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Effects of Bcl-2 Levels on Fas Signaling-Induced Caspase-3 Activation: Molecular Genetic Tests of Computational Model Predictions¹

Fei Hua^2,*, Melanie G. Cornejo^*, Michael H. Cardone, Cynthia L. Stokes and Douglas A. Lauffenburger^*,

^* 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

	Abstract

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 
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.

	Introduction

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Apoptosis is an essential cellular event for maintaining homeostasis of the immune system and its normal function. Dysregulation of apoptosis can contribute to various autoimmune diseases and cancer (1, 2). One major mechanism for inducing apoptosis is through the activation of death receptors such as TNF, Fas (Apo-1/CD95), DR3 (TRAMP), DR4 (TRAIL-R1), and DR5 (TRAIL-R2) (3, 4). Among death receptors, the signaling pathways for Fas-induced apoptosis are the best characterized (5) (Fig. 1). Two pathways activated by Fas have been identified (6), and are referred to as type I and type II pathways. For both pathways, caspases, a family of cysteine proteases, are crucial for both the initiation and execution of apoptosis. The pathways diverge after activation of initiator caspases (e.g., caspase-8 and caspase-10) and converge at the end by activating executor caspases (e.g., caspase-3). In the type I pathway, initiator caspases cleave and activate executor caspases directly. In the type II pathway, also called the mitochondrial pathway, a more complex signaling cascade is activated involving the disruption of mitochondrial membrane potential. Fas signaling is tightly regulated at multiple steps along both signaling cascades (2, 4, 5, 7). For instance, FLIP blocks activation of initiator caspases, Bcl-2 prevents mitochondrial disruption, and X-linked inhibitor of apoptosis protein (XIAP)³ inhibits downstream caspases (i.e., caspase-9 and caspase-3).

View larger version (26K): [in this window] [in a new window]   FIGURE 1. Schematic representation of the Fas signaling pathway. Molecules in bold are used in the model to represent two or more molecules with similar functions.

We first use model simulations with experiments to explore how the protein Bcl-2 regulates Fas signaling. Bcl-2 has been found to be a potent inhibitor of apoptosis in response to a variety of cytotoxic stimuli. It inhibits apoptosis through the mitochondrial pathway by preventing disruption of the mitochondria and the subsequent release of cytochrome c. Consequently, overexpression of Bcl-2 has a protective effect against Fas-induced apoptosis in cells in which the type II pathway is dominant, but not in cells in which the type I pathway is dominant (6). However, the exact mechanisms by which Bcl-2 protects the mitochondrial pathway are not clear. Conflicting results have shown that Bcl-2 may or may not interact with Bid, truncated Bid (tBid), Bax, and Bak (9, 10, 11, 12). This question could be approached experimentally using coimmunoprecipitation to observe which molecules coprecipitate with Bcl-2, or by staining multiple molecules to look for colocalization with microscopy techniques. However, both experimental methods can give ambiguous results due to their intricate nature, and they are limited by the lack of good Abs against tBid. Furthermore, neither approach is able to capture transient protein-protein interactions.

In this study, we use our Fas signaling model to explore four potential Bcl-2 mechanisms of action: Bcl-2 binding to Bax, Bid, or tBid individually, or both Bax and tBid. By examining the dynamic behavior of the system, the model suggests a simple experiment to differentiate the four hypotheses. Combining our model predictions with the experimental measurements, we discern that Bcl-2 interaction with both Bax and tBid is the most likely, as well as the most efficient, mechanism for Bcl-2 to block the mitochondrial pathway. Analysis of the model also suggests an explanation for potential insensitivity to Bcl-2 down-regulation.

In addition, we analyze how the model output for caspase-3 activation depends on signaling molecule levels to gain insight into the overall regulation of the Fas signaling pathway. The results show a prevalent phenomenon where increasing or decreasing the level of a molecule can have an asymmetrical effect on signaling outcome. Finally, we demonstrate that our model is capable of switching from the type II pathway dominant behavior (sensitive to Bcl-2 up-regulation) to the type I pathway dominant behavior (insensitive to Bcl-2 up-regulation) by simply increasing the level of caspase-8, while keeping the network structure unchanged.

	Materials and Methods

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Cells and reagents

Human tumor T cell line, Jurkat.E6, was purchased from American Type Culture Collection. Recombinant human SuperFasL was purchased from Alexis. For Western blot, rabbit anti-Bcl-2 polyclonal Ab was purchased from R&D Systems; rabbit anti-caspase-3 mAb was purchased from Santa Cruz Biotechnology; anti-tubulin mAb was obtained from Sigma-Aldrich. HRP-conjugated secondary Ab anti-mouse and anti-rabbit were purchased from Santa Cruz Biotechnology. PE-conjugated anti-Bcl-2 mAb (556536) and anti-active caspase-3 mAb (559565) used for intracellular staining were both purchased from BD Pharmingen. Fluor 647-conjugated anti-rabbit IgG Ab (A31573) was purchased from Molecular Probes.

Quantitative Western blot analysis

Resting or Fas ligand (FasL)-stimulated cells were washed once with ice-cold PBS, then lysed as described previously (13). Lysates from same number of cells were loaded in each lane. Proteins were separated on 12% polyacrylamide gel, then transferred to a polyvinylidene difluoride membrane. The reactive bands were detected by chemiluminescence (PerkinElmer) and captured with Kodak Image Station (Kodak). Band density was quantified using a Kodak 1D Image Analysis Software (Kodak). The linearity of the chemiluminescent signal was tested by a serial dilution of lysates. Measurements were always done within the linear range of the signal.

