Monte Carlo simulation of cell death signaling predicts large cell-to-cell stochastic fluctuations through the type 2 pathway of apoptosis

Combination Treatment with Liposomal Doxorubicin and Inductive Moderate Hyperthermia for Sarcoma Saos-2 Cells

Despite efforts in osteosarcoma (OS) research, the role of inductive moderate hyperthermia (IMH) in delivering and enhancing the antitumor effect of liposomal doxorubicin formulations (LDOX) remains unresolved. This study investigated the effect of a combination treatment with LDOX and IMH on Saos-2 human OS cells. We compared cell viability using a trypan blue assay, apoptosis and reactive oxygen species (ROS) measured by flow cytometry and pro-apoptotic Bax protein expression examined by immunocytochemistry in response to IMH (42 MHz frequency, 15 W power for 30 min), LDOX (0.4 μg/mL), and LDOX plus IMH. The lower IC50 value of LDOX at 72 h indicated increased accumulation of the drug in the OS cells. LDOX plus IMH resulted in a 61% lower cell viability compared to no treatment. Moreover, IMH potentiated the LDOX action on the Saos-2 cells by promoting ROS production at temperatures of <42 °C. There was a 12% increase in cell populations undergoing early apoptosis with a less heterogeneous distribution of Bax after combination treatment compared to those treated with LDOX (p < 0.05). Therefore, we determined that IMH could enhance LDOX delivery and its antitumor effect via altered membrane permeabilization, ROS generation, and a lower level of visualized Bax heterogeneity in the Saos-2 cells, suggesting the potential translation of these findings into in vivo studies.

J, M.D.P. DE. C, RAJENDRAM S. Photodynamic Therapy : An Overview and Insights into a Prospective Mainstream Anticancer Therapy

Photodynamic therapy (PDT) procedure has minimum invasiveness in contrast to conventional anticancer surgical procedures. Although clinically approved a few decades ago, it is not commonly used due to its poor efficacy, mainly due to poor light penetration into deeper tissues. PDT uses a photosensitizer (PS), which is photoactivated on illumination by light of appropriate wavelength and oxygen in the tissue, leading to a series of photochemical reactions producing reactive oxygen species (ROS) triggering various mechanisms resulting in lethal effects on tumor cells. This review looks into the fundamental aspects of PDT, such as photochemistry, photobiological effects, and the current clinical applications in the light of improving PDT to become a mainstream therapeutic procedure against a broad spectrum of cancers and malignant lesions. The side effects of PDT, both early and late-onset, are elaborated on in detail to highlight the available options to minimize side effects without compromising therapeutic efficacy. This paper summarizes the benefits, drawbacks, and limitations of photodynamic therapy along with the recent attempts to achieve improved therapeutic efficacy via monitoring various cellular and molecular processes through fluorescent imagery aided by suitable biomarkers, prospective nanotechnology-based targeted delivery methods, the use of scintillating nanoparticles to deliver light to remote locations and also combining PDT with conventional anticancer therapies have opened up new dimensions for PDT in treating cancers. This review inquires and critically analyses prospective avenues in which a breakthrough would finally enable PDT to be integrated into mainstream anticancer therapy.

A Probabilistic Approach to Explore Signal Execution Mechanisms With Limited Experimental Data

Mathematical models of biochemical reaction networks are central to the study of dynamic cellular processes and hypothesis generation that informs experimentation and validation. Unfortunately, model parameters are often not available and sparse experimental data leads to challenges in model calibration and parameter estimation. This can in turn lead to unreliable mechanistic interpretations of experimental data and the generation of poorly conceived hypotheses for experimental validation. To address this challenge, we evaluate whether a Bayesian-inspired probability-based approach, that relies on expected values for quantities of interest calculated from available information regarding the reaction network topology and parameters can be used to qualitatively explore hypothetical biochemical network execution mechanisms in the context of limited available data. We test our approach on a model of extrinsic apoptosis execution to identify preferred signal execution modes across varying conditions. Apoptosis signal processing can take place either through a mitochondria independent (Type I) mode or a mitochondria dependent (Type II) mode. We first show that in silico knockouts, represented by model subnetworks, successfully identify the most likely execution mode for specific concentrations of key molecular regulators. We then show that changes in molecular regulator concentrations alter the overall reaction flux through the network by shifting the primary route of signal flow between the direct caspase and mitochondrial pathways. Our work thus demonstrates that probabilistic approaches can be used to explore the qualitative dynamic behavior of model biochemical systems even with missing or sparse data.

