Stable maintenance of hidden switches as a strategy to increase the gene expression stability.

Journal

Nature computational science

ISSN: 2662-8457

Titre abrégé: Nat Comput Sci

Pays: United States

ID NLM: 101775476

Informations de publication

Date de publication:
Jan 2021

Historique:

received: 30 05 2020

accepted: 02 11 2020

medline: 1 1 2021

pubmed: 1 1 2021

entrez: 13 1 2024

Statut: ppublish

Résumé

In response to severe genetic and environmental perturbations, wild-type organisms can express hidden alternative phenotypes adaptive to such adverse conditions. While our theoretical understanding of the population-level fitness advantage and evolution of phenotypic switching under variable environments has grown, the mechanism by which these organisms maintain phenotypic switching capabilities under static environments remains to be elucidated. Here, using computational simulations, we analyzed the evolution of gene circuits under natural selection and found that different strategies evolved to increase the gene expression stability near the optimum level. In a population comprising bistable individuals, a strategy of maintaining bistability and raising the potential barrier separating the bistable regimes was consistently taken. Our results serve as evidence that hidden bistable switches can be stably maintained during environmental stasis-an essential property enabling the timely release of adaptive alternatives with small genetic changes in the event of substantial perturbations.

Identifiants

DOI: 10.1038/s43588-020-00001-y PMID: 38217152

pubmed: 38217152

doi: 10.1038/s43588-020-00001-y

pii: 10.1038/s43588-020-00001-y

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

62-70

Subventions

Organisme : King Abdullah University of Science and Technology (KAUST)

ID : FCC/1/1976-26

Organisme : King Abdullah University of Science and Technology (KAUST)

ID : BAS/1/1624-01

Informations de copyright

Références

Waddington, C. H. Canalization of development and the inheritance of acquired characters. Nature 150, 563–565 (1942).

doi: 10.1038/150563a0

Waddington, C. H. Genetic assimilation of an acquired character. Evolution 7, 118–126 (1953).

doi: 10.2307/2405747

Schmalhausen I. I., Dordick I. & Dobzhansky T. Factors of Evolution: The Theory of Stabilizing Selection (Univ. Chicago Press, 1987).

Gibson, G. & Wagner, G. Canalization in evolutionary genetics: a stabilizing theory? Bioessays 22, 372–380 (2000).

doi: 10.1002/(SICI)1521-1878(200004)22:4<372::AID-BIES7>3.0.CO;2-J

West-Eberhard, M. J. Toward a modern revival of Darwin’s theory of evolutionary novelty. Phil. Sci. 75, 899–908 (2008).

doi: 10.1086/594533

Félix, M. A. & Barkoulas, M. Pervasive robustness in biological systems. Nat. Rev. Genet. 16, 483–496 (2015).

doi: 10.1038/nrg3949

West-Eberhard, M. J. Phenotypic plasticity and the origins of diversity. Annu. Rev. Ecol. Syst. 20, 249–278 (1989).

doi: 10.1146/annurev.es.20.110189.001341

Suzuki, Y. & Nijhout, H. F. Evolution of a polyphenism by genetic accommodation. Science 311, 650–652 (2006).

doi: 10.1126/science.1118888

Eldar, A. et al. Partial penetrance facilitates developmental evolution in bacteria. Nature 460, 510–514 (2009).

doi: 10.1038/nature08150

Raj, A., Rifkin, S. A., Andersen, E. & van Oudenaarden, A. Variability in gene expression underlies incomplete penetrance. Nature 463, 913–918 (2010).

doi: 10.1038/nature08781

Specchia, V. et al. Hsp90 prevents phenotypic variation by suppressing the mutagenic activity of transposons. Nature 463, 662–665 (2010).

doi: 10.1038/nature08739

West-Eberhard, M. J. Developmental Plasticity and Evolution (Oxford Univ. Press, 2003).

Masel, J., King, O. D. & Maughan, H. The loss of adaptive plasticity during long periods of environmental stasis. Am. Nat. 169, 38–46 (2007).

doi: 10.1086/510212

Kærn, M., Elston, T., Blake, W. & Collins, J. Stochasticity in gene expression: from theories to phenotypes. Nat. Rev. Genet. 6, 451–464 (2005).

doi: 10.1038/nrg1615

Raser, J. M. & O’Shea, E. K. Noise in gene expression: origins, consequences, and control. Science 309, 2010–2013 (2005).

doi: 10.1126/science.1105891

Losick, R. & Desplan, C. Stochasticity and cell fate. Science 320, 65–68 (2008).

doi: 10.1126/science.1147888

Raj, A. & van Oudenaarden, A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell 135, 216–226 (2008).

doi: 10.1016/j.cell.2008.09.050

Acar, M., Mettetal, J. T. & van Oudenaarden, A. Stochastic switching as a survival strategy in fluctuating environments. Nat. Genet. 40, 471–475 (2008).

doi: 10.1038/ng.110

Capp, J. P. Noise-driven heterogeneity in the rate of genetic-variant generation as a basis for evolvability. Genetics 185, 395–404 (2010).

doi: 10.1534/genetics.110.118190

Johnston, R. J. Jr & Desplan, C. Stochastic mechanisms of cell fate specification that yield random or robust outcomes. Annu. Rev. Cell Dev. Biol. 26, 689–719 (2010).

doi: 10.1146/annurev-cellbio-100109-104113

Kuwahara, H. & Soyer, O. S. Bistability in feedback circuits as a byproduct of evolution of evolvability. Mol. Syst. Biol. 8, 564 (2012).

