The intrinsic, or mitochondrial, pathway of caspase activation is essential for apoptosis induction by various stimuli including cytotoxic stress. It depends on the cellular context, whether cytochrome c released from mitochondria induces caspase activation gradually or in an all-or-none fashion, and whether caspase activation irreversibly commits cells to apoptosis. By analyzing a quantitative kinetic model, we show that inhibition of caspase-3 (Casp3) and Casp9 by inhibitors of apoptosis (IAPs) results in an implicit positive feedback, since cleaved Casp3 augments its own activation by sequestering IAPs away from Casp9. We demonstrate that this positive feedback brings about bistability (i.e., all-or-none behaviour), and that it cooperates with Casp3-mediated feedback cleavage of Casp9 to generate irreversibility in caspase activation. Our calculations also unravel how cell-specific protein expression brings about the observed qualitative differences in caspase activation (gradual versus all-or-none and reversible versus irreversible). Finally, known regulators of the pathway are shown to efficiently shift the apoptotic threshold stimulus, suggesting that the bistable caspase cascade computes multiple inputs into an all-or-none caspase output. As cellular inhibitory proteins (e.g., IAPs) frequently inhibit consecutive intermediates in cellular signaling cascades (e.g., Casp3 and Casp9), the feedback mechanism described in this paper is likely to be a widespread principle on how cells achieve ultrasensitivity, bistability, and irreversibility. Multicellular organisms eliminate damaged or excess cells by programmed cell death, also known as apoptosis. By modelling the signaling pathways involved in the initiation of apoptosis, the authors provide insight into how cells prevent spontaneous apoptosis, but yet efficiently enter cell death, once proapoptotic signals exceed a threshold. The simulations also explain how cells accurately translate a complex set of pro- and anti-apoptotic signals into a life-or-death decision. Once apoptosis has been initiated, cellular demise must irreversibly proceed even if the initial trigger is removed, as partial cellular disintegration might lead to tissue inflammation or cellular deregulation. The authors explain how such irreversible commitment arises in the initiation pathways of apoptosis and provide experimentally testable predictions. Finally, the simulations reveal an unanticipated role for the inhibitor of apoptosis family of proteins, as these proteins are predicted to be involved in the amplification of death signals and not only in their suppression.

Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal‐regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin‐induced increase in the phosphatidylinositol‐3,4,5‐triphosphate (PIP3) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin‐induced amplification of mitogenic signaling is abolished by disrupting PIP3‐mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non‐linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues. We present an integrated analysis of crosstalk between the insulin receptor (IR) and epidermal growth factor receptor (EGFR) signaling pathways. Our experimental and computational findings show how systems‐level interactions between the EGFR and IR networks convert the insulin‐induced increase in the phosphatidylinositol‐3,4,5‐triphosphate (PIP3) concentration into enhanced activity of the extracellular signal‐regulated kinase (ERK) pathway. Physiological stimuli never act in isolation, and often cells in the body are simultaneously exposed to EGF and insulin. The EGFR and IR networks share many downstream components, yet their physiological responses to stimuli are different. In cells that express EGFR, including HEK293 cells, EGF acts as a potent activator of mitogenesis through activation of the Ras/ERK pathway. In contrast, mitogenesis and the Ras/ERK pathway are poorly activated by insulin. The main biological function of insulin is metabolic, involving the control of glucose metabolism and stimulation of protein and lipid syntheses. We show that in HEK293 cells, insulin amplifies Ras/ERK activation by low, physiological [EGF], and at saturating [EGF] the insulin effect becomes insignificant. Following 1.5‐ and 15‐min co‐stimulation with EGF plus insulin, the phospho‐ERK level (which is directly related to ERK activity) is significantly larger than the sum of these levels observed for each ligand ([Figure 3E][1], left and right panels), displaying EGF–insulin synergy. The peak ERK activity (at ∼5 min co‐stimulation) does not display synergistic effects ([Figure 3E][1], middle panel). We show that insulin–EGF crosstalk is not a consequence of extra activation of either receptor by co‐stimulation with two ligands, or activation of insulin‐like growth factor receptor‐1 by insulin. Multiple points of crosstalk between EGFR and IR make it difficult to comprehend and predict intricate Ras/ERK signaling dynamics in a cell‐dependent context, using only qualitative arguments. These dynamics depend on a variety of non‐linear interactions and feedback loops. A testable computational model helps us provide insights into the key causative relationships between the input stimuli and Ras/ERK signaling and reveal specific functions of critical network nodes in generating cellular responses ([Kholodenko, 2006][2]). Our mechanistic computational model, trained by the data from HEK293 cells, suggests that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Some of the crosstalk interactions affect multiple Ras activation and deactivation routes, which involve the adaptor proteins, Grb2‐associated binder‐1 (GAB1) and insulin receptor substrates (IRS), and the SH2‐domain containing protein tyrosine phosphatase‐2 (SHP2). In the model, EGF and insulin co‐stimulation increases the amount of PIP3 produced by phosphatidylinositol 3‐kinase (PI3K) and further facilitates the GAB1 membrane recruitment and its subsequent tyrosine phosphorylation. An increase in the membrane‐bound phospho‐GAB1 promotes Grb2–SOS binding and increases \[SOS\] (Ras activator) in close proximity to Ras. At the same time, this gain in phospho‐GAB1 also increases the amounts of RasGAP (Ras deactivator) and SHP2 bound to GAB1. Although SHP2 negatively regulates IR, EGFR, IRS, and GAB1 phosphorylation levels, it has a positive effect on Ras activation, as we showed using a specific SHP2 inhibitor, NSC‐87877 ([Chen et al , 2006][3]). This positive effect is related to the formation of the GAB1–SHP2 and IRS–SHP2 complexes and subsequent dephosphorylation of multiple docking sites, involved in RasGAP binding. Simulations predict that the net result of all these interactions is an increase in positive signaling and decrease in negative signaling to Ras, which amplifies the Ras‐GTP level. Additional crosstalk interactions occur at the Ras/Raf level. In the model, at any given Ras‐GTP load, the simultaneous exposure to insulin plus EGF increases Raf activity, relative to insulin alone, owing to EGF‐induced stimulation of tyrosine kinases, which are assumed to belong to the Src family ([Wellbrock et al , 2004][4]). We tested the model against the experiment, using kinetic data on responses to multiple perturbations, including different EGF doses, specific inhibitors and small interfering RNA (siRNA). We...

Biochemical networks are characterized by recurrent patterns and motifs, but the design principles underlying the dynamics of the mammalian intracellular signalling network remain unclear. We systematically analysed decay rates of 134 signalling proteins and investigated their gene expression profiles in response to stimulation to get insights into transcriptional feedback regulation. We found a clear separation of the signalling pathways into flexible and static parts: for each pathway a subgroup of unstable signal inhibitors is transcriptionally induced upon stimulation, while the other constitutively expressed signalling proteins are long‐lived. Kinetic modelling suggests that this design principle allows for swift feedback regulation and establishes latency phases after signalling, and that it might be an optimal design due to a trade‐off between energy efficiency and flexibility.

Cellular decision‐making and environmental adaptation are dependent upon a heterogeneous response of gene expression to external cues. Heterogeneity arises in transcription from random switching between transcriptionally active and inactive states, resulting in bursts of RNA synthesis. Furthermore, the cellular state influences the competency of transcription, thereby globally affecting gene expression in a cell‐specific manner. We determined how external stimuli interplay with cellular state to modulate the kinetics of bursting. To this end, single‐cell dynamics of nascent transcripts were monitored at the endogenous estrogen‐responsive GREB1 locus. Stochastic modeling of gene expression implicated a two‐state promoter model in which the estrogen stimulus modulates the frequency of transcriptional bursting. The cellular state affects transcriptional dynamics by altering initiation and elongation kinetics and acts globally, as GREB1 alleles in the same cell correlate in their transcriptional output. Our results suggest that cellular state strongly affects the first step of the central dogma of gene expression, to promote heterogeneity in the transcriptional output of isogenic cells.

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