Photodynamic therapy: Toward a systemic computational model

We have designed a systemic model to understand the effect of Photodynamic Therapy (PDT) on long time scales. The model takes into account cell necrosis due to oxygen reactive species, cell apoptosis through the caspase pathway and the competition between healthy and tumor cells. We attempted to describe the system using state of the art computational techniques (necrosis and apoptosis) and simple models that allow a deeper understanding of the long time scale processes involved (healing and tumor growth). We analyzed the influence of the surface and tumor depth on the effectiveness of different treatment plans and we proposed, for the set of parameters used in this work, an optimum timing between sessions of PDT.

Dynamic Reorganization of the Cytoskeleton during Apoptosis: The Two Coffins Hypothesis

During apoptosis, cells undergo characteristic morphological changes in which the cytoskeleton plays an active role. The cytoskeleton rearrangements have been mainly attributed to actinomyosin ring contraction, while microtubule and intermediate filaments are depolymerized at early stages of apoptosis. However, recent results have shown that microtubules are reorganized during the execution phase of apoptosis forming an apoptotic microtubule network (AMN). Evidence suggests that AMN is required to maintain plasma membrane integrity and cell morphology during the execution phase of apoptosis. The new “two coffins” hypothesis proposes that both AMN and apoptotic cells can adopt two morphological patterns, round or irregular, which result from different cytoskeleton kinetic reorganization during the execution phase of apoptosis induced by genotoxic agents. In addition, round and irregular-shaped apoptosis showed different biological properties with respect to AMN maintenance, plasma membrane integrity and phagocyte responses. These findings suggest that knowing the type of apoptosis may be important to predict how fast apoptotic cells undergo secondary necrosis and the subsequent immune response. From a pathological point of view, round-shaped apoptosis can be seen as a physiological and controlled type of apoptosis, while irregular-shaped apoptosis can be considered as a pathological type of cell death closer to necrosis.

In silico modelling of apoptosis induced by photodynamic therapy

Photodynamic therapy (PDT) is an emergent technique used for the treatment of several diseases. After PDT, cells die by necrosis, apoptosis or autophagy. Necrosis is produced immediately during photodynamic therapy by high concentration of reactive oxygen species, apoptosis and autophagy are triggered by mild or low doses of light and photosensitizer. In this work we model the cell response to low doses of PDT assuming a bi-dimensional matrix of interacting cells. For each cell of the matrix we simulate in detail, with the help of the Gillespie's algorithm, the two main chemical pathways leading to apoptosis. We unveil the role of both pathways in the cell death rate of the tumor, as well as the relevance of several molecules in the process. Our model suggests values of concentrations for several species of molecules to enhance the effectiveness of PDT.

Neuroglobin, a Factor Playing for Nerve Cell Survival

Cell death represents the final outcome of several pathological conditions of the central nervous system and available evidence suggests that in both acute injuries and neurodegenerative diseases it is often associated with mitochondrial dysfunction. Thus, the possibility to prevent mitochondrial events involved in cell death might represent efficient tools to limit neuronal damage. In recent years, increased attention has been paid to the endogenous protein neuroglobin, since accumulating evidence showed that its high expression was associated with preserved mitochondrial function and to an increased survival of nerve cells in vitro and in vivo in a variety of experimental models of cell insult. The biological and structural features of neuroglobin and the mitochondria-related mechanisms of neuroglobin-induced neuroprotection will be here briefly discussed. In this respect, the inhibition of the intrinsic pathway of apoptosis emerges as a key neuroprotective effect induced by the protein. These findings could open the possibility to develop efficient neuroglobin-mediated therapeutic strategies aimed at minimizing the neuronal cell death occurring in impacting neurological pathologies like stroke and neurodegenerative diseases.

Protection by Neuroglobin Expression in Brain Pathologies

Astrocytes play an important role in physiological, metabolic, and structural functions, and when impaired, they can be involved in various pathologies including Alzheimer, focal ischemic stroke, and traumatic brain injury. These disorders involve an imbalance in the blood flow and nutrients such as glucose and lactate, leading to biochemical and molecular changes that cause neuronal damage, which is followed by loss of cognitive and motor functions. Previous studies have shown that astrocytes are more resilient than neurons during brain insults as a consequence of their more effective antioxidant systems, transporters, and enzymes, which made them less susceptible to excitotoxicity. In addition, astrocytes synthesize and release different protective molecules for neurons, including neuroglobin, a member of the globin family of proteins. After brain injury, neuroglobin expression is induced in astrocytes. Since neuroglobin promotes neuronal survival, its increased expression in astrocytes after brain injury may represent an endogenous neuroprotective mechanism. Here, we review the role of neuroglobin in the central nervous system, its relationship with different pathologies, and the role of different factors that regulate its expression in astrocytes.