Intracellular staining of cleaved caspase-3 and Bcl-2

Resting or stimulated cells were fixed with 4% paraformaldehyde for 10 min at room temperature, followed by permeabilization with 100% MeOH overnight at –20°C. Cells were washed twice with PBS + 0.1% Tween (PBST) before incubating with anti-active caspase-3 (BD Pharmingen) for 1 h. Cells were washed twice again with PBST, then incubated with Fluor 647-conjugated anti-rabbit and PE-conjugated anti-Bcl-2 mAb at room temperature for 1 h in the dark. After two more washes with PBST, cells were analyzed on a FACSCalibur machine (BD Biosciences). For experiments to differentiate low and high amounts of Bcl-2 expression, cells were first gated on the level of Bcl-2, then gated on active caspase-3. The percentage of cells negative in active caspase-3 (i.e., percentage of cells with full-length caspase-3) were measured and normalized using the following formula: (percentage of cells negative in active caspase-3 with stimulation)/(percentage of cells negative in active caspase-3 without stimulation).

Cytotoxicity assay

Cells at density of 1 x 10⁶ cells/ml were incubated in the culture medium with different concentrations of FasL in 96-well plates for 24 h. Cells were washed once with ice-cold PBS and resuspended in 5 µg/ml propidium iodide (PI), after which cells were immediately analyzed on a FACScan machine (BD Biosciences). Specific cell death was calculated using the formula: (percentage of total cell death – percentage of spontaneous death)/(100% – percentage of spontaneous death), where percentage of spontaneous death is the percentage of cell death without adding any stimulation.

Genetic manipulations

Stably transduced cell lines were generated as described previously (14, 15). Briefly, the Ca²⁺ precipitation method was used to transfect 293T cells. Supernatants collected 48 and 72 h after transfection were used to infect Jurkat cells. To overexpress Bcl-2, the MIG-Bcl2 vector was cotransfected with CMV-gag/pol and VSVG packaging vectors (15). To down-regulate Bcl-2, a short hairpin RNA sequence was selected and cloned into pll3.7 vector (14). The targeting sequence for Bcl-2 short hairpin RNA is GTGATGAAGTACATCCATT. pll3.7-Bcl2 was cotransfected with VSVG, RSV-REV, and pMDL g/p RRE. Empty MIG or pll3.7 vector was used as a control, respectively. Because both MIG and pll3.7 vectors contain enhanced GFP reporter gene, successfully infected cells were identified with green fluorescence. GFP-positive populations were sorted using FACStarPlus (BD Biosciences), and only the sorted cells were used for experiments.

Mathematical model

Model structure. A schematic representation of the Fas signaling network described by our computational model is shown in Fig. 1. The model starts with FasL binding to Fas and concludes at caspase-3 activation because the latter results in the cleavage of many important cellular substrates, leading to morphological changes that are typically associated with apoptosis. In the model, both Fas and FasL are preassociated as trimers (16, 17). Once FasL binds to Fas, the complex recruits Fas-associated death domain (FADD), which then recruits caspase-8, forming a death-inducing signaling complex (DISC) (18). Because the stoichiometry and type of molecular interactions at the DISC are not clear, we assumed 1:1 noncooperative interactions between Fas and FADD, and between FADD and caspase-8, with up to three FADD and three caspase-8 molecules recruited to the DISC. When two (or more) caspase-8 molecules are recruited to the DISC, they cleave each other, generating an intermediate cleavage product p43/41, which further cleaves itself to generate activated caspase-8. Although caspase-10 can also be recruited to the DISC and may have redundant function with caspase-8, caspase-8 is included in our model as a functional surrogate for the combined effect.

Activated caspase-8 either cleaves and activates caspase-3 directly (type I pathway) or cleaves Bid into tBid to initialize the type II pathway. tBid recruits two Bax molecules, which leads to the release of cytochrome c and second mitochondria-activator of caspase (Smac) from the mitochondria. Bak and Bax have been shown to be redundant in tBid-induced cytochrome c release (19); therefore, we use Bax in the model to represent the combined functionality of both molecules. Subsequently, cytochrome c binds to Apaf-1 and two caspase-9 molecules in the presence of ATP, forming the apoptosome. Caspase-9 becomes activated in the apoptosome and then activates caspase-3. Smac released from the mitochondria can bind to XIAP. Several IAP molecules (XIAP, cIAP-1, cIAP-2) have been implicated in the regulation of apoptosis. We selected XIAP to represent the functionality of the IAP family because it has the highest binding affinity to caspases (20).

There are three negative regulators in this model: FLIP, Bcl-2, and XIAP. FLIP competes with caspase-8 to bind FADD, thereby preventing caspase-8 activation and inhibiting both the type I and II pathways. Bcl-2 in the model represents the net functionality of both Bcl-2 and Bcl-x_L, and functions to inhibit the type II pathway. The molecular mechanism by which Bcl-2 exerts this effect is unclear, and four separate hypotheses were analyzed. The initial model has Bcl-2 binding to Bax only. Alternative models include Bcl-2 binding to Bid alone, tBid alone, or Bax plus tBid. XIAP, the third negative regulator binds to both caspase-9 and active caspase-3 (20).

