Dynamics within the CD95 death-inducing signaling complex decide life and death of cells

Mosaic gene network modelling identified new regulatory mechanisms in HCV infection

Modelling of gene networks is widely used in systems biology to study the functioning of complex biological systems. Most of the existing mathematical modelling techniques are useful for analysis of well-studied biological processes, for which information on rates of reactions is available. However, complex biological processes such as those determining the phenotypic traits of organisms or pathological disease processes, including pathogen-host interactions, involve complicated cross-talk between interacting networks. Furthermore, the intrinsic details of the interactions between these networks are often missing. In this study, we developed an approach, which we call mosaic network modelling, that allows the combination of independent mathematical models of gene regulatory networks and, thereby, description of complex biological systems. The advantage of this approach is that it allows us to generate the integrated model despite the fact that information on molecular interactions between parts of the model (so-called mosaic fragments) might be missing. To generate a mosaic mathematical model, we used control theory and mathematical models, written in the form of a system of ordinary differential equations (ODEs). In the present study, we investigated the efficiency of this method in modelling the dynamics of more than 10,000 simulated mosaic regulatory networks consisting of two pieces. Analysis revealed that this approach was highly efficient, as the mean deviation of the dynamics of mosaic network elements from the behaviour of the initial parts of the model was less than 10%. It turned out that for construction of the control functional, data on perturbation of one or two vertices of the mosaic piece are sufficient. Further, we used the developed method to construct a mosaic gene regulatory network including hepatitis C virus (HCV) as the first piece and the tumour necrosis factor (TNF)-induced apoptosis and NF-κB induction pathways as the second piece. Thus, the mosaic model integrates the model of HCV subgenomic replicon replication with the model of TNF-induced apoptosis and NF-κB induction. Analysis of the mosaic model revealed that the regulation of TNF-induced signaling by the HCV network is crucially dependent on the RIP1, TRADD, TRAF2, FADD, IKK, IκBα, c-FLIP, and BAR genes. Overall, the developed mosaic gene network modelling approach demonstrated good predictive power and allowed the prediction of new regulatory nodes in HCV action on apoptosis and the NF-κB pathway. Those theoretical predictions could be a basis for further experimental verification.

Agonist mobility on supported lipid bilayers affects Fas mediated death response

Extrinsic apoptosis is initiated by recognition and clustering of the single-pass transmembrane proteins Fas ligand and Fas expressed at the surface of closely apposed lymphocytes and target cells, respectively. Since Fas-mediated death response was mainly studied with soluble antibodies, the mobility constraints for receptor activation by a membrane embedded agonist is not well understood. We explored this influence by stimulating apoptosis on functionalized supported lipid bilayers, where we quantified agonist mobility by z-scan fluorescence correlation spectroscopy. Using different lipid compositions, we show that the apoptotic response correlates with increased lateral mobility of the agonist in the lipid bilayer.

Combinatorial treatment of CD95L and gemcitabine in pancreatic cancer cells induces apoptotic and RIP1-mediated necroptotic cell death network

Combination therapy of cancer is based on the cumulative effects mediated by several drugs. Although molecular mechanisms of action of each particular drug are partially elucidated, understanding of the dynamic cross-talk between different cell death pathways at the quantitative level induced by combination therapy is still missing. Here, we exemplified this question for the death receptor (DR) networks in pancreatic cancer cells. We demonstrate that the combined action of CD95L and gemcitabine in pancreatic cancer cells leads to the simultaneous induction of caspase-dependent and caspase-independent cell death. The pro-apoptotic effects are mediated through down-regulation of the anti-apoptotic proteins c-FLIP and Mcl-1, while caspase-independent cell death was blocked by inhibition of the kinase activity of RIP1. Furthermore, gemcitabine co-treatment strongly increased the amount of cells undergoing CD95-induced RIP1-regulated necrosis. Imaging flow cytometry has enabled us to get the quantitative insights into the apoptosis-necroptosis network and reveal that the majority of the cells upon the CD95L/gemcitabine co-treatment undergoes necroptosis. Our data underlie the importance of the quantitative understanding of the interplay between different cell death modalities, which is essential for the development of anti-cancer therapies. Taken together, our results are important for combination therapy of pancreatic cancer comprising chemotherapeutics and DR-agonists and offer a possibility to sensitize cells with defects in the apoptotic machinery towards necroptosis-type-mediated death.

Molecular basis of death effector domain chain assembly and its role in caspase-8 activation

Assembly of a death-inducing signaling complex is a key event in the extrinsic apoptotic pathway, enabling activation of the caspase cascade and subsequent cell death. However, the molecular events governing DISC assembly have remained largely elusive because of the lack of information on mechanism and specificity regulating the death effector domain (DED)-DED interaction network. Using molecular modeling, mutagenesis, and biochemical and ex vivo experiments, we identified the precise binding interface and hot spots crucial for intermolecular DED chain assembly. Mutation of key interface residues (Leu42/Phe45) in procaspase-8 DED-A completely abrogated DED chain formation in HEK293 cells and prevented its association with FADD. A significant 2.6-3.6-fold reduction in procaspase-8 activation was observed in functional cell-death assays after substitution of the interfacial residues. Based on our results we propose a new model for DISC formation that refines the current understanding of the activation mechanism. Upon stimulation, FADD self-associates weakly via reciprocal interaction between helices α1/α4 and α2/α3 of the DED to form an oligomeric signaling platform that provides a stage for the initial recruitment of procaspase-8 through direct interaction with α1/α4 of DED-A, followed by sequential interaction mediated by helices α2/α5 of DED-B, to form the procaspase-8 DED chain that is crucial for its activation and subsequent cell death.