A Viability Approach for Robustness Measurement, Organizational Autopoiesis, and Cell Turnover in a Multicellular System

In this article, we use the potential of computational biology to highlight the key role of cell apoptosis for studying some tissue's properties through in silico experiments of morphogenesis. Our morphogenesis model is a new approach focusing on the deterministic program within cells that controls their placement and their differentiation at the beginning of the embryogenesis. Indeed, when the tissue is made by just a few pair of cells, we consider that cellular mechanisms are related neither to the influence of mechanical forces nor to the spread of chemicals. Dynamics are based on spatial and logical choices, the other factors being involved when the tissue contains a large number of cells. We had established a mathematical formulation of such a model and had enlightened the link between phenotype (cell placement and cell differentiation) and genotype (cell program) at the early embryogenesis. Indeed, that work allowed for generating any early tissue and the associated program that designs it. We propose now to study and assess some properties of these tissues for further selection and classification purposes. More precisely, we present in this article novel methods to measure tissue robustness based on the backward morphogenesis of our model. We also show some implementations of their self-maintenance properties, on the one hand to deal with environment disturbances through autopoiesis and on the other hand to achieve a dynamical steady state which ensures tissue renewal.

Lifetime Distributions from Tracking Individual BC3H1 Cells Subjected to Yessotoxin

This work shows examples of lifetime distributions for individual BC3H1 cells after start of exposure to the marine toxin yessotoxin (YTX) in an experimental dish. The present tracking of many single cells from time-lapse microscopy data demonstrates the complexity in individual cell fate and which can be masked in aggregate properties. This contribution also demonstrates the general practicality of cell tracking. It can serve as a conceptually simple and non-intrusive method for high throughput early analysis of cytotoxic effects to assess early and late time points relevant for further analyzes or to assess for variability and sub-populations of interest. The present examples of lifetime distributions seem partly to reflect different cell death modalities. Differences between cell lifetime distributions derived from populations in different experimental dishes can potentially provide measures of inter-cellular influence. Such outcomes may help to understand tumor-cell resistance to drug therapy and to predict the probability of metastasis.

Neuroglobin protects cardiomyocytes against apoptosis and cardiac hypertrophy induced by isoproterenol in rats

Neuroglobin (Ngb) is well known as a physiological role in oxygen homeostasis of neurons and perhaps a protective role against hypoxia and oxidative stress. In this study, we found that Ngb is expressed in rat heart tissues and it is related to isoproterenol induced cardiac hypertrophy. Moreover, overexpression or knock-down of Ngb influences the expression of hypertrophic markers ANP and BNP and the ratio of hypertrophic cells in rat H9c2 myoblasts when isoproterenol treatment. The Annexin V-FITC/PI Staining, Western blot and qPCR analysis showed that the involvement in p53-mediated apoptosis of cardiomyocytes of Ngb is might be the mechanism. This protein could prevent the cells against ROS and POS-induced apoptosis not only in nervous systems but also in cardiomyocytes. From the results, it is concluded that Ngb is a promising protectant in the cardiac hypertrophy, it may be a candidate target to cardiac hypertrophy for clinic treatment.

Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer

Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs.

Death ligand concentration and the membrane proximal signaling module regulate the type 1/type 2 choice in apoptotic death signaling

Apoptotic death pathways are frequently activated by death ligand induction and subsequent activation of the membrane proximal signaling module. Death receptors cluster upon binding to death ligands, leading to formation of a membrane proximal death-inducing-signaling-complex (DISC). In this membrane proximal signalosome, initiator caspases (caspase 8) are processed resulting in activation of both type 1 and type 2 pathways of apoptosis signaling. How the type 1/type 2 choice is made is an important question in the systems biology of apoptosis signaling. In this study, we utilize a Monte Carlo based in silico approach to elucidate the role of membrane proximal signaling module in the type 1/type 2 choice of apoptosis signaling. Our results provide crucial mechanistic insights into the formation of DISC signalosome and caspase 8 activation. Increased concentration of death ligands was shown to correlate with increased type 1 activation. We also study the caspase 6 mediated system level feedback activation of apoptosis signaling and its role in the type 1/type 2 choice. Our results clarify the basis of cell-to-cell stochastic variability in apoptosis activation and ramifications of this issue is further discussed in the context of therapies for cancer and neurodegenerative disorders.

