, R. T. et al. The Lambda and P22 phage repressors. J. Biomol. Struct. Dyn. 1, 1011–1022 (1983).
Ptashne, M. A Genetic Switch: Gene Control and Phage Lambda.. (Blackwell Scientific Publications, Palo Alto, CA, US, 1986).
Susskind, M. M. & Botstein, D. Molecular genetics of bacteriophage P22. Microbiol. Rev. 42, 385–413 (1978).
Sarai, A. & Takeda, Y. Lambda repressor recognizes the approximately 2-fold symmetric half-operator sequences asymmetrically. PNAS 86, 6513–6517 (1989).
Hilchey, S. P., Wu, L. & Koudelka, G. B. Recognition of nonconserved bases in the P22 operator by P22 repressor requires specific interactions between repressor and conserved bases. J. Biol. Chem. 32, 19898–19905 (1997).
Lutz, R. & Bujard, H. Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucl. Acids Res. 25, 1203–1210 (1997).
Degnan, P. H., Michalowski, C. B., Babić, A. C., Cordes, M. H. J. & Little, J. W. Conservation and diversity in the immunity regions of wild phages with the immunity specificity of phage λ. Mol. Microbiol. 64, 232–244 (2007).
Bintu, L. et al. Transcriptional regulation by the numbers: models. Curr. Opin. Genet. Develop. 15, 116–124 (2005).
Shea, M. A. & Ackers, G. K. The OR Control system of bacteriophage lambda. A physical-chemical model for gene regulation. J. Mol. Biol. 181, 211–230 (1985).
Maerkl, S. J. & Quake, S. R. A systems approach to measuring the binding energy landscapes of transcription factors. Science 315, 233–237 (2007).
Zhao, Y., Ruan, S., Pandey, M. & Stormo, G. D. Improved models for transcription factor binding site identification using nonindependent interactions. Genetics 191, 781–790 (2012).
Weirauch, M. T. et al. Evaluation of methods for modeling transcription factor sequence specificity. Nat. Biotechnol. 31, 126–134 (2013).
Klumpp, S. & Hwa, T. Growth-rate-dependent partitioning of RNA polymerases in bacteria. PNAS 105, 20245–20250 (2008).
Razo-Mejia, M. et al. Comparison of the theoretical and real-world evolutionary potential of a genetic circuit. Phys. Biol. 11, 026005 (2014).
Lässig, M. From Biophysics to evolutionary genetics: statistical aspects of gene regulation. BMC Bioinform. 8, S7 (2007).
Lagator, M., Paixão, T., Barton, N. H., Bollback, J. P. & Guet, C. C. On the mechanistic nature of epistasis in a canonical cis-regulatory element. Elife e25192 (2017). https://doi.org/10.7554/eLife.25192.001
Kreamer, N. N., Phillips, R., Newman, D. K. & Boedicker, J. Q. Predicting the impact of promoter variability on regulatory outputs. Sci. Rep. 5, 18238 (2015).
Luscombe, N. M. & Thornton, J. M. Protein–DNA interactions: amino acid conservation and the effects of mutations on binding specificity. J. Mol. Biol. 320, 991–1009 (2002).
Watkins, D., Hsiao, C., Woods, K. K., Koudelka, G. B. & Williams, L. D. P22c2 repressor−operator complex: mechanisms of direct and indirect readout. Biochemistry 47, 2325–2338 (2008).
Gertz, J., Gerke, J. P. & Cohen, B. A. Epistasis in a quantitative trait captured by a molecular model of transcription factor interactions. Theor. Popul. Biol. 77, 1–5 (2010).
Stormo, G. D. & Zhao, Y. Determining the specificity of protein–DNA interactions. Nat. Rev. Genet. 11, 751–760 (2010).
Ancel, L. W. & Fontana, W. Plasticity, evolvability, and modularity in RNA. J. Exp. Zoology Mol. Dev. Evol. 288, 242–283 (2000).
Draghi, J. A., Parsons, T. L., Wagner, G. P. & Plotkin, J. B. Mutational robustness can facilitate adaptation. Nature 463, 353–355 (2010).
Wagner, A. The Role of Robustness in Phenotypic Adaptation and Innovation. Proc. Roy. Soc. B: Biol. Sci. 279, 1249–1258 (2012).
Bakk, A. & Metzler, R. In vivo non-specific binding of λ CI and Cro repressors is significant. FEBS Lett. 563, 66–68 (2004).
Fattah, K. R., Mizutani, S., Fattah, F. J., Matsushiro, A. & Sugino, Y. A comparative study of the immunity region of lambdoid phages including shiga-toxin-converting phages: molecular basis for cross immunity. Genes Genet. Syst. 75, 223–232 (2000).
Friedlander, T., Prizak, R., Guet, C., Barton, N. H. & Tkacik, G. Intrinsic limits to gene regulation by global crosstalk. Nat. Commun. 7, 1–12 (2016).
Duque, T. et al. Simulations of enhancer evolution provide mechanistic insights into gene regulation. Mol. Biol. Evol. 31, 184–200 (2013).
Nagai, T. et al. A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat. Biotechnol. 20, 87–90 (2002).
Meyer, B. J., Maurer, R. & Ptashne, M. Gene regulation at the right operator (Or) of bacteriophage II. Or1, Or2, and Or3: their roles in mediating the effects of repressor and cro. J. Mol. Biol. 139, 163–194 (1980).
Datsenko, K. A. & Wanner, B. R. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. PNAS 97, 6640–6645 (2000).
Koblan, K. S. & Ackers, G. K. Energetics of subunit dimerization in bacteriophage Lambda cI repressor: linkage to protons, temperature, and KCl. Biochemistry 30, 7817–7821 (1991).
Santillán, M. & Mackey, M. C. Why the lysogenic state of phage is so stable: a mathematical modeling approach. Biophys. J. 86, 75–84 (2004).
Brunner, M. & Bujard, H. Promoter recognition and promoter strength in the Escherichia coli system. EMBO J. 6, 3139–3144 (1987).
Vilar, J. M. G. Accurate prediction of gene expression by integration of DNA sequence statistics with detailed modeling of transcription regulation. Biophys. J. 99, 2408–2413 (2010).
Kinney, J. B., Murugan, A., Callan, C. G. J. & Cox, E. C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. PNAS 107, 9158–9163 (2010).
Hermsen, R., Tans, S. & Wolde ten, P. R. Transcriptional regulation by competing transcription factor modules. PLoS Comput. Biol. 2, e164 (2006).
Acknowledgements
We thank S. Abedon, R. Grah, K. Jain, C. Nizak, T. Paixão, M. Pleska, E. Reichhart and S. Sarikas for helpful discussions. This work was supported by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. [291734] to M.L., and European Research Council under the Horizon 2020 Framework Programme (FP/2007-2013) / ERC grant agreement no. [648440] to J.P.B. C.I. is the recipient of a DOC (Doctoral Fellowship Programme of the Austrian Academy of Sciences) Fellowship of the Austrian Academy of Sciences.
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All authors conceived the study together. C.I. and M.L. designed and carried out the experiments and analysed the data. C.I. wrote the code and ran the model. C.I. and M.L. wrote the initial draft of the manuscript and revised it together with G.T., J.P.B and C.C.G.
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Igler, C., Lagator, M., Tkačik, G. et al. Evolutionary potential of transcription factors for gene regulatory rewiring. Nat Ecol Evol 2, 1633–1643 (2018). https://doi.org/10.1038/s41559-018-0651-y
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DOI: https://doi.org/10.1038/s41559-018-0651-y
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