Surviving apoptosis: life-death signaling in single cells

Tissue development and homeostasis are regulated by opposing pro-survival and pro-death signals. An interesting feature of the Tumor Necrosis Factor (TNF) family of ligands is that they simultaneously activate opposing signals within a single cell via the same ligand-receptor complex. The magnitude of pro-death events such as caspase activation and pro-survival events such as Nuclear Factor (NF)-κB activation vary not only from one cell type to the next but also among individual cells of the same type due to intrinsic and extrinsic noise. The molecules involved in these pro-survival and/or pro-death pathways, and the different phenotypes that result from their activities, have been recently reviewed. Here we focus on the impact of cell-to-cell variability in the strength of these opposing signals on shaping cell fate decisions.

Low concentrations of doxycycline attenuates FasL-induced apoptosis in HeLa cells

Background

Doxycycline (DC) has been shown to possess non-antibiotic properties including Fas/Fas Ligand (FasL)-mediated apoptosis against several tumor types in the concentration range of 10–40 µg/mL. However, the effect of DC in apoptotic signaling at much low concentrations was not studied.

Methods

The present study investigated the attenuation effect of low dose of DC on FasL-induced apoptosis in HeLa cell by the methods of MTT assay, fluorescence microscopy, DNA fragmentation, flow cytometry analysis, and western blotting.

Results and conclusion

In the present findings we showed that low concentration of DC (<2.0 µg/mL) exhibited protective effects against FasL-induced apoptosis in HeLa cells. FasL treatment to HeLa cells resulted in a concentration-dependent induction of cell death, and treatment with low concentrations of DC (0.1–2 µg/mL) significantly (p < 0.001) attenuated the FasL-induced cell death as measured by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Further, the FasL-induced apoptotic features in HeLa cells, such as morphological changes, DNA fragmentation and cell cycle arrest was also inhibited by DC (0.5 µg/mL). Tetracycline and minocycline also showed similar anti-apoptotic effects but were not significant when compared to DC, tested at same concentrations. Further, DC (0.01–16 µg/mL) did not influence the hydrogen peroxide- or cisplatin-induced intrinsic apoptotic pathway in HeLa cells. Protein analysis using Western blotting confirmed that FasL-induced cleavage/activation of caspase-8 and caspase-3, were inhibited by DC treatment at low concentration (0.5 µg/mL). Considering the overall data, we report for the first time that DC exhibited anti-apoptotic effects at low concentrations in HeLa cells by inhibition of caspase activation via FasL-induced extrinsic pathway.

Electronic supplementary material

The online version of this article (doi:10.1186/s40659-015-0025-8) contains supplementary material, which is available to authorized users.

Quantification of CD95-induced apoptosis and NF-κB activation at the single cell level

CD95/Fas/APO-1 is a member of the death receptor (DR) family. Stimulation of CD95 leads to the induction of apoptosis as well as to NF-κB signaling. Crosstalk between these two pathways plays a central role in cell fate. Defects in the regulation of apoptosis and of NF-κB are connected to a number of chronic inflammatory diseases and cancer. For a better understanding of the life/death decisions in the cell and their contribution to disease progression, the development of new technologies is required. Using imaging flow cytometry we developed a method that enables a quantitative detection of different CD95 signaling pathways in the single cell. The important advantage of this method compared to other approaches is that it allows quantifying a large number of single cells undergoing apoptosis and NF-κB activation. This technology could provide new insights into the quantitative characterization of apoptosis and NF-κB at the single cell level and could be used for the quantitative network analysis in systems biology studies.

Fractional killing arises from cell-to-cell variability in overcoming a caspase activity threshold

When cells are exposed to death ligands such as TRAIL, a fraction undergoes apoptosis and a fraction survives; if surviving cells are re-exposed to TRAIL, fractional killing is once again observed. Therapeutic antibodies directed against TRAIL receptors also cause fractional killing, even at saturating concentrations, limiting their effectiveness. Fractional killing arises from cell-to-cell fluctuations in protein levels (extrinsic noise), but how this results in a clean bifurcation between life and death remains unclear. In this paper, we identify a threshold in the rate and timing of initiator caspase activation that distinguishes cells that live from those that die; by mapping this threshold, we can predict fractional killing of cells exposed to natural and synthetic agonists alone or in combination with sensitizing drugs such as bortezomib. A phenomenological model of the threshold also quantifies the contributions of two resistance genes (c-FLIP and Bcl-2), providing new insight into the control of cell fate by opposing pro-death and pro-survival proteins and suggesting new criteria for evaluating the efficacy of therapeutic TRAIL receptor agonists.

