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Sci. Signal., 27 March 2012
[DOI: 10.1126/scisignal.2002469]

Supplementary Materials for:

A Dynamic Network Model of mTOR Signaling Reveals TSC-Independent mTORC2 Regulation

Piero Dalle Pezze, Annika G. Sonntag, Antje Thien, Mirja T. Prentzell, Markus Gödel, Sven Fischer, Elke Neumann-Haefelin, Tobias B. Huber, Ralf Baumeister, Daryl P. Shanley,* Kathrin Thedieck*

*To whom correspondence should be addressed. E-mail: kathrin.thedieck{at}biologie.uni-freiburg.de (K.T.); daryl.shanley{at}newcastle.ac.uk (D.P.S.)

This PDF file includes:

  • Fig. S1. Extended graphical model of the mammalian TOR network.
  • Fig. S2. A linear relationship between Western blot signals and protein concentrations.
  • Fig. S3. Phases of the calibration process.
  • Fig. S4. Details of a calibration phase.
  • Fig. S5. Identifiability analysis for the general model.
  • Fig. S6. Sensitivity analysis for the general model.
  • Fig. S7. Comparison between the simulated and experimental time courses for hypotheses 1, 2, and 3 for readouts of the mTOR network.
  • Fig. S8. Identifiability analysis for hypothesis 1: TSC1-TSC2–dependent hypothesis mTORC2 regulation.
  • Fig. S9. Sensitivity analysis for hypothesis 1: TSC1-TSC2–dependent hypothesis mTORC2 regulation.
  • Fig. S10. Identifiability analysis for hypothesis 2: NFL-mTORC2 regulation.
  • Fig. S11. Sensitivity analysis for hypothesis 2: NFL-mTORC2 regulation.
  • Fig. S12. Identifiability analysis for hypothesis 3: PI3K-independent mTORC2 regulation.
  • Fig. S13. Sensitivity analysis for hypothesis 3: PI3K-independent mTORC2 regulation.
  • Fig. S14. The influence of perturbations of TSC1-TSC2, mTORC1, and PI3K on the phosphorylation of Akt-T308 for the three hypotheses.
  • Fig. S15. The influence of perturbations of TSC1-TSC2, mTORC1, and PI3K on the phosphorylation of p70-S6K-T389 for the three hypotheses.
  • Fig. S16. Simulation and perturbations for the new network structure based on hypothesis 4: PI3K-dependent, NFL-independent regulation of mTORC2.
  • Fig. S17. Identifiability analysis for hypothesis 4: PI3K-dependent, NFL-independent regulation of mTORC2.
  • Fig. S18. Sensitivity analysis for hypothesis 4: PI3K-dependent, NFL-independent regulation of mTORC2.
  • Table S1. Ordinary differential equations of the general model and the models representing hypotheses, 1, 2, and 3 for mTORC2 activation.
  • Table S2. Parameter values of the general model.
  • Table S3. Parameter values of hypotheses 1, 2, and 3.
  • Table S4. Summary of model goodness of fit.
  • Legends for Models S1 to S6.

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Other Supplementary Material for this manuscript includes the following:

  • Models S1 to S6 (.xml format).

[Download Models S1 to S6 (Compressed)]

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Citation: P. Dalle Pezze, A. G. Sonntag, A. Thien, M. T. Prentzell, M. Gödel, S. Fischer, E. Neumann-Haefelin, T. B. Huber, R. Baumeister, D. P. Shanley, K. Thedieck, A Dynamic Network Model of mTOR Signaling Reveals TSC-Independent mTORC2 Regulation. Sci. Signal. 5, ra25 (2012).

© 2012 American Association for the Advancement of Science


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