Model simulation. The model describing the signal transduction of the Fas pathway was created using Entelos PhysioLab Modeler (Entelos). Biochemical reactions were used to describe the molecular interactions. Most of the interactions were described with the following class of mass-action equation:

(1)

where k_f is forward rate constant and k_r is reverse rate constant. Concentration changes of all the molecules were described by ordinary differential equations (ODEs):

(2)

Enzymatic reactions were split into two reactions, with k_f of the second one being 0:

(3)

The equations for Smac and cytochrome c release are different to represent transport processes, where the release of molecules depends on the amount of oligomerized Bax, but does not bind to oligomerized Bax:

(4)

where A is either the concentration of Smac or cytochrome c in mitochondria, A* is the concentration of the same molecule in cytosol, and B is the concentration of oligomerized Bax. It is an irreversible reaction, and the concentration changes were described by the following ODEs:

(5)

All the equations used in the model are listed in Table I. Fig. 2 is a graphical representation of all the biochemical reactions used for the model with Bcl-2 binding to Bax only.

View larger version (31K): [in this window] [in a new window]   FIGURE 2. Translating the Fas signaling pathway into biochemical reactions in the model. Molecules in blue are directly involved in Fas signaling; molecules in red are negative regulators of the pathway; and molecules in black are transient intermediate complexes. Arrows in red represent catalytic reactions, and arrows in green represent transport processes as described in Materials and Methods. Blue shaded area encloses steps for DISC formation, where the molecule FLIP or caspase-8 is omitted for most reactions. The model is shown here with Bcl-2 binding to Bax only.

Parameter estimation and model evaluation with experimentally measured kinetic data. Approximately one-third of the parameter values (rate constants and initial conditions) used in the model were taken from the literature or obtained through unpublished observations (Tables II and III). The remaining parameters were manually adjusted within an expected physiological range so that the model reproduced the behavior of Jurkat cells in the presence of 100 ng/ml FasL. More specifically, forward rate constants were limited to the range between 1 x 10^–6 and 1 x 10^–1 (diffusion limit) nM^–1s^–1; reverse rate constants were limited to 1 x10 ^–5 to 10 s^–1. The data used to tune the model were time-dependent reductions of caspase-8 and caspase-3 measured from Jurkat cells using quantitative Western blot assay (Fig. 3). The mean values of three experiments were used for model fitting. As seen in Fig. 3, C and D, the model can accurately represent the dynamics of both an upstream (caspase-8) and a downstream (caspase-3) signal in response to FasL stimulation. All the resulting rate constants are listed in Table II, and the initial conditions are listed in Table III. These values are referred to as baseline values.

View larger version (31K): [in this window] [in a new window]   FIGURE 3. Model fitting. A and B, Representative Western blot showing the time course of caspase-8 (A) and caspase-3 (B) activation following stimulation of 100 ng/ml FasL in Jurkat cells. C and D, Good fit between model output and the experimental data for caspase-8 (C) and caspase-3 (D). The amount of full-length caspases averaged from three experiments was quantified and plotted vs time. Error bars represent SEM.

	Results

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Bcl-2 blocks the mitochondrial pathway by binding to both tBid and Bax/Bak

Bcl-2 is known to block the mitochondrial pathway; however, the exact mechanism by which Bcl-2 exerts its effect is still not clear. Our model is adjusted to describe the Fas signaling pathway in Jurkat cells, which are known to be sensitive to the overexpression of Bcl-2 (6, 21). Therefore, we could use this model to explore how different mechanisms of Bcl-2 blockage of the mitochondrial pathway may generate different dynamics of caspase-3 activation.

In our initial model, Bcl-2 binds to Bax; however, there are suggestions in the literature that Bcl-2 may bind to only Bid, only tBid, or both Bax and tBid (9, 10, 11, 12). To test these different hypotheses, we generated three new models, changing only the specific molecule interacting with Bcl-2. The initial concentration of Bcl-2, as well as the association and dissociation rate constants for Bcl-2 interacting with other molecules, was kept the same in all four models. For 100 ng/ml FasL stimulation, the four models show very similar kinetics of caspase-3 activation when Bcl-2 is at the baseline value (Fig. 4A). In contrast, when the Bcl-2 level is increased by 10 or 100 times (simulating its overexpression), caspase-3 activation kinetics are quite different for the four models (Fig. 4, B–E). The model with Bcl-2 binding to both Bax and tBid is the most sensitive to increases in Bcl-2, where only a 10-fold increase of Bcl-2 almost completely blocks the mitochondrial pathway (Fig. 4E). On the other hand, the model with Bcl-2 binding to Bax alone is somewhat less sensitive to Bcl-2 overexpression (Fig. 4B), whereas the model with Bcl-2 binding to Bid alone is the least sensitive (Fig. 4C). Because the effect of Bcl-2 binding to Bid is minimal, the model with Bcl-2 binding to both Bax and Bid gives results similar to those observed when Bcl-2 binds to Bax alone (data not shown).

View larger version (31K): [in this window] [in a new window]   FIGURE 4. Sensitivity of caspase-3 activation to increases in Bcl-2 level. Four models were generated that differed only in the molecule(s) to which Bcl-2 binds. A, Comparison of caspase-3 activation among all four models with Bcl-2 level at the baseline value. B–E, Kinetics of caspase-3 activation with a baseline amount of Bcl-2, 10 or 100 times increased Bcl-2 levels from the model with Bcl-2 binding to Bax only (B), Bid only (C), tBid only (D), or both Bax and tBid (E).