Systems biology network-based discovery of a small molecule activator BL-AD008 targeting AMPK/ZIPK and inducing apoptosis in cervical cancer

The aim of this study was to discover a small molecule activator BL-AD008 targeting AMPK/ZIPK and inducing apoptosis in cervical cancer. In this study, we systematically constructed the global protein-protein interaction (PPI) network and predicted apoptosis-related protein connections by the Naïve Bayesian model. Then, we identified some classical apoptotic PPIs and other previously unrecognized PPIs between apoptotic kinases, such as AMPK and ZIPK. Subsequently, we screened a series of candidate compounds targeting AMPK/ZIPK, synthesized some compounds and eventually discovered a novel dual-target activator (BL-AD008). Moreover, we found BL-AD008 bear remarkable anti-proliferative activities toward cervical cancer cells and could induce apoptosis by death-receptor and mitochondrial pathways. Additionally, we found that BL-AD008-induced apoptosis was affected by the combination of AMPK and ZIPK. Then, we found that BL-AD008 bear its anti-tumor activities and induced apoptosis by targeting AMPK/ZIPK in vivo. In conclusion, these results demonstrate the ability of systems biology network to identify some key apoptotic kinase targets AMPK and ZIPK; thus providing a dual-target small molecule activator (BL-AD008) as a potential new apoptosis-modulating drug in future cervical cancer therapy.

CYLD deletion triggers nuclear factor-κB-signaling and increases cell death resistance in murine hepatocytes

AIM: To analyze the role of CYLD for receptor-mediated cell death of murine hepatocytes in acute liver injury models.

METHODS: Hepatocyte cell death in CYLD knockout mice (CYLD^-/-) was analyzed by application of liver injury models for CD95- (Jo2) and tumor necrosis factor (TNF)-α- [D-GalN/lipopolysaccharide (LPS)] induced apoptosis. Liver injury was assessed by measurement of serum transaminases and histological analysis. Apoptosis induction was quantified by cleaved PARP staining and Western blotting of activated caspases. Nuclear factor (NF)-κB, ERK, Akt and jun amino-terminal kinases signaling were assessed. Primary Hepatocytes were isolated by two step-collagenase perfusion and treated with recombinant TNF-α and with the CD95-ligand Jo2. Cell viability was analyzed by MTT-assay.

RESULTS: Livers of CYLD^-/- mice showed increased anti-apoptotic NF-κB signaling. In both applied liver injury models CYLD^-/- mice showed a significantly reduced apoptosis sensitivity. After D-GalN/LPS treatment CYLD^-/- mice exhibited significantly lower levels of alanine aminotransferase (ALT) (295 U/L vs 859 U/L, P < 0.05) and aspartate aminotransferase (AST) (560 U/L vs 1025 U/L, P < 0.01). After Jo injection CYLD^-/- mice showed 2-fold lower ALT (50 U/L vs 110 U/L, P < 0.01) and lower AST (250 U/L vs 435 U/L, P < 0.01) serum-levels compared to WT mice. In addition, isolated CYLD^-/- primary murine hepatocytes (PMH) were less sensitive towards death receptor-mediated apoptosis and showed increased levels of Bcl-2, XIAP, cIAP1/2, survivin and c-FLIP expression upon TNF- and CD95-receptor triggering, respectively. Inhibition of NF-κB activation by the inhibitor of NF-κB phosphorylation inhibitor BAY 11-7085 inhibited the expression of anti-apoptotic proteins and re-sensitized CYLD^-/- PMH towards TNF- and CD95-receptor mediated cell death.

CONCLUSION: CYLD is a central regulator of apoptotic cell death in murine hepatocytes by controlling NF-κB dependent anti-apoptotic signaling.

Modeling dynamics of cell-to-cell variability in TRAIL-induced apoptosis explains fractional killing and predicts reversible resistance

Isogenic cells sensing identical external signals can take markedly different decisions. Such decisions often correlate with pre-existing cell-to-cell differences in protein levels. When not neglected in signal transduction models, these differences are accounted for in a static manner, by assuming randomly distributed initial protein levels. However, this approach ignores the a priori non-trivial interplay between signal transduction and the source of this cell-to-cell variability: temporal fluctuations of protein levels in individual cells, driven by noisy synthesis and degradation. Thus, modeling protein fluctuations, rather than their consequences on the initial population heterogeneity, would set the quantitative analysis of signal transduction on firmer grounds. Adopting this dynamical view on cell-to-cell differences amounts to recast extrinsic variability into intrinsic noise. Here, we propose a generic approach to merge, in a systematic and principled manner, signal transduction models with stochastic protein turnover models. When applied to an established kinetic model of TRAIL-induced apoptosis, our approach markedly increased model prediction capabilities. One obtains a mechanistic explanation of yet-unexplained observations on fractional killing and non-trivial robust predictions of the temporal evolution of cell resistance to TRAIL in HeLa cells. Our results provide an alternative explanation to survival via induction of survival pathways since no TRAIL-induced regulations are needed and suggest that short-lived anti-apoptotic protein Mcl1 exhibit large and rare fluctuations. More generally, our results highlight the importance of accounting for stochastic protein turnover to quantitatively understand signal transduction over extended durations, and imply that fluctuations of short-lived proteins deserve particular attention.

c-FLIPp43 induces activation of the nuclear factor‑κB signaling pathway in a dose-dependent manner in the A375 melanoma cell line

In order to investigate the role of c‑FLIPp43 in the regulation of the nuclear factor (NF)‑κB signaling pathway in melanoma cell lines, a eukaryotic expression vector for c‑FLIPp43 was constructed with the pCMV‑Tag2B plasmid. The monoclonal A375 cells with stable expression of c‑FLIPp43 were obtained by G418 selection and were identified with western blot analysis. The protein level of NF‑κBp65 in the A375 cell line with stable expression of c‑FLIPp43 was examined by western blot analysis. The translocation of NF‑κBp65 was examined using immunofluorescence. The A375 cell lines were transfected with the pCMV‑Tag2B‑cFLIPp43 vector at different doses and the activation of the NF‑κB signaling pathway was examined by the dual‑luciferase reporter assay system. The stable expression of c‑FLIPp43 in the A375 cell lines transfected with the pCMV‑Tag2B‑cFLIPp43 vector increased the protein level of NF‑κBp65 compared with in the A375 cell lines transfected with the empty vector. Transfection of the cells using the pCMV‑Tag2B‑cFLIPp43 vector increased the amount of NF‑κBp65 in the nucleus in a dose‑dependent manner. In conclusion, the transfection of the c‑FLIPp43 expression vector induces the protein expression of NF‑κBp65 and promotes the activation of the NF‑κB signaling pathway in the A375 melanoma cell line.

