Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Parameter sensitivity analysis of IL-6 signalling pathways

Parameter sensitivity analysis of IL-6 signalling pathways

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Systems Biology — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Signal transduction pathways generally consist of a large number of individual components and have an even greater number of parameters describing their reaction kinetics. Although the structure of some signalling pathways can be found in the literature, many of the parameters are not well known and they would need to be re-estimated from experimental data for each specific case. However it is not feasible to estimate hundreds of parameters because of the cost of the experiments associated with generating data. Parameter sensitivity analysis can address this situation as it investigates how the system behaviour is changed by variations of parameters and the analysis identifies which parameters play a key role in signal transduction. Only these important parameters need then be re-estimated using data from further experiments. This article presents a detailed parameter sensitivity analysis of the JAK/STAT and MAPK signal transduction pathway that is used for signalling by the cytokine IL-6. As no parameter sensitivity analysis technique is known to work best for all situations, a comparison of the results returned by four techniques is presented: differential analysis, the Morris method, a sampling-based approach and the Fourier amplitude sensitivity test. The recruitment of the transcription factor STAT3 to the dimer of the phosphorylated receptor complex is determined as the most important step by the sensitivity analysis. Additionally, the desphosphorylation of the nuclear STAT3 dimer by PP2 as well as feedback inhibition by SOCS3 are found to play an important role for signal transduction.

