Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Energy Cost and Mean Dwell Times for the Activity of Promoter with Complex Structure

  • Published:
Journal of Systems Science and Complexity Aims and scope Submit manuscript

Abstract

Regulatory molecules present on the core promoter of a gene interact often in a dynamic, highly combinatorial and possibly energy-dependent manner, leading to complex promoter structure and even complex global dynamics. The authors analyze dynamics of an arbitrarily complex promoter from the view of thermodynamics combined with statistic physics. First, the authors formulize transcription factors-mediated promoter kinetics in terms of energy. Then, the authors analyze energetic cost in several representative cases of promoter structure, deriving useful analytical results. Third, the authors derive analytical expressions for mean dwell times of the promoter activity states, experimentally measurable quantities related to the energy cost of promoter dynamics. The overall framework lays a theoretical foundation for analysis of complex promoter kinetics and gene expression dynamics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Vilar J M G and Saiz L, CplexA: A mathematica package to study macromolecular-assembly control of gene expression, Bioinformatics, 2010, 26: 2060–2061.

    Article  Google Scholar 

  2. Hornung G, Bar-Ziv R, Rosin D, et al., Noise-mean relationship in mutated promoters, Genome Research, 2012, 22: 2409–2417.

    Article  Google Scholar 

  3. Halme A, Bumgarner S, Styles C, et al., Genetic and epigenetic regulation of the FLO gene family generates cell-surface variation in yeast, Cell, 2004, 116: 405–415.

    Article  Google Scholar 

  4. Octavio L M, Gedeon K, and Maheshri N, Epigenetic and conventional regulation is distributed among activators of FLO11 allowing tuning of population-level heterogeneity in its expression, PLoS Genetics, 2009, 5: e1000673.

    Google Scholar 

  5. Weinberger L, Voichek Y, Tirosh I, et al., Expression noise and acetylation profiles distinguish HDAC functions, Molecular Cell, 2012, 47: 193–202.

    Article  Google Scholar 

  6. Eldar A and Elowitz M B, Functional roles for noise in genetic circuits, Nature, 2010, 467: 167–173.

    Article  Google Scholar 

  7. McNally J, Müller W, Walker D, et al., The glucocorticoid receptor: rapid exchange with regulatory sites in living cells, Science, 2000, 287: 1262–1265.

    Article  Google Scholar 

  8. Becker M, Baumann C, John S, et al., Dynamic behavior of transcription factors on a natural promoter in living cells, EMBO Reports, 2002, 3: 1188–1194.

    Article  Google Scholar 

  9. Phair R, Scaffdi P, Elbi C, et al., Global nature of dynamic protein-chromatin interactions in vivo: Three-dimensional genome scanning and dynamic interaction networks of chromatin proteins, Molecule Cell Biology, 2004, 24: 6393–6402.

    Article  Google Scholar 

  10. Karpova T S, Kim M J, Spriet C, et al., Concurrent fast and slow cycling of a transcriptional activator at an endogenous promoter, Science, 2008, 319: 466–469.

    Article  Google Scholar 

  11. Shang Y, Hu X, DiRenzo J, et al., Cofactor dynamics and sufficiency in estrogen receptorregulated transcription, Cell, 2000, 103: 843–852.

    Article  Google Scholar 

  12. Mtivier R, Penot G, Hubner M, et al., Estrogen receptor-alpha directs ordered, cyclical, and combinatorial recruitment of cofactors on a natural target promoter, Cell, 2003, 115: 751–763.

    Article  Google Scholar 

  13. Nagaich A, Walker D, Wolford R, et al., Rapid periodic binding and displacement of the glucocorticoid receptor during chromatin remodeling, Molecular Cell, 2004, 14: 163–174.

    Article  Google Scholar 

  14. Degenhardt T, Rybakova K N, Tomaszewska A, et al., Population-level transcription cycles derive from stochastic timing of single-cell transcription, Cell, 2009, 138: 489–501.

    Article  Google Scholar 

  15. Mtivier R, Reid G, and Gannon F, Transcription in four dimensions: Nuclear receptor-directed initiation of gene expression, EMBO Reports, 2006, 7: 161–167.

    Article  Google Scholar 

  16. Hager G, Elbi C, Johnson T, et al., Chromatin dynamics and the evolution of alternate promoter states, Chromosome Research, 2006, 14: 107–116.

    Article  Google Scholar 

  17. Misteli T, Beyond the sequence: Cellular organization of genome function, Cell, 2007, 128: 787–800.

    Article  Google Scholar 

  18. Browning D and Busby S, The regulation of bacterial transcription initiation, Nature Review Microbiology, 2004, 2: 57–65.

    Article  Google Scholar 

  19. Dodd I, Shearwin K, Perkins A, et al., Cooperativity in long-range gene regulation by the lambda CI repressor, Genes Development, 2004, 18: 344–354.