Cell-to-cell variability in cell death: can systems biology help us make sense of it all?

One of the most common observations in cell death assays is that not all cells die at the same time, or at the same treatment dose. Here, using the perspective of the systems biology of apoptosis and the context of cancer treatment, we discuss possible sources of this cell-to-cell variability as well as its implications for quantitative measurements and computational models of cell death. Many different factors, both within and outside of the apoptosis signaling networks, have been correlated with the variable responses to various death-inducing treatments. Systems biology models offer us the opportunity to take a more synoptic view of the cell death process to identify multifactorial determinants of the cell death decision. Finally, with an eye toward 'systems pharmacology', we discuss how leveraging this new understanding should help us develop combination treatment strategies to compel cancer cells toward apoptosis by manipulating either the biochemical state of cancer cells or the dynamics of signal transduction.

Systems biology of death receptor networks: live and let die

The extrinsic apoptotic pathway is initiated by death receptor activation. Death receptor activation leads to the formation of death receptor signaling platforms, resulting in the demolition of the cell. Despite the fact that death receptor-mediated apoptosis has been studied to a high level of detail, its quantitative regulation until recently has been poorly understood. This situation has dramatically changed in the last years. Creation of mathematical models of death receptor signaling led to an enormous progress in the quantitative understanding of the network regulation and provided fascinating insights into the mechanisms of apoptosis control. In the following sections, the models of the death receptor signaling and their biological implications will be addressed. Central attention will be given to the models of CD95/Fas/APO-1, an exemplified member of the death receptor signaling pathways. The CD95 death-inducing signaling complex (DISC) and regulation of CD95 DISC activity by its key inhibitor c-FLIP, have been vigorously investigated by modeling approaches, and therefore will be the major topic here. Furthermore, the non-linear dynamics of the DISC, positive feedback loops and bistability as well as stoichiometric switches in extrinsic apoptosis will be discussed. Collectively, this review gives a comprehensive view how the mathematical modeling supported by quantitative experimental approaches has provided a new understanding of the death receptor signaling network.

Transcriptional and metabolic adaptation of human neurons to the mitochondrial toxicant MPP(+)

Assessment of the network of toxicity pathways by Omics technologies and bioinformatic data processing paves the road toward a new toxicology for the twenty-first century. Especially, the upstream network of responses, taking place in toxicant-treated cells before a point of no return is reached, is still little explored. We studied the effects of the model neurotoxicant 1-methyl-4-phenylpyridinium (MPP⁺) by a combined metabolomics (mass spectrometry) and transcriptomics (microarrays and deep sequencing) approach to provide unbiased data on earliest cellular adaptations to stress. Neural precursor cells (LUHMES) were differentiated to homogeneous cultures of fully postmitotic human dopaminergic neurons, and then exposed to the mitochondrial respiratory chain inhibitor MPP⁺ (5 μM). At 18–24 h after treatment, intracellular ATP and mitochondrial integrity were still close to control levels, but pronounced transcriptome and metabolome changes were seen. Data on altered glucose flux, depletion of phosphocreatine and oxidative stress (e.g., methionine sulfoxide formation) confirmed the validity of the approach. New findings were related to nuclear paraspeckle depletion, as well as an early activation of branches of the transsulfuration pathway to increase glutathione. Bioinformatic analysis of our data identified the transcription factor ATF-4 as an upstream regulator of early responses. Findings on this signaling pathway and on adaptive increases of glutathione production were confirmed biochemically. Metabolic and transcriptional profiling contributed complementary information on multiple primary and secondary changes that contribute to the cellular response to MPP⁺. Thus, combined ‘Omics' analysis is a new unbiased approach to unravel earliest metabolic changes, whose balance decides on the final cell fate.

S-nitrosylation of FLICE inhibitory protein determines its interaction with RIP1 and activation of NF-κB

Death receptor (DR) ligation can lead to divergent signaling pathways causing either caspase-mediated cell death or cell proliferation and inflammation. These variations in cellular fate are determined by adaptor proteins that are recruited to the DR signaling complex. FLICE inhibitory protein (FLIP) is an established inhibitor of caspase-8-mediated apoptosis, and it is also involved in NF-κB activation. However, the molecular mechanism that regulates FLIP within this complex is unknown. In this study, we provide new evidence for the regulation of NF-κB by FLIP through S-nitrosylation, which involves covalent modification of the protein's cysteine thiol by nitric oxide to form S-nitrosothiol. Point mutations of FLIP at cysteine residues 254 and 259 prevent FLIP S-nitrosylation and its ability to activate NF-κB. The mechanism by which FLIP nitrosylation regulates NF-κB activity involves RIP1 binding and redistribution, whereas TRAF2 binding and distribution are unaffected. We further show that FLIP processing and cleavage is dependent on its nitrosylation status. Collectively, our study reveals a novel pathway for FLIP regulation of NF-κB through protein S-nitrosylation, which is a key posttranslational mechanism controlling DR-mediated cell death and survival. Since increased expression of FLIP and nitric oxide are frequently observed in chemotherapy-resistant tumors, S-nitrosylation of FLIP could be a key mechanism of chemoresistance and tumor growth.

