IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0088167.html
   My bibliography  Save this article

Constructing the Energy Landscape for Genetic Switching System Driven by Intrinsic Noise

Author

Listed:
  • Cheng Lv
  • Xiaoguang Li
  • Fangting Li
  • Tiejun Li

Abstract

Genetic switching driven by noise is a fundamental cellular process in genetic regulatory networks. Quantitatively characterizing this switching and its fluctuation properties is a key problem in computational biology. With an autoregulatory dimer model as a specific example, we design a general methodology to quantitatively understand the metastability of gene regulatory system perturbed by intrinsic noise. Based on the large deviation theory, we develop new analytical techniques to describe and calculate the optimal transition paths between the on and off states. We also construct the global quasi-potential energy landscape for the dimer model. From the obtained quasi-potential, we can extract quantitative results such as the stationary distributions of mRNA, protein and dimer, the noise strength of the expression state, and the mean switching time starting from either stable state. In the final stage, we apply this procedure to a transcriptional cascades model. Our results suggest that the quasi-potential energy landscape and the proposed methodology are general to understand the metastability in other biological systems with intrinsic noise.

Suggested Citation

  • Cheng Lv & Xiaoguang Li & Fangting Li & Tiejun Li, 2014. "Constructing the Energy Landscape for Genetic Switching System Driven by Intrinsic Noise," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
  • Handle: RePEc:plo:pone00:0088167
    DOI: 10.1371/journal.pone.0088167
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0088167
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0088167&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0088167?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ertugrul M. Ozbudak & Mukund Thattai & Han N. Lim & Boris I. Shraiman & Alexander van Oudenaarden, 2004. "Multistability in the lactose utilization network of Escherichia coli," Nature, Nature, vol. 427(6976), pages 737-740, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hao Ge & Pingping Wu & Hong Qian & Xiaoliang Sunney Xie, 2018. "Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-24, March.
    2. Rowan D Brackston & Eszter Lakatos & Michael P H Stumpf, 2018. "Transition state characteristics during cell differentiation," PLOS Computational Biology, Public Library of Science, vol. 14(9), pages 1-24, September.
    3. Ye, Yusong & Yang, Zhuoqin & Zhang, Zili, 2016. "Opinion evolution and rare events in an open community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1178-1188.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Avraham E Mayo & Yaakov Setty & Seagull Shavit & Alon Zaslaver & Uri Alon, 2006. "Plasticity of the cis-Regulatory Input Function of a Gene," PLOS Biology, Public Library of Science, vol. 4(4), pages 1-1, March.
    2. Lai, Qiang & Norouzi, Benyamin & Liu, Feng, 2018. "Dynamic analysis, circuit realization, control design and image encryption application of an extended Lü system with coexisting attractors," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 230-245.
    3. Tomas Tokar & Jozef Ulicny, 2013. "The Mathematical Model of the Bcl-2 Family Mediated MOMP Regulation Can Perform a Non-Trivial Pattern Recognition," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-8, December.
    4. Paul Miller & Anatol M Zhabotinsky & John E Lisman & Xiao-Jing Wang, 2005. "The Stability of a Stochastic CaMKII Switch: Dependence on the Number of Enzyme Molecules and Protein Turnover," PLOS Biology, Public Library of Science, vol. 3(4), pages 1-1, March.
    5. Matthieu Wyart & David Botstein & Ned S Wingreen, 2010. "Evaluating Gene Expression Dynamics Using Pairwise RNA FISH Data," PLOS Computational Biology, Public Library of Science, vol. 6(11), pages 1-14, November.
    6. Georg Fritz & Judith A Megerle & Sonja A Westermayer & Delia Brick & Ralf Heermann & Kirsten Jung & Joachim O Rädler & Ulrich Gerland, 2014. "Single Cell Kinetics of Phenotypic Switching in the Arabinose Utilization System of E. coli," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-12, February.
    7. Najme Khorasani & Mehdi Sadeghi & Abbas Nowzari-Dalini, 2020. "A computational model of stem cell molecular mechanism to maintain tissue homeostasis," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-25, July.
    8. Jan Hasenauer & Christine Hasenauer & Tim Hucho & Fabian J Theis, 2014. "ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-17, July.
    9. Tobias May & Lee Eccleston & Sabrina Herrmann & Hansjörg Hauser & Jorge Goncalves & Dagmar Wirth, 2008. "Bimodal and Hysteretic Expression in Mammalian Cells from a Synthetic Gene Circuit," PLOS ONE, Public Library of Science, vol. 3(6), pages 1-7, June.
    10. Song, Yi & Xu, Wei & Wei, Wei & Niu, Lizhi, 2023. "Dynamical transition of phenotypic states in breast cancer system with Lévy noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).
    11. Chen, Aimin & Tian, Tianhai & Chen, Yiren & Zhou, Tianshou, 2022. "Stochastic analysis of a complex gene-expression model," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    12. Zhou, Peipei & Cai, Shuiming & Liu, Zengrong & Chen, Luonan & Wang, Ruiqi, 2013. "Coupling switches and oscillators as a means to shape cellular signals in biomolecular systems," Chaos, Solitons & Fractals, Elsevier, vol. 50(C), pages 115-126.
    13. Navneet Rai & Rajat Anand & Krishna Ramkumar & Varun Sreenivasan & Sugat Dabholkar & K V Venkatesh & Mukund Thattai, 2012. "Prediction by Promoter Logic in Bacterial Quorum Sensing," PLOS Computational Biology, Public Library of Science, vol. 8(1), pages 1-14, January.
    14. Li, Chunbiao & Sprott, Julien Clinton & Kapitaniak, Tomasz & Lu, Tianai, 2018. "Infinite lattice of hyperchaotic strange attractors," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 76-82.
    15. Marco Montalva-Medel & Thomas Ledger & Gonzalo A. Ruz & Eric Goles, 2021. "Lac Operon Boolean Models: Dynamical Robustness and Alternative Improvements," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    16. Xiu-Deng Zheng & Xiao-Qian Yang & Yi Tao, 2011. "Bistability, Probability Transition Rate and First-Passage Time in an Autoactivating Positive-Feedback Loop," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-10, March.
    17. Ermelinda Porpiglia & Daniel Hidalgo & Miroslav Koulnis & Abraham R Tzafriri & Merav Socolovsky, 2012. "Stat5 Signaling Specifies Basal versus Stress Erythropoietic Responses through Distinct Binary and Graded Dynamic Modalities," PLOS Biology, Public Library of Science, vol. 10(8), pages 1-19, August.
    18. Hao Ge & Pingping Wu & Hong Qian & Xiaoliang Sunney Xie, 2018. "Relatively slow stochastic gene-state switching in the presence of positive feedback significantly broadens the region of bimodality through stabilizing the uninduced phenotypic state," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-24, March.
    19. Carl Song & Hilary Phenix & Vida Abedi & Matthew Scott & Brian P Ingalls & Mads Kærn & Theodore J Perkins, 2010. "Estimating the Stochastic Bifurcation Structure of Cellular Networks," PLOS Computational Biology, Public Library of Science, vol. 6(3), pages 1-11, March.
    20. Shintaro Nagata & Macoto Kikuchi, 2020. "Emergence of cooperative bistability and robustness of gene regulatory networks," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-24, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0088167. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.