References

    1. 1)
      • H.C. Frey , S.R. Patil . Identification and review of sensitivity analysis methods. Risk Anal. , 3 , 553 - 578
    2. 2)
      • R. Haspel , M. Salditt-Georgieff , J.E. Darnell . The rapid inactivation of nuclear tyrosine phosphorylated Stat1 depends upon a protein tyrosine phosphatase. Embo J. , 22 , 6262 - 6268
    3. 3)
    4. 4)
    5. 5)
      • B. Schoeberl , C. Eichler-Jonsson , E.D. Gilles , G. Muller . Computational modeling of the dynamics of the MAP kinase cascade activated by surface and internalized EGF receptors. Nat. Biotechnol. , 370 - 375
    6. 6)
      • J.T. Hwang , E.P. Dougherty , S. Rabitz , H. Rabitz . Greens function method of sensitivity analysis in chemical-kinetics. J. Chem. Phys. , 11 , 5180 - 5191
    7. 7)
      • P.M. Frank . (1978) Introduction to system sensitivity theory.
    8. 8)
      • C. Detre , E. Kiss , Z. Varga , K. Ludanyi , K. Paszty , A. Enyedi , D. Kovesdi , G. Panyi , E. Rajnavolgyi , J. Matko . Death or survival: membrane ceramide controls the fate and activation of antigen-specific T-cells depending on signal strength and duration. Cell Signal. , 3 , 294 - 306
    9. 9)
      • A. Saltelli , K. Chan , E.M. Scott . (2000) Sensitivity analysis.
    10. 10)
      • A. Saltelli , S. Tarantola , K.P.S. Chan . A quantitative model-independent method for global sensitivity analysis of model output. Technometrics , 1 , 39 - 56
    11. 11)
    12. 12)
      • B.P. Ingalls , H.M. Sauro . Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories. J. Theor. Biol. , 1 , 23 - 36
    13. 13)
      • Z.K. Zi , K.H. Cho , M.H. Sung , X.F. Xia , J.S. Zheng , Z.R. Sun . In silico identification of the key components and steps in INF-γ induced JAK-STAT signaling pathway. FEBS Lett. , 1101 - 1108.
    14. 14)
      • U. Lehmann , J. Schmitz , M. Weissenbach , R.M. Sobota , M. Hortner , K. Friederichs , I. Behrmann , W. Tsiaris , A. Sasaki , J. Schneider-Mergener , A. Yoshimura , B.G. Neel , P.C. Heinrich , F. Schaper . SHP2 and SOCS3 contribute to Tyr-759-dependent attenuation of interleukin-6 signaling through gp130. J. Biol. Chem. , 1 , 661 - 671
    15. 15)
      • C.Y. Huang , J.E. Ferrell . Ultrasensitivity in the mitogen-activated protein kinase cascade. Proc. Natl Acad. Sci. USA , 19 , 10078 - 10083
    16. 16)
      • G.M. Hornberger , R.C. Spear . An approach to the preliminary-analysis of environmental systems. J. Environ. Manage , 1 , 7 - 18
    17. 17)
      • I. Aksan , M.L. Kurnaz . A computer-based model for the regulation of mitogen activated protein kinase (MAPK) activation. J. Recept. Signal Transduct. , 197 - 209
    18. 18)
    19. 19)
      • A.R. Asthagiri , D.A. Lauffenburger . A computational study of feedback effects on signal dynamics in a mitogen activated protein kinase (MAPK) pathway model. Biotechnol. Prog. , 227 - 239
    20. 20)
      • A. Hoffmann , A. Levchenko , M.L. Scott , D. Baltimore . The IκB-NF-κB signaling module: temporal control and selective gene activation. Science , 1241 - 1245
    21. 21)
      • K.H. Cho , S.Y. Shin , W. Kolch , O. Wolkenhauer . Experimental design in systems biology, based on parameter sensitivity analysis using a Monte Carlo method: A case study for the TNFα-mediated NF-κB signal transduction pathway. Simul. Trans. Soc. Model. Simul. Int. , 12 , 726 - 739
    22. 22)
    23. 23)
    24. 24)
      • A. Saltelli , M. Ratto , S. Tarantola , F. Campolongo . Sensitivity analysis for chemical models. Chem. Rev. , 7 , 2811 - 2827
    25. 25)
      • J. Schmitz , M. Weissenbach , S. Haan , P.C. Heinrich , F. Schaper . SOCS3 exerts its inhibitory function on interleuking-6 signal transduction through SHP2 recruitment site of gp130. J. Biol. Chem. , 17 , 12848 - 12856
    26. 26)
      • A. Saltelli , S. Tarantola , F. Campolongo , M. Ratto . (2004) Sensitivity analysis in practice: a guide to assessing scientific models.
    27. 27)
      • A.K. Singh , A. Jayaraman , J. Hahn . Modeling regulatory mechanisms in IL-6 signal transduction in hepatocytes. Biotechnol. Bioeng. , 5 , 850 - 862
    28. 28)
      • I. Swameye , T.G. Muller , J. Timmer , O. Sandra , U. Klingmuller . Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling. Proc. Natl Acad. Sci. USA , 3 , 1028 - 1033
    29. 29)
      • P.C. Heinrich , I. Behrmann , S. Haan , H.M. Hermanns , G. Muller-Newen , F. Schaper . Principles of interleukin (IL)-6-type cytokine signalling and its regulation. Biochem. J. , 1 - 20
    30. 30)
      • S. Yamada , S. Shiono , A. Joo , A. Yoshimura . Control mechanism of JAK/STAT signal transduction pathway. FEBS Lett. , 190 - 196
    31. 31)
      • M.D. McKay , R.J. Beckman , W.J. Conover . A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics , 1 , 55 - 61
    32. 32)
      • G. Liu , M.T. Swihart , S. Neelamegham . Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling. Bioinformatics , 7 , 1194 - 1202
    33. 33)
      • R.L. Iman , J.C. Helton , J.E. Campbell . An approach to sensitivity analysis of computer models, Part 1. Introduction, input variable selection and preliminary variable assessment. J. Qual. Technol. , 3 , 174 - 183
    34. 34)
    35. 35)
      • C.J. Marshall . Specificity of receptor tyrosine kinase signaling: transient versus sustained extracellular signal-regulated activation. Cell , 179 - 185
    36. 36)
      • D.W. Hu , J.M. Yuan . Time-dependent sensitivity analysis of biological networks: coupled MAPK and PI3K signal transduction pathways. J. Phys. Chem. A , 16 , 5361 - 5370
    37. 37)
    38. 38)
      • I. Turanyi . Sensitivity analysis of complex kinetic systems – tools and applications. J. Math. Chem. , 3 , 203 - 248
    39. 39)
      • U. Sommer , C. Schmid , R.M. Sobota , U. Lehmann , N.J. Stevenson , J.A. Johnston , F. Schaper , P.C. Heinrich , S. Haan . Mechanisms of SOCS3 phosphorylation upon interleukin-6 stimulation. J. Biol. Chem. , 36 , 31478 - 31488
    40. 40)
    41. 41)
      • M. Bentele , I. Lavrik , M. Ulrich , S. Stosser , D.W. Heermann , H. Kalthoff , P.H. Krammer , R. Eils . Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis. J. Cell Biol. , 6 , 839 - 852
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-syb_20060053
Loading

Related content

content/journals/10.1049/iet-syb_20060053
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address