Intra- and interdimeric caspase-8 self-cleavage controls strength and timing of CD95-induced apoptosis

Apoptosis in response to the ligand CD95L (also known as Fas ligand) is initiated by caspase-8, which is activated by dimerization and self-cleavage at death-inducing signaling complexes (DISCs). Previous work indicated that the degree of substrate cleavage by caspase-8 determines whether a cell dies or survives in response to a death stimulus. To determine how a death ligand stimulus is effectively translated into caspase-8 activity, we assessed this activity over time in single cells with compartmentalized probes that are cleaved by caspase-8 and used multiscale modeling to simultaneously describe single-cell and population data with an ensemble of single-cell models. We derived and experimentally validated a minimal model in which cleavage of caspase-8 in the enzymatic domain occurs in an interdimeric manner through interaction between DISCs, whereas prodomain cleavage sites are cleaved in an intradimeric manner within DISCs. Modeling indicated that sustained membrane-bound caspase-8 activity is followed by transient cytosolic activity, which can be interpreted as a molecular timer mechanism reflected by a limited lifetime of active caspase-8. The activation of caspase-8 by combined intra- and interdimeric cleavage ensures weak signaling at low concentrations of CD95L and strongly accelerated activation at higher ligand concentrations, thereby contributing to precise control of apoptosis.

Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology.

Evaluating strategies to normalise biological replicates of Western blot data

Western blot data are widely used in quantitative applications such as statistical testing and mathematical modelling. To ensure accurate quantitation and comparability between experiments, Western blot replicates must be normalised, but it is unclear how the available methods affect statistical properties of the data. Here we evaluate three commonly used normalisation strategies: (i) by fixed normalisation point or control; (ii) by sum of all data points in a replicate; and (iii) by optimal alignment of the replicates. We consider how these different strategies affect the coefficient of variation (CV) and the results of hypothesis testing with the normalised data. Normalisation by fixed point tends to increase the mean CV of normalised data in a manner that naturally depends on the choice of the normalisation point. Thus, in the context of hypothesis testing, normalisation by fixed point reduces false positives and increases false negatives. Analysis of published experimental data shows that choosing normalisation points with low quantified intensities results in a high normalised data CV and should thus be avoided. Normalisation by sum or by optimal alignment redistributes the raw data uncertainty in a mean-dependent manner, reducing the CV of high intensity points and increasing the CV of low intensity points. This causes the effect of normalisations by sum or optimal alignment on hypothesis testing to depend on the mean of the data tested; for high intensity points, false positives are increased and false negatives are decreased, while for low intensity points, false positives are decreased and false negatives are increased. These results will aid users of Western blotting to choose a suitable normalisation strategy and also understand the implications of this normalisation for subsequent hypothesis testing.

The C-terminal domain of the long form of cellular FLICE-inhibitory protein (c-FLIPL) inhibits the interaction of the caspase 8 prodomain with the receptor-interacting protein 1 (RIP1) death domain and regulates caspase 8-dependent nuclear factor κB (NF-κB) activation

Caspase 8 plays an essential role in the regulation of apoptotic and non-apoptotic signaling pathways. The long form of cellular FLICE-inhibitory protein (c-FLIPL) has been shown previously to regulate caspase 8-dependent nuclear factor κB (NF-κB) activation by receptor-interacting protein 1 (RIP1) and TNF receptor-associated factor 2 (TRAF2). In this study, the molecular mechanism by which c-FLIPL regulates caspase 8-dependent NF-κB activation was further explored in the human embryonic kidney cell line HEK 293 and variant cells barely expressing caspase 8. The caspase inhibitor benzyloxycarbonyl-Val-Ala-Asp(OMe)-fluoromethylketone greatly diminished caspase 8-dependent NF-κB activation induced by Fas ligand (FasL) when c-FLIPL, but not its N-terminal fragment c-FLIP(p43), was expressed. The prodomain of caspase 8 was found to interact with the RIP1 death domain and to be sufficient to mediate NF-κB activation induced by FasL or c-FLIP(p43). The interaction of the RIP1 death domain with caspase 8 was inhibited by c-FLIPL but not c-FLIP(p43). Thus, these results reveal that the C-terminal domain of c-FLIPL specifically inhibits the interaction of the caspase 8 prodomain with the RIP1 death domain and, thereby, regulates caspase 8-dependent NF-κB activation.