View larger version (20K): [in this window] [in a new window]   FIGURE 5. Effects of Bcl-2 overexpression on caspase-3 activation in Jurkat cells. A, Dose response to FasL-induced apoptosis in control cells transduced with empty MIG vector (•) or Bcl-2 overexpressing (OE) cells tranduced with MIG-Bcl-2 (). Cells were incubated with the indicated concentration of FasL for 24 h, after which apoptosis was measured by PI staining. B, Intracellular staining of Bcl-2 in control and Bcl-2-overexpressing cells. The two gates on the FACS plot indicate the low and high Bcl-2-overexpressing subpopulations, with the average fluorescence intensity shown for each population. C, Time course of caspase-3 activation following stimulation with 100 ng/ml FasL. Active caspase-3 was measured by intracellular staining with flow cytometry in control cells (•), the whole population of Bcl-2-overexpressing cells (), and subpopulations of low () and high () levels of Bcl-2-overexpressing-cells.

Based on these findings, all further simulations were done using the model with Bcl-2 binding to both Bax and tBid.

Insensitivity of Fas-induced apoptosis to a decrease in Bcl-2 expression level

Aberrant Bcl-2 expression has been identified in many different cancers (22). Treatments aimed at decreasing the level of Bcl-2, such as Bcl-2 antisense drugs and small molecule inhibitors of Bcl-2, have been explored as anticancer agents (22, 23). We tested whether the model can predict the effect of decreasing Bcl-2 on caspase-3 activation. Surprisingly, whereas overexpressing Bcl-2 in Jurkat cells slows caspase-3 activation, reducing the level of Bcl-2 using the RNA interference technique in Jurkat cells (Fig. 6A) neither increases the sensitivity to Fas-induced apoptosis (Fig. 6B) nor accelerates caspase-3 activation (Fig. 6C). Consistent with this experimental data, decreasing Bcl-2 by 10- or 100-fold in the model has only a minimal effect on caspase-3 activation (Fig. 6D).

View larger version (29K): [in this window] [in a new window]   FIGURE 6. Insensitivity of caspase-3 activation to Bcl-2 down-regulation demonstrated by both experiments and computational simulation. A, Western blot analysis for Bcl-2 and Bcl-xL in control cells transduced with empty pll3.7 vector or Bcl-2 knockdown (KD) cells tranduced with pll3.7-Bcl-2. Tubulin was used as a protein loading control. B, Dose response to FasL-induced apoptosis in control cells (•) and Bcl-2 knockdown cells (). Cells were incubated with the indicated concentrations of FasL for 24 h, after which apoptosis was measured by PI staining. C, Kinetics of caspase-3 activation following stimulation with 100 ng/ml FasL in control cells (•) and Bcl-2 knockdown cells () measured by intracellular staining with flow cytometry. D, Computer simulation of caspase-3 activation following a 10- or 100-fold decrease in Bcl-2 level.

Asymmetrical effects of varying expression levels of the Fas signaling network components

Using a computational model to predict the effects of increasing or decreasing a single component in the model is a mathematical technique termed "sensitivity analysis." If perturbation of a given molecule has a relatively large impact on the outcome, the system is considered to be sensitive to the level of this molecule. In the above studies, we increased and decreased the Bcl-2 level in the model to discern its effects on caspase-3 activation. Our associated overexpression and knockdown experimental studies tested the veracity of those predictions.

We applied this analytical technique to all of the molecular components of the model except caspase-3 by varying the initial concentration of each molecule by one and two orders of magnitude higher and lower than the baseline values. The half-time for caspase-3 activation is used to represent how fast caspase-3 becomes activated (Fig. 7). The faster the full-length caspase-3 level decreases, the shorter the half-time is, and vice versa. As described above, caspase-3 activation has an asymmetric sensitivity to Bcl-2, being sensitive to increases of Bcl-2, but not to decreases of Bcl-2. Similar asymmetric sensitivities are observed for many molecules. For example, caspase-3 activation is sensitive to increases in the levels of FLIP and XIAP, but not to decreases in these molecules. Conversely, caspase-3 activation is sensitive to decreases, but not increases in the levels of Apaf-1, cytochrome c, FADD, and Bid. Caspase-3 activation is sensitive to changes in caspase-8 and caspase-9 in both directions. These results suggest that because changes in Bax, caspase-9, Bcl-2, and XIAP most dramatically block caspase-3 activation, these molecules could be good targets for blocking Fas signaling and reducing apoptosis in cells that function similar to Jurkat cells. Conversely, the analysis predicts that the only efficient way to increase apoptosis in Jurkat cells is to increase caspase-8 or caspase-9 levels.

View larger version (24K): [in this window] [in a new window]   FIGURE 7. Sensitivity analysis for network model components. The expression level (initial condition for model calculations) of one component was changed for each simulation, while holding the others constant. Levels were changed one or two orders of magnitude in either direction from the baseline values. The half-time of caspase-3 activation is plotted to represent how fast caspase-3 becomes activated.

