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Unravelling the Sensitivity of Two Motif Structures Under Random Perturbation

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Trends in Biomathematics: Modeling, Optimization and Computational Problems

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Abstract

The aim of the present study is to capture the sensitivity of two frequently observed motif structures under stochastic perturbation. The study is done by building stochastic differential equation (SDE) models for these two motif structures. The use of motif structure in defining noise-signal relation can then be used to filter signals from noise in signalling pathway. Knowledge on the sensitivity nature of nodes can then be explored further in screening potential candidates for drug targets. The results obtained will be especially useful in diseases such as cancer, diabetes, obesity that cause complex perturbations in cellular signalling networks.

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References

  1. U. Alon, Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007)

    Article  Google Scholar 

  2. C.P. Bagowski, J.E. Ferrell Jr., Bistability in the JNK cascade. Curr. Biol. 11, 1176–1182 (2001)

    Article  Google Scholar 

  3. Y. Bar-Yam, I.R. Epstein, Response of complex networks to stimuli. Proc. Natl. Acad. Sci. USA 101, 4341–4345 (2004)

    Article  MathSciNet  Google Scholar 

  4. U.S. Bhalla, R. Iyengar, Emergent properties of networks of biological signaling pathways. Science 283, 381–387 (1999)

    Article  Google Scholar 

  5. U.S. Bhalla, P.T. Ram, R. Iyengar, MAP kinase phosphatase as a locus of flexibility in a mitogen-activated protein kinase signaling network. Science 297, 1018–1023 (2002)

    Article  Google Scholar 

  6. R.P. Bhattacharyya, A. Remenyi, B.J. Yeh, W.A. Lim, Domains, motifs, and scaffolds: the role of modular interactions in the evolution and wiring of cell signaling circuits. Annu. Rev. Biochem. 75, 655–680 (2006)

    Article  Google Scholar 

  7. M.J. Bissell, D. Radisky, Putting tumours in context. Nat. Rev. Cancer 1, 46–54 (2001)

    Article  Google Scholar 

  8. S.M. Blower, H. Dowlatabadi, Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example. Int. Stat. Rev. 62, 229–243 (1994)

    Article  Google Scholar 

  9. O. Brandman, T. Meyer, Feedback loops shape cellular signals in space and time. Science 322, 390–395 (2008)

    Article  MathSciNet  Google Scholar 

  10. O. Brandman, J.E. Ferrell Jr., R. Li, T. Meyer, Interlinked fast and slow positive feedback loops drive reliable cell decisions. Science 310, 496–498 (2005)

    Article  MathSciNet  Google Scholar 

  11. F.J. Bruggeman, N. Bluthgen, H.V. Westerhoff, Noise management by molecular networks. PLoS Comput. Biol. 5, e1000506 (2009)

    Article  MathSciNet  Google Scholar 

  12. M. Carletti, On the stability properties of a stochastic model for phage-bacteria interaction in open marine environment. Math. Biosci. 175, 117–131 (2002)

    Article  MathSciNet  Google Scholar 

  13. T. Eissing, H. Conzelmann, E.D. Gilles, F. Allgower, E. Bullinger, P. Scheurich, Bistability analyses of a caspase activation model for receptor-induced apoptosis. J. Biol. Chem. 279(35), 36892–36897 (2004)

    Article  Google Scholar 

  14. J.E. Ferrell Jr., Self-perpetuating states in signal transduction: positive feedback, double-negative feedback and bistability. Curr. Opin. Cell Biol. 14, 140–148 (2002)

    Article  Google Scholar 

  15. J.E. Ferrell Jr., R.R. Bhatt, Mechanistic studies of the dual phosphorylation of mitogen-activated protein kinase. J. Biol. Chem. 272, 19008–19016 (1997)

    Article  Google Scholar 

  16. A. Ghaffarizadeh, N.S. Flann, G.J. Podgorski, Multistable switches and their role in cellular differentiation networks. BMC Bioinf. 15(Suppl. 7), S7 (2014)

    Google Scholar 

  17. L.H. Hartwell, J.J. Hopfield, S. Leibler, A.W. Murray, From molecular to modular cell biology. Nature 402, C47–52 (1999)