Decision-tree based model analysis for efficient identification of parameter relations leading to different signaling states

In systems biology, a mathematical description of signal transduction processes is used to gain a more detailed mechanistic understanding of cellular signaling networks. Such models typically depend on a number of parameters that have different influence on the model behavior. Local sensitivity analysis is able to identify parameters that have the largest effect on signaling strength. Bifurcation analysis shows on which parameters a qualitative model response depends. Most methods for model analysis are intrinsically univariate. They typically cannot consider combinations of parameters since the search space for such analysis would be too large. This limitation is important since activation of a signaling pathway often relies on multiple rather than on single factors. Here, we present a novel method for model analysis that overcomes this limitation. As input to a model defined by a system of ordinary differential equations, we consider parameters for initial chemical species concentrations. The model is used to simulate the system response, which is then classified into pre-defined classes (e.g., active or not active). This is combined with a scan of the parameter space. Parameter sets leading to a certain system response are subjected to a decision tree algorithm, which learns conditions that lead to this response. We compare our method to two alternative multivariate approaches to model analysis: analytical solution for steady states combined with a parameter scan, and direct Lyapunov exponent (DLE) analysis. We use three previously published models including a model for EGF receptor internalization and two apoptosis models to demonstrate the power of our approach. Our method reproduces critical parameter relations previously obtained by both steady-state and DLE analysis while being more generally applicable and substantially less computationally expensive. The method can be used as a general tool to predict multivariate control strategies for pathway activation and to suggest strategies for drug intervention.

Human T-cell leukemia virus type 1 Tax-deregulated autophagy pathway and c-FLIP expression contribute to resistance against death receptor-mediated apoptosis

The human T-cell leukemia virus type 1 (HTLV-1) Tax protein is considered to play a central role in the process that leads to adult T-cell leukemia/lymphoma (ATL) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). HTLV-1 Tax-expressing cells show resistance to apoptosis induced by Fas ligand (FasL) and tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL). The regulation of Tax on the autophagy pathway in HeLa cells and peripheral T cells was recently reported, but the function and underlying molecular mechanism of the Tax-regulated autophagy are not yet well defined. Here, we report that HTLV-1 Tax deregulates the autophagy pathway, which plays a protective role during the death receptor (DR)-mediated apoptosis of human U251 astroglioma cells. The cellular FLICE-inhibitory protein (c-FLIP), which is upregulated by Tax, also contributes to the resistance against DR-mediated apoptosis. Both Tax-induced autophagy and Tax-induced c-FLIP expression require Tax-induced activation of IκB kinases (IKK). Furthermore, Tax-induced c-FLIP expression is regulated through the Tax-IKK-NF-κB signaling pathway, whereas Tax-triggered autophagy depends on the activation of IKK but not the activation of NF-κB. In addition, DR-mediated apoptosis is correlated with the degradation of Tax, which can be facilitated by the inhibitors of autophagy.

IMPORTANCE

Our study reveals that Tax-deregulated autophagy is a protective mechanism for DR-mediated apoptosis. The molecular mechanism of Tax-induced autophagy is also illuminated, which is different from Tax-increased c-FLIP. Tax can be degraded via manipulation of autophagy and TRAIL-induced apoptosis. These results outline a complex regulatory network between and among apoptosis, autophagy, and Tax and also present evidence that autophagy represents a new possible target for therapeutic intervention for the HTVL-1 related diseases.

Systems modeling of anti-apoptotic pathways in prostate cancer: psychological stress triggers a synergism pattern switch in drug combination therapy

Prostate cancer patients often have increased levels of psychological stress or anxiety, but the molecular mechanisms underlying the interaction between psychological stress and prostate cancer as well as therapy resistance have been rarely studied and remain poorly understood. Recent reports show that stress inhibits apoptosis in prostate cancer cells via epinephrine/beta2 adrenergic receptor/PKA/BAD pathway. In this study, we used experimental data on the signaling pathways that control BAD phosphorylation to build a dynamic network model of apoptosis regulation in prostate cancer cells. We then compared the predictive power of two different models with or without the role of Mcl-1, which justified the role of Mcl-1 stabilization in anti-apoptotic effects of emotional stress. Based on the selected model, we examined and quantitatively evaluated the induction of apoptosis by drug combination therapies. We predicted that the combination of PI3K inhibitor LY294002 and inhibition of BAD phosphorylation at S112 would produce the best synergistic effect among 8 interventions examined. Experimental validation confirmed the effectiveness of our predictive model. Moreover, we found that epinephrine signaling changes the synergism pattern and decreases efficacy of combination therapy. The molecular mechanisms responsible for therapeutic resistance and the switch in synergism were explored by analyzing a network model of signaling pathways affected by psychological stress. These results provide insights into the mechanisms of psychological stress signaling in therapy-resistant cancer, and indicate the potential benefit of reducing psychological stress in designing more effective therapies for prostate cancer patients.

Psychological stress and anxiety are often experienced by prostate cancer patients, but the underlying mechanisms of interactions between psychological stress and cancer development, as well as drug resistance, are unclear. Here, we employed a systems biology approach to study interactions between stress-activated epinephrine/beta2 adrenergic receptor/protein kinase A signaling and a regulatory network that controls apoptosis in prostate cancer cells. We developed a dynamic network model of signaling pathways that control apoptosis in prostate cancer cells and quantitatively evaluated the effects of stress-activated signaling on apoptosis induced by drug combinations. Experimental data were used to guide modeling, to fit the unknown parameters and validate the model. Based on our model we found that epinephrine/beta2 adrenergic receptor/protein kinase A signaling can decrease drug efficiency, and can shift the effect of drug combination from synergy to antagonism. We also predicted that in addition to BAD phosphorylation Mcl-1 expression could be upregulated by stress/epinephrine signaling to inhibit apoptosis. This study provides insights into the mechanisms of psychological stress signaling in therapy-resistant cancer, and suggests that reducing psychological stress could help to make prostate cancer treatment more effective.