Human cells that are not sensitive to Bcl-2 overexpression have been identified in the literature (6, 24). In these cells, following FasL stimulation, caspase-3 is activated mostly through the type I pathway, such that even if the type II pathway is functioning normally in these cells, blocking it by Bcl-2 has only a minimal effect on caspase-3 activation. It has been suggested that the amount of active caspase-8 generated following FasL stimulation determines type I or type II dominancy (6, 24), reasoning that large amounts of activated caspase-8 can directly activate a sufficient amount of caspase-3 to induce death. In contrast, if only a small amount of caspase-8 is generated at the DISC, the type II pathway becomes essential to amplify the signal. To test this hypothesis in our model, we increased the formation of active caspase-8 by increasing the concentration of caspase-8 to 20 times the baseline value, while keeping everything else in the model unchanged (Fig. 8). This leads to faster caspase-3 activation kinetics (black line, compared to Fig. 4A). In addition, caspase-3 activation in this modified model becomes insensitive to a 100-fold increase in Bcl-2 (red line), which is the phenotype for the type I pathway dominant behavior. This consistency between the hypothesis and model simulation results both further validates the model and provides mechanistic validation for the hypothesis derived from experimental phenomenon.

View larger version (17K): [in this window] [in a new window]   FIGURE 8. Conversion of the model to type I pathway dominant behavior. Computer simulation of caspase-3 activation with Bcl-2 either at the baseline level or 100 times the baseline level when caspase-8 level in the model was increased by 20 times.

	Discussion

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Mechanisms of Bcl-2 blocking the type II pathway

Bcl-2 has been a promising target molecule for anticancer therapies (27), and a better understanding of its function should help in the development of effective drugs targeting its regulation of the mitochondrial pathway. Combining model predictions with experiments, our results support the hypothesis that Bcl-2 inhibits the type II pathway by binding to both Bax and tBid, giving a strong antiapoptotic effect of Bcl-2 compared with the other scenarios tested.

Consideration of signaling network kinetics provided us a new approach to differentiate different interaction possibilities using relatively simple experimental methods. Bid, BAX, Bcl-x_L, and Bcl-2 (28, 29, 30) all have similar three-dimensional structures (28, 29, 30), and the structures of Bid and tBid are also similar to one another (28). This structural similarity is likely to confound other possible approaches. For example, we expect it would be difficult to differentiate the binding preference of Bcl-x_L/Bcl-2 for Bid, tBid, and Bax according to structure information, and coimmunoprecipitation experiments are also likely to give false results.

Because many parameters in the model are adjusted to fit the kinetics of two molecules, we performed additional simulations to make sure this conclusion is not limited to the specific parameter set used in our study. Specifically, we changed forward and reverse rate constants of Bcl-2 binding and the initial conditions of Bax and Bid individually. We find that, although the models with these different parameter values do not fit to experimental data as well as using the baseline values, whenever Bcl-2 is able to effectively block the mitochondrial pathway with at least one of the mechanisms, Bcl-2 binding to both Bax and tBid is the most efficient mechanism compared with Bcl-2 binding to Bax, Bid, or tBid alone.

In addition to the hypotheses tested above, there are other possible mechanisms by which Bcl-2 may block the mitochondrial pathway. For example, Bcl-2 may gate a mitochondrial pore independent of Bax/Bak to prevent the movement of material into and out of the mitochondria (31); Bcl-2 may compete with Bax/Bak binding to a third molecule to regulate the release of cytochrome c; or Bcl-2 may sequester some unknown caspase activator, as is seen in the analogous Caenorhabditis elegans system (32). These questions could be addressed in the future with a similar combined modeling and experimental approach when more data supporting these hypothetical mechanisms become available.

Sensitivity analysis and the nonlinearity of caspase-3 activation dependence on signal molecule levels

Sensitivity analysis of Bcl-2 using our computer simulation, and subsequently confirmed by our experimental data, demonstrates that caspase-3 activation is not linearly dependent on Bcl-2 expression level. Such nonlinearity can explain why the results of overexpression of a molecule are not necessarily opposite to those observed when a molecule is underexpressed. Interestingly, the asymmetric effect of Bcl-2 may allow therapies aimed at decreasing Bcl-2 to have a specific effect on tumor cells, thereby sparing healthy cells. According to the model analysis, the insensitivity of Jurkat cells to Bcl-2 down-regulation is due to the low level of endogenous Bcl-2, which does not block the type II pathway significantly. However, in many tumor cells, Bcl-2 is aberrantly up-regulated to render tumor cells resistant to many apoptotic stimuli (22). In this case, decreasing Bcl-2 is equivalent to decreasing Bcl-2 from 10- or 100-fold of the baseline back to its original value, thus promoting cell death. At the same time, because normal and Jurkat cells both have low Bcl-2 levels, decreasing the level of Bcl-2 will have only a minimal effect on their apoptosis. Most anti-Bcl-2 drugs are being used to increase the efficiency of standard anticancer therapies. Although anti-Bcl-2 drugs will not affect the level of apoptosis in healthy cells caused by anticancer therapies, their coadministration should at least not aggravate this side effect.

Although the same sensitivity analysis, as described here for Bcl-2, could be done experimentally for all the molecules involved in the Fas signaling to identify potential drug targets, it would be extremely costly and time-consuming. Computer simulations using an experimentally validated model can help point out the most sensitive parts of a pathway, thereby identifying the key experiments most likely to generate interesting results.

