Monte Carlo Simulation of Cell Death Signaling Predicts Large Cell-to-Cell Stochastic Fluctuations through the Type 2 Pathway of Apoptosis

Abstract

Apoptosis, or genetically programmed cell death, is a crucial cellular process that maintains the balance between life and death in cells. The precise molecular mechanism of apoptosis signaling and the manner in which type 1 and type 2 pathways of the apoptosis signaling network are differentially activated under distinct apoptotic stimuli is poorly understood. Based on Monte Carlo stochastic simulations, we show that the type 1 pathway becomes activated under strong apoptotic stimuli, whereas the type 2 mitochondrial pathway dominates apoptotic signaling in response to a weak death signal. Our results also show signaling in the type 2 pathway is stochastic; the population average over many cells does not capture the cell-to-cell fluctuations in the time course (approximately 1-10 h) of downstream caspase-3 activation. On the contrary, the probability distribution of caspase-3 activation for the mitochondrial pathway shows a distinct bimodal behavior that can be used to characterize the stochastic signaling in type 2 apoptosis and other similar complex signaling processes. Interestingly, such stochastic fluctuations in apoptosis signaling occur even in the presence of large numbers of signaling molecules.

Nonlinear regulation of commitment to apoptosis by simultaneous inhibition of Bcl-2 and XIAP in leukemia and lymphoma cells

“…1), we have developed a computational model of the mitochondrial pathway of apoptosis, which can be applied to study the activation of caspases over a wide range of apoptotic network parameters (described in detail in [9]). The model explicitly simulates diffusion and reaction events at the level of individual molecules, and is based on a probabilistic method in which the reactivity of all the signaling molecules follows a stochastic, rather than deterministic behavior, probing the induction of apoptosis at a single cell level [10]. At the beginning of the simulation all signaling molecules are distributed randomly and uniformly in the cell volume simulated by a three dimensional cubic lattice.…”

“…Considering the possibility of non-specific labeling with reagents such as PhiPhiLux, which contain an artificial caspase cleavage site, as well as varying sensitivity of different approaches for detection of caspase activity, it will be of interest to perform similar analysis using alternative experimental avenues that allow assessment of caspase activity in living cells, for example with the use of recently described crown nanoparticle probes [18]. The advantage of in silico models of cellular systems is that one can selectively study the behavior of specific pathways, reducing the complexity of biological systems, and thus test concepts that are otherwise difficult to verify experimentally [10,19]. Recent developments in the field of computational systems biology have paved the way to important new discoveries pertinent to cancer therapy [9,20,21].…”

A role for human neuroglobin in apoptosis

“…To further unravel the details of the actions of neuroglobin recourse has been made to modern systems level modelling of the cellular processes. Using Monte Carlo computational modeling of apoptotic signaling, based on measured reaction rate constants, where diffusion and reaction of signaling molecules are simulated at an individual molecular level, it is possible to explicitly simulate molecular interactions and model spatial heterogeneity such as the localization of pro and antiapoptotic proteins on mitochondrial membranes or formation of multiprotein apoptosome complexes (56). Using this experimentally validated model, it has been possible to probe the effects of variations in protein concentrations and the significance of the two phases of neuroglobin reactivity with cytochrome c (56).…”

“…Using Monte Carlo computational modeling of apoptotic signaling, based on measured reaction rate constants, where diffusion and reaction of signaling molecules are simulated at an individual molecular level, it is possible to explicitly simulate molecular interactions and model spatial heterogeneity such as the localization of pro and antiapoptotic proteins on mitochondrial membranes or formation of multiprotein apoptosome complexes (56). Using this experimentally validated model, it has been possible to probe the effects of variations in protein concentrations and the significance of the two phases of neuroglobin reactivity with cytochrome c (56). The model predicts that significant stochastic variation exists between cells in terms of their time to commitment to cell death and that resulting caspase activity shows all-or-none type (bistable) behavior at the level of single cells.…”

Analysis of a mathematical model of apoptosis: individual differences and malfunction in programmed cell death

“…After pioneering studies by Fussenegger et al 7 and Eissing et al, 8 many apoptosis models have been published (see review by Salvioli et al 9 and other references 3,[10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28] ), however, none of these studies focused on resistance to treatment (i.e., despite treatment, the cells survive due to lack of apoptosis). In treatments that target apoptotic pathways, drugs affecting extracellularly either activate Fas or another death signaling receptor.…”