Modeling heterogeneous responsiveness of intrinsic apoptosis pathway

BACKGROUND

Apoptosis is a cell suicide mechanism that enables multicellular organisms to maintain homeostasis and to eliminate individual cells that threaten the organism's survival. Dependent on the type of stimulus, apoptosis can be propagated by extrinsic pathway or intrinsic pathway. The comprehensive understanding of the molecular mechanism of apoptotic signaling allows for development of mathematical models, aiming to elucidate dynamical and systems properties of apoptotic signaling networks. There have been extensive efforts in modeling deterministic apoptosis network accounting for average behavior of a population of cells. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level.

RESULTS

To address the inevitable randomness in the intrinsic apoptosis mechanism, we develop a theoretical and computational modeling framework of intrinsic apoptosis pathway at single-cell level, accounting for both deterministic and stochastic behavior. Our deterministic model, adapted from the well-accepted Fussenegger model, shows that an additional positive feedback between the executioner caspase and the initiator caspase plays a fundamental role in yielding the desired property of bistability. We then examine the impact of intrinsic fluctuations of biochemical reactions, viewed as intrinsic noise, and natural variation of protein concentrations, viewed as extrinsic noise, on behavior of the intrinsic apoptosis network. Histograms of the steady-state output at varying input levels show that the intrinsic noise could elicit a wider region of bistability over that of the deterministic model. However, the system stochasticity due to intrinsic fluctuations, such as the noise of steady-state response and the randomness of response delay, shows that the intrinsic noise in general is insufficient to produce significant cell-to-cell variations at physiologically relevant level of molecular numbers. Furthermore, the extrinsic noise represented by random variations of two key apoptotic proteins, namely Cytochrome C and inhibitor of apoptosis proteins (IAP), is modeled separately or in combination with intrinsic noise. The resultant stochasticity in the timing of intrinsic apoptosis response shows that the fluctuating protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Finally, simulations illustrate that the mean abundance of fluctuating IAP protein is positively correlated with the degree of cellular stochasticity of the intrinsic apoptosis pathway.

CONCLUSIONS

Our theoretical and computational study shows that the pronounced non-genetic heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations. In addition, it predicts that the IAP protein could serve as a potential therapeutic target for suppression of the cell-to-cell variation in the intrinsic apoptosis responsiveness.

Monte carlo study elucidates the type 1/type 2 choice in apoptotic death signaling in healthy and cancer cells

Apoptotic cell death is coordinated through two distinct (type 1 and type 2) intracellular signaling pathways. How the type 1/type 2 choice is made remains a central problem in the biology of apoptosis and has implications for apoptosis related diseases and therapy. We study the problem of type 1/type 2 choice in silico utilizing a kinetic Monte Carlo model of cell death signaling. Our results show that the type 1/type 2 choice is linked to deterministic versus stochastic cell death activation, elucidating a unique regulatory control of the apoptotic pathways. Consistent with previous findings, our results indicate that caspase 8 activation level is a key regulator of the choice between deterministic type 1 and stochastic type 2 pathways, irrespective of cell types. Expression levels of signaling molecules downstream also regulate the type 1/type 2 choice. A simplified model of DISC clustering elucidates the mechanism of increased active caspase 8 generation and type 1 activation in cancer cells having increased sensitivity to death receptor activation. We demonstrate that rapid deterministic activation of the type 1 pathway can selectively target such cancer cells, especially if XIAP is also inhibited; while inherent cell-to-cell variability would allow normal cells stay protected.