Life in the Fas lane: differential outcomes of Fas signaling

Fas, also known as CD95 or APO-1, is a member of the tumor necrosis factor/nerve growth factor superfamily. Although best characterized in terms of its apoptotic function, recent studies have identified several other cellular responses emanating from Fas. These responses include migration, invasion, inflammation, and proliferation. In this review, we focus on the diverse cellular outcomes of Fas signaling and the molecular switches identified to date that regulate its pro- and anti-apoptotic functions. Such switches occur at different levels of signal transduction, ranging from the receptor through to cross-talk with other signaling pathways. Factors identified to date including other extracellular signals, proteins recruited to the death-inducing signaling complex, and the availability of different intracellular components of signal transduction pathways. The success of therapeutically targeting Fas will require a better understanding of these pathways, as well as the regulatory mechanisms that determine cellular outcome following receptor activation.

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.

Programming biological models in Python using PySB

PySB is a framework for creating biological models as Python programs using a high-level, action-oriented vocabulary that promotes transparency, extensibility and reusability. PySB interoperates with many existing modeling tools and supports distributed model development.

PySB models are programs and leverage existing programming tools for documentation, testing, and collaborative development.

Reusable functions can encode common low-level biochemical processes as well as high-level modules, making models transparent and concise.

Modeling workflow is accelerated through close integration with Python numerical tools and interoperability with existing modeling software.

We demonstrate the use of PySB to encode 15 alternative hypotheses for the mitochondrial regulation of apoptosis, including a new ‘Embedded Together' model based on recent biochemical findings.

Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

Mathematical modeling of apoptosis

Apoptosis is a form of programmed cell death, which is fundamental to all multicellular organisms. Deregulation of apoptosis leads to a number of severe diseases including cancer. Apoptosis is initiated either by extrinsic signals via stimulation of receptors at the cellular surface or intrinsic signals, such as DNA damage or growth factor withdrawal. Apoptosis has been extensively studied using systems biology which substantially contributed to the understanding of this death signaling network. This review gives an overview of mathematical models of apoptosis and the potential of systems biology to contribute to the development of novel therapies for cancer or other apoptosis-related diseases.

Modulating cell-to-cell variability and sensitivity to death ligands by co-drugging

TRAIL (tumor necrosis factor-related apoptosis-inducing ligand) holds promise as an anti-cancer therapeutic but efficiently induces apoptosis in only a subset of tumor cell lines. Moreover, even in clonal populations of responsive lines, only a fraction of cells dies in response to TRAIL and individual cells exhibit cell-to-cell variability in the timing of cell death. Fractional killing in these cell populations appears to arise not from genetic differences among cells but rather from differences in gene expression states, fluctuations in protein levels and the extent to which TRAIL-induced death or survival pathways become activated. In this study, we ask how cell-to-cell variability manifests in cell types with different sensitivities to TRAIL, as well as how it changes when cells are exposed to combinations of drugs. We show that individual cells that survive treatment with TRAIL can regenerate the sensitivity and death-time distribution of the parental population, demonstrating that fractional killing is a stable property of cell populations. We also show that cell-to-cell variability in the timing and probability of apoptosis in response to treatment can be tuned using combinations of drugs that together increase apoptotic sensitivity compared to treatment with one drug alone. In the case of TRAIL, modulation of cell-to-cell variability by co-drugging appears to involve a reduction in the threshold for mitochondrial outer membrane permeabilization.

Cells surviving fractional killing by TRAIL exhibit transient but sustainable resistance and inflammatory phenotypes

Cells that survive fractional killing by TRAIL or FasR agonists enter a state of resistance accompanied by inflammatory phenotypes. This state is transient, decaying over the course of several days, but can be sustained by periodic TRAIL treatments. This finding has implications for optimal dosing strategies of extrinsic cell death agents.

When clonal populations of human cells are exposed to apoptosis-inducing agents, some cells die and others survive. This fractional killing arises not from mutation but from preexisting, stochastic differences in the levels and activities of proteins regulating apoptosis. Here we examine the properties of cells that survive treatment with agonists of two distinct death receptors, tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) and anti-FasR antibodies. We find that “survivor” cells are highly resistant to a second ligand dose applied 1 d later. Resistance is reversible, resetting after several days of culture in the absence of death ligand. “Reset” cells appear identical to drug-naive cells with respect to death ligand sensitivity and gene expression profiles. TRAIL survivors are cross-resistant to activators of FasR and vice versa and exhibit an NF-κB–dependent inflammatory phenotype. Remarkably, reversible resistance is induced in the absence of cell death when caspase inhibitors are present and can be sustained for 1 wk or more, also without cell death, by periodic ligand exposure. Thus stochastic differences in cell state can have sustained consequences for sen­sitivity to prodeath ligands and acquisition of proinflammatory phenotypes. The important role played by periodicity in TRAIL exposure for induction of opposing apoptosis and survival mechanisms has implications for the design of optimal therapeutic agents and protocols.

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters.