The results of this sensitivity analysis explicitly depend on the baseline expression levels of all the molecules in the Fas signaling pathway. Because the baseline levels for some of the molecules might be different in different cell types, those other cell types may exhibit different sensitivities than those observed in our study.

Our sensitivity analysis of all the molecules involved in Fas signaling illustrates that the sensitivity of caspase-3 activation to the various molecules varies dramatically, and many signaling molecules have asymmetric effects on the signaling outcome. These results suggest that signaling cascades are highly nonlinear and nonintuitive. Consequently, understanding the kinetics of the overall signaling pathway using mathematical model is critical in understanding its regulation. More extensive discussions about the utility of models can be found elsewhere (26).

Limitations of the model and future improvements

Although our model describes many aspects of the Fas signaling system and, in particular, specific aspects of type II dominant signaling, there are limitations of the model. One discrepancy between our model and known biology is that, whereas the qualitative trends are similar, caspase-3 activation in the model is less sensitive to FasL concentration changes than has been reported experimentally. This may be due to the relatively simple ligand binding structure of the model and exclusion of endocytosis and receptor trafficking, both of which are known to modulate signaling dynamics in other receptor systems (e.g., epidermal growth factor receptor) (8). Extension of the model to address this issue is part of future model development.

More generally, there are various details in the Fas pathway that are not included in the current model. For example, we have not included the clustering of receptors on the cell membrane that occurs following Fas stimulation (33, 34), the phosphorylation-induced deactivation of Bcl-2 (35, 36), the regulation of the mitochondrial pathway by other Bcl-2 family members (27, 37), or the nonredundant functions of Bcl-2 and Bcl-xL (27, 30). Representing a simplified system at the beginning of a model's development follows a philosophy of question-oriented, iterative model development and validation. With this philosophy, each iteration of model development is focused on addressing particular research questions and includes careful and extensive validation. In this first iteration of our model, the focus is on reproducing only a few key system behaviors relevant to the problem of interest. The breadth and detail of its components and functions are limited to only those necessary to meet that goal. In future iterations, we must be cautious about expanding a model because it introduces more parameters and, if data are not available to assign them values, or at least constrain their values, they simply become free knobs for tuning the system that may provide too much flexibility to the model.

In summary, this study has demonstrated how the consideration of quantitative aspects and dynamics of a system, interpreted through a mathematical model and in collaboration with kinetics experiments, can provide additional understanding of a signaling system.

	Acknowledgments

 
We thank John Albeck and Dr. Suzanne Gaudet for useful discussion and technical help. We thank Liming Yang for her help making Bcl-2 knockdown construct. We are also grateful for Rayka Yokoo’s help with mathematical modeling.

	Disclosures

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The authors have no financial conflict of interest.

	Footnotes

¹ This work was partially supported by Entelos, and the National Institute of General Medical Sciences Cell Decision Processes Center at Massachusetts Institute of Technology.

² Address correspondence to Dr. Fei Hua, Building 56, Room 353, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139. E-mail address: fhua{at}mit.edu

³ Abbreviations used in this paper: XIAP, X-linked inhibitor of apoptosis protein; tBid, truncated Bid; FasL, Fas ligand; PI, propidium iodide; FADD, Fas-associated death domain; DISC, death-inducing signaling complex; Smac, second mitochondria-derived activator of caspase; ODE, ordinary differential equation.

Received for publication February 14, 2005. Accepted for publication May 3, 2005.

	References

Top Abstract Introduction Materials and Methods Results Discussion Disclosures References

 