Modeling cell-to-cell stochastic variability in intrinsic apoptosis pathway

Apoptosis is a cell suicide mechanism that enables metazoans to control cell number in tissues and to eliminate individual cells that threaten the animal's survival. Dependent on the type of stimulus, apoptosis can be propagated by intrinsic pathway or extrinsic pathway. Previously, we have proposed a deterministic model of intrinsic apoptosis pathway which is bistable in a robust parameter region. Cellular networks, however, are inherently stochastic and significant cell-to-cell variability in apoptosis response has been observed at single cell level. In this work, we examine the impact of intrinsic stochastic fluctuations as well as variation of protein concentrations on behavior of the intrinsic apoptosis network. First, Gillespie Stochastic Simulation Algorithm (SSA) of the model is implemented to account for intrinsic noise. Using histograms of steady-state output at varying input levels, we show that the intrinsic noise in the apoptosis network elicits a wider region of bistability. We further analyze the dependence of system stochasticity due to intrinsic fluctuations, such as steady-state noise level and random response delay time, on the input signal. We find however that the intrinsic noise is insufficient to generate significant stochastic variations at physiologically relevant level of molecular numbers. Finally, extrinsic fluctuation represented by variations of two key proteins is modeled and the resultant stochasticity of apoptosis timing is analyzed. Indeed, these protein variations can induce cell-to-cell stochastic variability at a quantitative level agreeing with experiments. Therefore, we conclude that the heterogeneity in intrinsic apoptosis responses among individual cells plausibly arises from extrinsic rather than intrinsic origin of fluctuations.

Real-time cell viability assays using a new anthracycline derivative DRAQ7®

The exclusion of charged fluorescent dyes by intact cells has become a well-established assay for determining viability of cells. In search for a noninvasive fluorescent probe capable of long-term monitoring of cell death in real-time, we evaluated a new anthracycline derivative DRAQ7. The novel probe does not penetrate the plasma membrane of living cells but when the membrane integrity is compromised, it enters and binds readily to nuclear DNA to report cell death. It proved to be nontoxic to a panel of cancer cell lines grown continuously for up to 72 h and did not induce any detectable DNA damage signaling when analyzed using laser scanning microscopy and flow cytometry. The DRAQ7 provided a sensitive, real-time readout of cell death induced by a variety of stressors such as hypoxia, starvation, and drug-induced cytotoxicity. The overall responses to anticancer agents and resulting pharmacological dose-response profiles were not affected by the growth of tumor cells in the presence DRAQ7. Moreover, we for the first time introduced a near real-time microflow cytometric assay based on combination of DRAQ7 and mitochondrial inner membrane potential (ΔΨ(m) ) sensitive probe TMRM. We provide evidence that this low-dosage, real-time labeling procedure provides multiparameter and kinetic fingerprint of anticancer drug action.

A network-oriented perspective on cardiac calcium signaling

The normal contractile, electrical, and energetic function of the heart depends on the synchronization of biological oscillators and signal integrators that make up cellular signaling networks. In this review we interpret experimental data from molecular, cellular, and transgenic models of cardiac signaling behavior in the context of established concepts in cell network architecture and organization. Focusing on the cellular Ca(2+) handling machinery, we describe how the plasticity and adaptability of normal Ca(2+) signaling is dependent on dynamic network configurations that operate across a wide range of functional states. We consider how (mal)adaptive changes in signaling pathways restrict the dynamic range of the network such that it cannot respond appropriately to physiologic stimuli or perturbation. Based on these concepts, a model is proposed in which pathologic abnormalities in cardiac rhythm and contractility (e.g., arrhythmias and heart failure) arise as a consequence of progressive desynchronization and reduction in the dynamic range of the Ca(2+) signaling network. We discuss how a systems-level understanding of the network organization, cellular noise, and chaotic behavior may inform the design of new therapeutic modalities that prevent or reverse the disease-linked unraveling of the Ca(2+) signaling network.

A role for human neuroglobin in apoptosis

Over the past decade, following the discovery of the human heme protein neuroglobin, many studies have searched for evidence for this protein's mechanism of action. Much data has accrued showing that high levels of neuroglobin will protect cells from apoptotic cell death, following a wide range of challenges. Various explanations of its actions, based on measured reactivity with oxygen, nitric oxide, or free radicals, have been proposed, but none have, as yet, been substantiated in vivo. Following preliminary experiments, it was previously hypothesised that "the central role of neuroglobin in highly metabolically active cells and retinal and brain neurons is to reset the trigger level of mitochondrial cytochrome c release necessary to commit the cells to apoptosis" (I.U.M.B.M. Life (2008) 60, 398). In this article, we review the evidence, which has accumulated to support this hypothesised mechanism of action of neuroglobin and integrate this data, with other reported intracellular functions of neuroglobin, to suggest a plausible central role for neuroglobin in the control of apoptosis.