doi: 10.1038/msb.2011.98

Becskei, A., Séraphin, B. & Serrano, L. Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion. EMBO J. 20, 2528–2535 (2001).

doi: 10.1093/emboj/20.10.2528

Thattai, M. & Van Oudenaarden, A. Stochastic gene expression in fluctuating environments. Genetics 167, 523–530 (2004).

doi: 10.1534/genetics.167.1.523

Salathé, M., Van Cleve, J. & Feldman, M. W. Evolution of stochastic switching rates in asymmetric fitness landscapes. Genetics 182, 1159–1164 (2009).

doi: 10.1534/genetics.109.103333

Balázsi, G., van Oudenaarden, A. & Collins, J. J. Cellular decision making and biological noise: from microbes to mammals. Cell 144, 910–925 (2011).

doi: 10.1016/j.cell.2011.01.030

Liberman, U., Van Cleve, J. & Feldman, M. W. On the evolution of mutation in changing environments: recombination and phenotypic switching. Genetics 187, 837–851 (2011).

doi: 10.1534/genetics.110.123620

Bedford, T. & Hartl, D. L. Optimization of gene expression by natural selection. Proc. Natl Acad. Sci. USA 106, 1133–1138 (2009).

doi: 10.1073/pnas.0812009106

Ozbudak, E. M., Thattai, M., Kurtser, I., Grossman, A. D. & van Oudenaarden, A. Regulation of noise in the expression of a single gene. Nat. Genet. 31, 69–73 (2002).

doi: 10.1038/ng869

Lachmann, M. & Jablonka, E. The inheritance of phenotypes: an adaptation to fluctuating environments. J. Theor. Biol. 181, 1–9 (1996).

doi: 10.1006/jtbi.1996.0109

Meyers, L. A., Ancel, F. D. & Lachmann, M. Evolution of genetic potential. PLoS Comput. Biol. 1, 236–243. (2005).

Zhang, Z., Qian, W. & Zhang, J. Positive selection for elevated gene expression noise in yeast. Mol. Syst. Biol. 5, 299 (2009).

doi: 10.1038/msb.2009.58

Bintu, L. et al. Transcriptional regulation by the numbers: models. Curr. Opin. Genet. Dev. 15, 116–124 (2005).

doi: 10.1016/j.gde.2005.02.007

Kuwahara, H. et al. in Transactions on Computational Systems Biology VI (eds Priami, C. & Plotkin, G.) 150–175 (Springer, 2006).

Gunawardena, J. Time-scale separation—Michaelis and Menten’s old idea, still bearing fruit. FEBS J. 281, 473–488 (2014).

doi: 10.1111/febs.12532

Acar, M., Becskei, A. & van Oudenaarden, A. Enhancement of cellular memory by reducing stochastic transitions. Nature 435, 228–232 (2005).

doi: 10.1038/nature03524

Xiong, W. & Ferrell, J. E. Jr A positive-feedback-based bistable’memory module’ that governs a cell fate decision. Nature 426, 460–465 (2003).

doi: 10.1038/nature02089

Lestas, I., Vinnicombe, G. & Paulsson, J. Fundamental limits on the suppression of molecular fluctuations. Nature 467, 174–178 (2010).

doi: 10.1038/nature09333

Thattai, M. & van Oudenaarden, A. Intrinsic noise in gene regulatory networks. Proc. Natl Acad. Sci. USA 98, 8614–8619 (2001).

doi: 10.1073/pnas.151588598

Kuwahara, H., Arold, S. T. & Gao, X. Beyond initiation-limited translational bursting: the effects of burst size distributions on the stability of gene expression. Integr. Biol. 7, 1622–1632 (2015).

doi: 10.1039/c5ib00107b

Duveau, F. et al. Fitness effects of altering gene expression noise in Saccharomyces cerevisiae. eLife 7, e37272 (2018).

doi: 10.7554/eLife.37272

Gibson, G. & Dworkin, I. Uncovering cryptic genetic variation. Nat. Rev. Genet. 5, 681–690 (2004).

doi: 10.1038/nrg1426

Nevozhay, D., Adams, R. M., Van Itallie, E., Bennett, M. R. & Balázsi, G. Mapping the environmental fitness landscape of a synthetic gene circuit. PLoS Comput. Biol. 8, e1002480 (2012).

doi: 10.1371/journal.pcbi.1002480

González, C. et al. Stress-response balance drives the evolution of a network module and its host genome. Mol. Syst. Biol. 11, 827 (2015).

doi: 10.15252/msb.20156185

Kheir Gouda, M., Manhart, M. & Balázsi, G. Evolutionary regain of lost gene circuit function. Proc. Natl Acad. Sci. USA 116, 25162–25171 (2019).

doi: 10.1073/pnas.1912257116

Pujadas, E. & Feinberg, A. P. Regulated noise in the epigenetic landscape of development and disease. Cell 148, 1123–1131 (2012).

doi: 10.1016/j.cell.2012.02.045

Gillespie, D. T. Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81, 2340–2361 (1977).

doi: 10.1021/j100540a008

Friedman, N., Cai, L. & Xie, X. S. Linking stochastic dynamics to population distribution: an analytical framework of gene expression. Phys. Rev. Lett. 97, 168302 (2006).

doi: 10.1103/PhysRevLett.97.168302

Kuwahara, H. Simulation tool and data analysis scripts for the study of stable maintenance of bistable switch under static environments (version 0.16). Zenodo https://doi.org/10.5281/zenodo.4120179 (2020).