    Article  Google Scholar 

  20. Adams C and Workman J, Binding of disparate transcriptional activators to nucleosomal DNA is inherently cooperative, Molecule Cell Biology, 1995, 15: 1405–1421.

    Article  Google Scholar 

  21. Agresti A, Scaffidi P, Riva A, et al., GR and HMGB1 interact only within chromatin and influence each other’s residence time, Molecular Cell, 2005, 18: 109–121.

    Article  Google Scholar 

  22. Mellor J, Dynamic nucleosomes and gene transcription, Trends Genet, 2006, 22: 320–329.

    Article  Google Scholar 

  23. Li B, Carey M, and Workman J, The role of chromatin during transcription, Cell, 2007, 128: 707–719.

    Article  Google Scholar 

  24. Ackers G, Johnson A, and Shea M, Quantitative model for gene regulation by lambda phage repressor, Proceedings of National Academy of Sciences of the United States of America, 1982, 79: 1129–1133.

    Article  Google Scholar 

  25. Bintu L, Buchler N, Garcia H, et al., Transcriptional regulation by the numbers: Models, Current Opinion in Genetic Development, 2005, 15: 116–124.

    Article  Google Scholar 

  26. Coulon A, Gandrillon O, and Beslon G, On the spontaneous stochastic dynamics of a single gene: Complexity of the molecular interplay at the promoter, BMC Systems Biology, 2010, 4: 2.

    Article  Google Scholar 

  27. Vilar J and Saiz L, DNA looping in gene regulation: From the assembly of macromolecular complexes to the control of transcriptional noise, Current Opinion in Genetic Development, 2005, 15: 136–144.

    Article  Google Scholar 

  28. Saiz L and Vilar J, Stochastic dynamics of macromolecular-assembly networks, Molecular Systems Biology, 2006, 2(1): 20060024.

    Google Scholar 

  29. Raser J and O’Shea E, Control of stochasticity in eukaryotic gene expression, Science, 2004, 304: 1811–1814.

    Article  Google Scholar 

  30. Ge H and Qian H, The physical origins of entropy production, free energy dissipation and their mathematical representations, Physical Review E, 2009, 81: 561–578.

    Google Scholar 

  31. Zhang J J, Chen J J, and Zhou T S, Analytical distribution and tunability of noise in a model of promoter progress, Biophysical Journal, 2012, 102: 1247–1257.

    Article  Google Scholar 

  32. Pedraza J and Paulsson J, Effects of molecular memory and bursting on fluctuations in gene expression, Science, 2008, 319: 339–343.

    Article  Google Scholar 

  33. Gillespie D T, Exact stochastic simulation of coupled chemical-reactions, Journal of Physical Chemistry, 1977, 81: 2340–2361.

    Article  Google Scholar 

  34. Zhang J J and Zhou T S, Promoter-mediated transcriptional dynamics, Biophysical Journal, 2014, 106: 479–488.

    Article  Google Scholar 

  35. Zhou T S and Zhang J S, Analytical results for a multistate gene model, SIAM Journal of Applied Mathematics, 2010, 72: 789–818.

    Article  MathSciNet  MATH  Google Scholar 

  36. Tu Y, The nonequilibrium mechanism for ultrasensitivity in a biological switch: Sensing by Maxwell’s demons, Proceedings of National Academy of Sciences of the United States of America, 2008, 105: 11737–11741.

    Article  Google Scholar 

  37. Li G and Qian H, Kinetic timing: A novel mechanism that improves the accuracy of GTPase timers in endosome fusion and other biological processes, Traffic, 2002, 3: 249–255.

    Article  Google Scholar 

  38. Mehta P and Schwab D J, Energetic costs of cellular computation, Proceedings of National Academy of Sciences of the United States of America, 2012, 109: 17978–17982.

    Article  Google Scholar 

  39. Qian H, Phosphorylation energy hypothesis: Open chemical systems and their biological functions, Annual Review of Physical Chemistry, 2007, 58: 113–142.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Guangdong Province Key Laboratory of Computational Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, 510275, China

    Qingqing Li, Anwarud Din & Tianshou Zhou

Authors
  1. Qingqing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anwarud Din
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tianshou Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tianshou Zhou.

Additional information

This research was supported by Science and Technology Department under Grant No. 2014CB964703 and the Natural Science Foundation under Grant Nos. 91530320 and 11761025.

This paper was recommended for publication by Editor HU Xiaoming.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Q., Din, A. & Zhou, T. Energy Cost and Mean Dwell Times for the Activity of Promoter with Complex Structure. J Syst Sci Complex 32, 510–525 (2019). https://doi.org/10.1007/s11424-018-7180-2

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11424-018-7180-2

Keywords

Search

Navigation