How can we kill cancer cells: Insights from the computational models of apoptosis

Cancer cells are widely known to be protected from apoptosis, a phenomenon that is a major hurdle to successful anticancer therapy. Over-expression of several anti-apoptotic proteins, or mutations in pro-apoptotic factors, has been recognized to confer such resistance. Development of new experimental strategies, such as in silico modeling of biological pathways, can increase our understanding of how abnormal regulation of apoptotic pathway in cancer cells can lead to tumour chemoresistance. Monte Carlo simulations are in particular well suited to study inherent variability, such as spatial heterogeneity and cell-to-cell variations in signaling reactions. Using this approach, often in combination with experimental validation of the computational model, we observed that large cell-to-cell variability could explain the kinetics of apoptosis, which depends on the type of pathway and the strength of stress stimuli. Most importantly, Monte Carlo simulations of apoptotic signaling provides unexpected insights into the mechanisms of fractional cell killing induced by apoptosis-inducing agents, showing that not only variation in protein levels, but also inherent stochastic variability in signaling reactions, can lead to survival of a fraction of treated cancer cells.

Real-Time dynamics of Ca2+, caspase-3/7, and morphological changes in retinal ganglion cell apoptosis under elevated pressure

Quantitative information on the dynamics of multiple molecular processes in individual live cells under controlled stress is central to the understanding of the cell behavior of interest and the establishment of reliable models. Here, the dynamics of the apoptosis regulator intracellular Ca(2+), apoptosis effector caspase-3/7, and morphological changes, as well as temporal correlation between them at the single cell level, are examined in retinal gangling cell line (differentiated RGC-5 cells) undergoing apoptosis at elevated hydrostatic pressure using a custom-designed imaging platform that allows long-term real-time simultaneous imaging of morphological and molecular-level physiological changes in large numbers of live cells (beyond the field-of-view of typical microscopy) under controlled hydrostatic pressure. This examination revealed intracellular Ca(2+) elevation with transient single or multiple peaks of less than 0.5 hour duration appearing at the early stages (typically less than 5 hours after the onset of 100 mmHg pressure) followed by gradual caspase-3/7 activation at late stages (typically later than 5 hours). The data reveal a strong temporal correlation between the Ca(2+) peak occurrence and morphological changes of neurite retraction and cell body shrinkage. This suggests that Ca(2+) elevation, through its impact on ion channel activity and water efflux, is likely responsible for the onset of apoptotic morphological changes. Moreover, the data show a significant cell-to-cell variation in the onset of caspase-3/7 activation, an inevitable consequence of the stochastic nature of the underlying biochemical reactions not captured by conventional assays based on population-averaged cellular responses. This real-time imaging study provides, for the first time, statistically significant data on simultaneous multiple molecular level changes to enable refinements and testing of models of the dynamics of mitochondria-mediated apoptosis. Further, the platform developed and the approach has direct significance to the study of a variety of signaling pathway phenomena.

A minimal model of signaling network elucidates cell-to-cell stochastic variability in apoptosis

Background

Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli.

Methodology

We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. Gillespie's stochastic simulation algorithm (SSA) is used in this study.

Conclusions/Significance

We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.

Cell death goes LIVE: technological advances in real-time tracking of cell death

Cell population can be viewed as a quantum system, which like Schrödinger's cat exists as a combination of survival- and death-allowing states. Tracking and understanding cell-to-cell variability in processes of high spatio-temporal complexity such as cell death is at the core of current systems biology approaches. As probabilistic modeling tools attempt to impute information inaccessible by current experimental approaches, advances in technologies for single-cell imaging and omics (proteomics, genomics, metabolomics) should go hand in hand with the computational efforts. Over the last few years we have made exciting technological advances that allow studies of cell death dynamically in real-time and with the unprecedented accuracy. These approaches are based on innovative fluorescent assays and recombinant proteins, bioelectrical properties of cells, and more recently also on state-of-the-art optical spectroscopy. Here, we review current status of the most innovative analytical technologies for dynamic tracking of cell death, and address the interdisciplinary promises and future challenges of these methods.

