| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
* Center for Cancer Research and Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, MA 02139; Merrimack Pharmaceuticals, Cambridge, MA 02142; and Entelos, Foster City, CA 94404
Fas-induced apoptosis is a critical process for normal immune system development and function. Although many molecular components in the Fas signaling pathway have been identified, a systematic understanding of how they work together to determine network dynamics and apoptosis itself has remained elusive. To address this, we generated a computational model for interpreting and predicting effects of pathway component properties. The model integrates current information concerning the signaling network downstream of Fas activation, through both type I and type II pathways, until activation of caspase-3. Unknown parameter values in the model were estimated using experimental data obtained from human Jurkat T cells. To elucidate critical signaling network properties, we examined the effects of altering the level of Bcl-2 on the kinetics of caspase-3 activation, using both overexpression and knockdown in the model and experimentally. Overexpression was used to distinguish among alternative hypotheses for inhibitory binding interactions of Bcl-2 with various components in the mitochondrial pathway. In comparing model simulations with experimental results, we find the best agreement when Bcl-2 blocks the release of cytochrome c by binding to both Bax and truncated Bid instead of Bax, truncated Bid, or Bid alone. Moreover, although Bcl-2 overexpression strongly reduces caspase-3 activation, Bcl-2 knockdown has a negligible effect, demonstrating a general model finding that varying the expression levels of signal molecules frequently has asymmetric effects on the outcome. Finally, we demonstrate that the relative dominance of type I vs type II pathways can be switched by varying particular signaling component levels without changing network structure.
Related articles in The JI:
This article has been cited by other articles:
|
|
 |
|
  S. Raychaudhuri, E. Willgohs, T.-N. Nguyen, E. M. Khan, and T. Goldkorn Monte Carlo Simulation of Cell Death Signaling Predicts Large Cell-to-Cell Stochastic Fluctuations through the Type 2 Pathway of Apoptosis Biophys. J., October 15, 2008; 95(8): 3559 - 3562. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. E. Shoemaker and F. J. Doyle III Identifying Fragilities in Biochemical Networks: Robust Performance Analysis of Fas Signaling-Induced Apoptosis Biophys. J., September 15, 2008; 95(6): 2610 - 2623. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Chen, J. Cui, H. Lu, R. Wang, S. Zhang, and P. Shen Modeling of the Role of a Bax-Activation Switch in the Mitochondrial Apoptosis Decision Biophys. J., June 15, 2007; 92(12): 4304 - 4315. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Miller-Jensen, K. A. Janes, Y.-L. Wong, L. G. Griffith, and D. A. Lauffenburger Adenoviral vector saturates Akt pro-survival signaling and blocks insulin-mediated rescue of tumor-necrosis-factor-induced apoptosis J. Cell Sci., September 15, 2006; 119(18): 3788 - 3798. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