1. Rieux-Laucat, F., F. Le Deist, A. Fischer. 2003. Autoimmune lymphoproliferative syndromes: genetic defects of apoptosis pathways. Cell Death Differ. 10: 124-133.[Medline]
2. Igney, F. H., P. H. Krammer. 2002. Death and anti-death: tumour resistance to apoptosis. Nat. Rev. Cancer 2: 277-288.[Medline]
3. Ashkenazi, A., V. M. Dixit. 1998. Death receptors: signaling and modulation. Science 281: 1305-1308.[Abstract/Free Full Text]
4. Schmitz, I., S. Kirchhoff, P. H. Krammer. 2000. Regulation of death receptor-mediated apoptosis pathways. Int. J. Biochem. Cell Biol. 32: 1123-1136.[Medline]
5. Nagata, S.. 1999. Fas ligand-induced apoptosis. Annu. Rev. Genet. 33: 29-55.[Medline]
6. Scaffidi, C., S. Fulda, A. Srinivasan, C. Friesen, F. Li, K. J. Tomaselli, K. M. Debatin, P. H. Krammer, M. E. Peter. 1998. Two CD95 (APO-1/Fas) signaling pathways. EMBO J. 17: 1675-1687.[Medline]
7. Riedl, S. J., Y. Shi. 2004. Molecular mechanisms of caspase regulation during apoptosis. Nat. Rev. Mol. Cell Biol. 5: 897-907.[Medline]
8. Wiley, H. S., S. Y. Shvartsman, D. A. Lauffenburger. 2003. Computational modeling of the EGF-receptor system: a paradigm for systems biology. Trends Cell Biol. 13: 43-50.[Medline]
9. Wang, K., X. M. Yin, D. T. Chao, C. L. Milliman, S. J. Korsmeyer. 1996. BID: a novel BH3 domain-only death agonist. Genes Dev. 10: 2859-2869.[Abstract/Free Full Text]
10. Oltvai, Z. N., C. L. Milliman, S. J. Korsmeyer. 1993. Bcl-2 heterodimerizes in vivo with a conserved homolog, Bax, that accelerates programmed cell death. Cell 74: 609-619.[Medline]
11. Cheng, E. H., M. C. Wei, S. Weiler, R. A. Flavell, T. W. Mak, T. Lindsten, S. J. Korsmeyer. 2001. BCL-2, BCL-X_L sequester BH3 domain-only molecules preventing BAX- and BAK-mediated mitochondrial apoptosis. Mol. Cell 8: 705-711.[Medline]
12. Mikhailov, V., M. Mikhailova, D. J. Pulkrabek, Z. Dong, M. A. Venkatachalam, P. Saikumar. 2001. Bcl-2 prevents Bax oligomerization in the mitochondrial outer membrane. J. Biol. Chem. 276: 18361-18364.[Abstract/Free Full Text]
13. Kelly, E., A. Won, Y. Refaeli, L. Van Parijs. 2002. IL-2 and related cytokines can promote T cell survival by activating AKT. J. Immunol. 168: 597-603.[Abstract/Free Full Text]
14. Rubinson, D. A., C. P. Dillon, A. V. Kwiatkowski, C. Sievers, L. Yang, J. Kopinja, D. L. Rooney, M. M. Ihrig, M. T. McManus, F. B. Gertler, et al 2003. A lentivirus-based system to functionally silence genes in primary mammalian cells, stem cells and transgenic mice by RNA interference. Nat. Genet. 33: 401-406.[Medline]
15. Hickman, M. J., L. D. Samson. 2004. Apoptotic signaling in response to a single type of DNA lesion, O⁶-methylguanine. Mol. Cell 14: 105-116.[Medline]
16. Siegel, R. M., J. K. Frederiksen, D. A. Zacharias, F. K. Chan, M. Johnson, D. Lynch, R. Y. Tsien, M. J. Lenardo. 2000. Fas preassociation required for apoptosis signaling and dominant inhibition by pathogenic mutations. Science 288: 2354-2357.[Abstract/Free Full Text]
17. Tanaka, M., T. Suda, T. Takahashi, S. Nagata. 1995. Expression of the functional soluble form of human fas ligand in activated lymphocytes. EMBO J. 14: 1129-1135.[Medline]
18. Kischkel, F. C., S. Hellbardt, I. Behrmann, M. Germer, M. Pawlita, P. H. Krammer, M. E. Peter. 1995. Cytotoxicity-dependent APO-1 (Fas/CD95)-associated proteins form a death-inducing signaling complex (DISC) with the receptor. EMBO J. 14: 5579-5588.[Medline]
19. Wei, M. C., W. X. Zong, E. H. Cheng, T. Lindsten, V. Panoutsakopoulou, A. J. Ross, K. A. Roth, G. R. MacGregor, C. B. Thompson, S. J. Korsmeyer. 2001. Proapoptotic BAX and BAK: a requisite gateway to mitochondrial dysfunction and death. Science 292: 727-730.[Abstract/Free Full Text]
20. Salvesen, G. S., C. S. Duckett. 2002. IAP proteins: blocking the road to death’s door. Nat. Rev. Mol. Cell Biol. 3: 401-410.[Medline]
21. Armstrong, R. C., T. Aja, J. Xiang, S. Gaur, J. F. Krebs, K. Hoang, X. Bai, S. J. Korsmeyer, D. S. Karanewsky, L. C. Fritz, K. J. Tomaselli. 1996. Fas-induced activation of the cell death-related protease CPP32 is inhibited by Bcl-2 and by ICE family protease inhibitors. J. Biol. Chem. 271: 16850-16855.[Abstract/Free Full Text]
22. Reed, J. C., T. Miyashita, S. Takayama, H. G. Wang, T. Sato, S. Krajewski, C. Aime-Sempe, S. Bodrug, S. Kitada, M. Hanada. 1996. BCL-2 family proteins: regulators of cell death involved in the pathogenesis of cancer and resistance to therapy. J. Cell. Biochem. 60: 23-32.[Medline]
23. Klasa, R. J., A. M. Gillum, R. E. Klem, S. R. Frankel. 2002. Oblimersen Bcl-2 antisense: facilitating apoptosis in anticancer treatment. Antisense Nucleic Acid Drug Dev. 12: 193-213.[Medline]
24. Barnhart, B. C., E. C. Alappat, M. E. Peter. 2003. The CD95 type I/type II model. Semin. Immunol. 15: 185-193.[Medline]