Lung injury and cancer: Mechanistic insights into ceramide and EGFR signaling under cigarette smoke

Cigarette smoke has been connected to an array of chronic lung diseases and is a major source of morbidity and mortality. Active smoking is responsible for approximately 90% of lung cancer cases. In addition, cigarette smoke is associated with other chronic pulmonary diseases such as pulmonary edema, chronic bronchitis, and pulmonary emphysema, the last two also termed chronic obstructive pulmonary disease (COPD). Lung cancer and COPD are developed very frequently in chronic cigarette smokers. It has been known for some time that lung cancer incidence increases in patients with COPD. Even the existence of some low-grade emphysema without noticeable airflow obstruction is associated with significantly elevated risk of lung cancer. These recent clinical insights demand new thinking and exploration of novel mechanistic studies to fully understand these observations. Lung injury and repair involve cell death and hyperplasia of airway epithelial cells and infiltration of inflammatory cells. All of these occur simultaneously. The mechanisms of cell death and hyperplasia in the lung constitute two sides of the coin of lung injury and repair. However, most molecular studies in airway epithelial cells center on the mechanism(s) of either cell growth and proliferation or cell death and the ceramide-generating machinery that drives aberrant induction of apoptotic cell death. Very few address both sides of the coin as an outcome of cigarette smoke exposure, which is the focus of this review.

An antiapoptotic neuroprotective role for neuroglobin

Cell death associated with mitochondrial dysfunction is common in acute neurological disorders and in neurodegenerative diseases. Neuronal apoptosis is regulated by multiple proteins, including neuroglobin, a small heme protein of ancient origin. Neuroglobin is found in high concentration in some neurons, and its high expression has been shown to promote survival of neurons in vitro and to protect brain from damage by both stroke and Alzheimer's disease in vivo. Early studies suggested this protective role might arise from the protein's capacity to bind oxygen or react with nitric oxide. Recent data, however, suggests that neither of these functions is likely to be of physiological significance. Other studies have shown that neuroglobin reacts very rapidly with cytochrome c released from mitochondria during cell death, thus interfering with the intrinsic pathway of apoptosis. Systems level computational modelling suggests that the physiological role of neuroglobin is to reset the trigger level for the post-mitochondrial execution of apoptosis. An understanding of the mechanism of action of neuroglobin might thus provide a rational basis for the design of new drug targets for inhibiting excessive neuronal cell death.

Neuroglobin protects nerve cells from apoptosis by inhibiting the intrinsic pathway of cell death

In the past few years, overwhelming evidence has accrued that a high level of expression of the protein neuroglobin protects neurons in vitro, in animal models, and in humans, against cell death associated with hypoxic and amyloid insult. However, until now, the exact mechanism of neuroglobin's protective action has not been determined. Using cell biology and biochemical approaches we demonstrate that neuroglobin inhibits the intrinsic pathway of apoptosis in vitro and intervenes in activation of pro-caspase 9 by interaction with cytochrome c. Using systems level information of the apoptotic signalling reactions we have developed a quantitative model of neuroglobin inhibition of apoptosis, which simulates neuroglobin blocking of apoptosome formation at a single cell level. Furthermore, this model allows us to explore the effect of neuroglobin in conditions not easily accessible to experimental study. We found that the protection of neurons by neuroglobin is very concentration sensitive. The impact of neuroglobin may arise from both its binding to cytochrome c and its subsequent redox reaction, although the binding alone is sufficient to block pro-caspase 9 activation. These data provides an explanation the action of neuroglobin in the protection of nerve cells from unwanted apoptosis.

Bcl-2 inhibits apoptosis by increasing the time-to-death and intrinsic cell-to-cell variations in the mitochondrial pathway of cell death

BH3 mimetics have been proposed as new anticancer therapeutics. They target anti-apoptotic Bcl-2 proteins, up-regulation of which has been implicated in the resistance of many cancer cells, particularly leukemia and lymphoma cells, to apoptosis. Using probabilistic computational modeling of the mitochondrial pathway of apoptosis, verified by single-cell experimental observations, we develop a model of Bcl-2 inhibition of apoptosis. Our results clarify how Bcl-2 imparts its anti-apoptotic role by increasing the time-to-death and cell-to-cell variability. We also show that although the commitment to death is highly impacted by differences in protein levels at the time of stimulation, inherent stochastic fluctuations in apoptotic signaling are sufficient to induce cell-to-cell variability and to allow single cells to escape death. This study suggests that intrinsic cell-to-cell stochastic variability in apoptotic signaling is sufficient to cause fractional killing of cancer cells after exposure to BH3 mimetics. This is an unanticipated facet of cancer chemoresistance.