    Article  Google Scholar 

  18. T. Helikar, J. Konvalina, J. Heidel, J.A. Rogers, Emergent decision-making in biological signal transduction networks. Proc. Natl. Acad. Sci. USA 105, 1913–1918 (2008)

    Article  Google Scholar 

  19. Q.A. Justman, Z. Serber, J.E. Ferrell Jr., H. El-Samad, K.M. Shokat, Tuning the activation threshold of a kinase network by nested feedback loops. Science 324, 509–512 (2009)

    Article  Google Scholar 

  20. B.N. Kholodenko, Cell-signalling dynamics in time and space. Nat. Rev. Mol. Cell Biol. 7, 165–176 (2006)

    Article  Google Scholar 

  21. D. Kumar, R. Srikanth, H. Ahlfors, R. Lahesmaa, K.V. Rao, Capturing cell-fate decisions from the molecular signatures of a receptor-dependent signaling response. Mol. Syst. Biol. 3, 150 (2007)

    Article  Google Scholar 

  22. W. Ma, A. Trusina, H. El-Samad, W.A. Lim, C. Tang, Defining network topologies that can achieve biochemical adaptation. Cell 138, 760–773 (2009)

    Article  Google Scholar 

  23. S. Mangan, U. Alon, Structure and function of the feed-forward loop network motif. Proc. Natl. Acad. Sci. USA 100, 11980–11985 (2003)

    Article  Google Scholar 

  24. L.A. Martinez, Y. Chen, S.M. Fischer, C.J. Conti, Coordinated changes in cell cycle machinery occur during keratinocyte terminal differentiation. Oncogene 18, 397–406 (1999)

    Article  Google Scholar 

  25. N. Nagumo, Uber die Lage der Integralkurven gewonlicher Dierantialgleichungen. Proc. Phys. Math. Soc. Jpn. 24, 551 (1942)

    MATH  Google Scholar 

  26. S.H. Strogatz, Exploring complex networks. Nature 410, 268–276 (2001)

    Article  Google Scholar 

  27. G. Weng, U.S. Bhalla, R. Iyengar, Complexity in biological signaling systems. Science 284, 92–96 (1999)

    Article  Google Scholar 

  28. T. Wilhelm, The smallest chemical reaction system with bistability. BMC Syst. Biol. 3, 90 (2009)

    Article  Google Scholar 

  29. J.W. Williams, X. Cui, A. Levchenko, A.M. Stevens, Robust and sensitive control of a quorum-sensing circuit by two interlocked feedback loops. Mol. Syst. Biol. 4, 234 (2008)

    Article  Google Scholar 

  30. H.C. Yen, Q. Xu, D.M. Chou, Z. Zhao, S.J. Elledge, Global protein stability profiling in mammalian cells. Science 322, 918–923 (2008)

    Article  Google Scholar 

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Acknowledgements

This work is supported by DBT (Govt. of India), Grant no. BT/PR13086/ BRB/10/1380/2015. Samrat Chatterjee thanks to the International Union of Biological Sciences (IUBS) for partial support of living expenses in Moscow, during the 17th BIOMAT International Symposium, October 29–November 04, 2017.

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Authors and Affiliations

  1. Drug Discovery Research Centre, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, India

    Suvankar Halder & Samrat Chatterjee

  2. Centre for Mathematical Biology and Ecology, Department of Mathematics, Jadavpur University, Kolkata, India

    Nandadulal Bairagi

Authors
  1. Suvankar Halder
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  2. Samrat Chatterjee
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  3. Nandadulal Bairagi
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Corresponding author

Correspondence to Samrat Chatterjee .

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Editors and Affiliations

  1. Federal University of Rio de Janeiro, President, BIOMAT Consortium – International Institute for Interdisciplinary Sciences, Rio de Janeiro, Brazil, Rio de Janeiro, Brazil

    Rubem P. Mondaini

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Halder, S., Chatterjee, S., Bairagi, N. (2018). Unravelling the Sensitivity of Two Motif Structures Under Random Perturbation. In: Mondaini, R. (eds) Trends in Biomathematics: Modeling, Optimization and Computational Problems. Springer, Cham. https://doi.org/10.1007/978-3-319-91092-5_17

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