25. Fussenegger, M., J. E. Bailey, J. Varner. 2000. A mathematical model of caspase function in apoptosis. Nat. Biotechnol. 18: 768-774.[Medline]
26. Bentele, M., I. Lavrik, M. Ulrich, S. Stosser, D. W. Heermann, H. Kalthoff, P. H. Krammer, R. Eils. 2004. Mathematical modeling reveals threshold mechanism in CD95-induced apoptosis. J. Cell Biol. 166: 839-851.[Abstract/Free Full Text]
27. Cory, S., J. M. Adams. 2002. The Bcl2 family: regulators of the cellular life-or-death switch. Nat. Rev. Cancer 2: 647-656.[Medline]
28. Chou, J. J., H. Li, G. S. Salvesen, J. Yuan, G. Wagner. 1999. Solution structure of BID, an intracellular amplifier of apoptotic signaling. Cell 96: 615-624.[Medline]
29. McDonnell, J. M., D. Fushman, C. L. Milliman, S. J. Korsmeyer, D. Cowburn. 1999. Solution structure of the proapoptotic molecule BID: a structural basis for apoptotic agonists and antagonists. Cell 96: 625-634.[Medline]
30. Petros, A. M., A. Medek, D. G. Nettesheim, D. H. Kim, H. S. Yoon, K. Swift, E. D. Matayoshi, T. Oltersdorf, S. W. Fesik. 2001. Solution structure of the antiapoptotic protein bcl-2. Proc. Natl. Acad. Sci. USA 98: 3012-3017.[Abstract/Free Full Text]
31. Tsujimoto, Y., S. Shimizu. 2000. VDAC regulation by the Bcl-2 family of proteins. Cell Death Differ. 7: 1174-1181.[Medline]
32. Ottilie, S., Y. Wang, S. Banks, J. Chang, N. J. Vigna, S. Weeks, R. C. Armstrong, L. C. Fritz, T. Oltersdorf. 1997. Mutational analysis of the interacting cell death regulators CED-9 and CED-4. Cell Death Differ. 4: 526-533.[Medline]
33. Siegel, R. M., J. R. Muppidi, M. Sarker, A. Lobito, M. Jen, D. Martin, S. E. Straus, M. J. Lenardo. 2004. SPOTS: signaling protein oligomeric transduction structures are early mediators of death receptor-induced apoptosis at the plasma membrane. J. Cell Biol. 167: 735-744.[Abstract/Free Full Text]
34. Cremesti, A., F. Paris, H. Grassme, N. Holler, J. Tschopp, Z. Fuks, E. Gulbins, R. Kolesnick. 2001. Ceramide enables fas to cap and kill. J. Biol. Chem. 276: 23954-23961.[Abstract/Free Full Text]
35. Yamamoto, K., H. Ichijo, S. J. Korsmeyer. 1999. BCL-2 is phosphorylated and inactivated by an ASK1/Jun N-terminal protein kinase pathway normally activated at G₂/M. Mol. Cell. Biol. 19: 8469-8478.[Abstract/Free Full Text]
36. Scaffidi, C., J. Volkland, I. Blomberg, I. Hoffmann, P. H. Krammer, M. E. Peter. 2000. Phosphorylation of FADD/MORT1 at serine 194 and association with a 70-kDa cell cycle-regulated protein kinase. J. Immunol. 164: 1236-1242.[Abstract/Free Full Text]
37. Tsujimoto, Y.. 2003. Cell death regulation by the Bcl-2 protein family in the mitochondria. J. Cell. Physiol. 195: 158-167.[Medline]
38. Goltsev, Y. V., A. V. Kovalenko, E. Arnold, E. E. Varfolomeev, V. M. Brodianskii, D. Wallach. 1997. CASH, a novel caspase homologue with death effector domains. J. Biol. Chem. 272: 19641-19644.[Abstract/Free Full Text]
39. Pitti, R. M., S. A. Marsters, D. A. Lawrence, M. Roy, F. C. Kischkel, P. Dowd, A. Huang, C. J. Donahue, S. W. Sherwood, D. T. Baldwin, et al 1998. Genomic amplification of a decoy receptor for Fas ligand in lung and colon cancer. Nature 396: 699-703.[Medline]
40. Huang, Y., R. L. Rich, D. G. Myszka, H. Wu. 2003. Requirement of both the second and third BIR domains for the relief of X-linked inhibitor of apoptosis protein (XIAP)-mediated caspase inhibition by Smac. J. Biol. Chem. 278: 49517-49522.[Abstract/Free Full Text]
41. Renatus, M., H. R. Stennicke, F. L. Scott, R. C. Liddington, G. S. Salvesen. 2001. Dimer formation drives the activation of the cell death protease caspase 9. Proc. Natl. Acad. Sci. USA 98: 14250-14255.[Abstract/Free Full Text]
42. Boatright, K. M., M. Renatus, F. L. Scott, S. Sperandio, H. Shin, I. M. Pedersen, J. E. Ricci, W. A. Edris, D. P. Sutherlin, D. R. Green, G. S. Salvesen. 2003. A unified model for apical caspase activation. Mol. Cell 11: 529-541.[Medline]
43. Riedl, S. J., M. Renatus, R. Schwarzenbacher, Q. Zhou, C. Sun, S. W. Fesik, R. C. Liddington, G. S. Salvesen. 2001. Structural basis for the inhibition of caspase-3 by XIAP. Cell 104: 791-800.[Medline]
44. Letai, A., M. C. Bassik, L. D. Walensky, M. D. Sorcinelli, S. Weiler, S. J. Korsmeyer. 2002. Distinct BH3 domains either sensitize or activate mitochondrial apoptosis, serving as prototype cancer therapeutics. Cancer Cell 2: 183-192.[Medline]
45. Sun, X. M., S. B. Bratton, M. Butterworth, M. MacFarlane, G. M. Cohen. 2002. Bcl-2 and Bcl-x_L inhibit CD95-mediated apoptosis by preventing mitochondrial release of Smac/DIABLO and subsequent inactivation of X-linked inhibitor-of-apoptosis protein. J. Biol. Chem. 277: 11345-11351.[Abstract/Free Full Text]

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