EVER2 protein binds TRADD to promote TNF-α-induced apoptosis

EVER1 and 2 confer resistance to cutaneous oncogenic human papillomavirus infections by downregulating the activating protein 1 (AP-1) signaling pathway. Defects in their expression are associated with susceptibility to epidermodysplasia verruciformis, which is characterized by persistent β-HPV infection, tumor necrosis factor alpha (TNF-α) overproduction in keratinocytes and the development of skin cancers. TNF-α-induced apoptosis is a key defense strategy, preventing the persistence of the virus within cells, but the role of EVER proteins in this cell death mechanism triggered by extrinsic stimuli is unknown. We show here that EVER2 induces TNF-α- and TRAIL-dependant apoptosis. It interacts with the N-terminal domain of TRADD, impairs the recruitment of TRAF2 and RIPK1 and promotes apoptosis. The skin cancer-associated EVER2 I306 allele results in an impaired TRADD-EVER2 interaction, with lower levels of cell death following treatment with TNF-α. These data highlight a new, critical function of EVER2 in controlling cell survival in response to death stimuli.

Model composition through model reduction: a combined model of CD95 and NF-κB signaling pathways

Background

Many mathematical models characterizing mechanisms of cell fate decisions have been constructed recently. Their further study may be impossible without development of methods of model composition, which is complicated by the fact that several models describing the same processes could use different reaction chains or incomparable sets of parameters. Detailed models not supported by sufficient volume of experimental data suffer from non-unique choice of parameter values, non-reproducible results, and difficulty of analysis. Thus, it is necessary to reduce existing models to identify key elements determining their dynamics, and it is also required to design the methods allowing us to combine them.

Results

Here we propose a new approach to model composition, based on reducing several models to the same level of complexity and subsequent combining them together. Firstly, we suggest a set of model reduction tools that can be systematically applied to a given model. Secondly, we suggest a notion of a minimal complexity model. This model is the simplest one that can be obtained from the original model using these tools and still able to approximate experimental data. Thirdly, we propose a strategy for composing the reduced models together. Connection with the detailed model is preserved, which can be advantageous in some applications. A toolbox for model reduction and composition has been implemented as part of the BioUML software and tested on the example of integrating two previously published models of the CD95 (APO-1/Fas) signaling pathways. We show that the reduced models lead to the same dynamical behavior of observable species and the same predictions as in the precursor models. The composite model is able to recapitulate several experimental datasets which were used by the authors of the original models to calibrate them separately, but also has new dynamical properties.

Conclusion

Model complexity should be comparable to the complexity of the data used to train the model. Systematic application of model reduction methods allows implementing this modeling principle and finding models of minimal complexity compatible with the data. Combining such models is much easier than of precursor models and leads to new model properties and predictions.

Properties of cell death models calibrated and compared using Bayesian approaches

Using models to simulate and analyze biological networks requires principled approaches to parameter estimation and model discrimination. We use Bayesian and Monte Carlo methods to recover the full probability distributions of free parameters (initial protein concentrations and rate constants) for mass-action models of receptor-mediated cell death. The width of the individual parameter distributions is largely determined by non-identifiability but covariation among parameters, even those that are poorly determined, encodes essential information. Knowledge of joint parameter distributions makes it possible to compute the uncertainty of model-based predictions whereas ignoring it (e.g., by treating parameters as a simple list of values and variances) yields nonsensical predictions. Computing the Bayes factor from joint distributions yields the odds ratio (∼20-fold) for competing 'direct' and 'indirect' apoptosis models having different numbers of parameters. Our results illustrate how Bayesian approaches to model calibration and discrimination combined with single-cell data represent a generally useful and rigorous approach to discriminate between competing hypotheses in the face of parametric and topological uncertainty.

The adaptor protein FADD and the initiator caspase-8 mediate activation of NF-κB by TRAIL

Besides inducing apoptosis, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) activates NF-κB. The apoptosis signaling pathway of TRAIL is well characterized involving TRAIL receptors, Fas-associated protein with death domain (FADD) and caspase-8. In contrast, the molecular mechanism of TRAIL signaling to NF-κB remains controversial. Here, we characterized the receptor–proximal mediators of NF-κB activation by TRAIL. Deletion of the DD of TRAIL receptors 1 and 2 revealed that it is essential in NF-κB signaling. Because FADD interacts with the TRAIL receptor DD, FADD was tested. RNAi-mediated knockdown of FADD or FADD deficiency in JURKAT T-cell leukemia cells decreased or disabled NF-κB signaling by TRAIL. In contrast, TRAIL-induced activation of NF-κB was maintained upon loss of receptor interacting protein 1 (RIP1) or knockdown of FLICE-like inhibitory protein (FLIP). Exogenous expression of FADD rescued TRAIL-induced NF-κB signaling. Loss-of-function mutations of FADD within the RHDLL motif of the death effector domain, which is required for TRAIL-induced apoptosis, abrogated FADD's ability to recruit caspase-8 and mediate NF-κB activation. Accordingly, deficiency of caspase-8 inhibited TRAIL-induced activation of NF-κB, which was rescued by wild-type caspase-8, but not by a catalytically inactive caspase-8 mutant. These data establish the mechanism of TRAIL-induced NF-κB activation involving the TRAIL receptor DD, FADD and caspase-8, but not RIP1 or FLIP. Our results show that signaling of TRAIL-induced apoptosis and NF-κB bifurcates downstream of caspase-8.

Analysing the role of UVB-induced translational inhibition and PP2Ac deactivation in NF-κB signalling using a minimal mathematical model

Activation of nuclear factor κB (NF-κB) by interleukin-1β (IL-1) usually results in an anti-apoptotic activity that is rapidly terminated by a negative feedback loop involving NF-κB dependent resynthesis of its own inhibitor IκBα. However, apoptosis induced by ultraviolet B radiation (UVB) is not attenuated, but significantly enhanced by co-stimulation with IL-1 in human epithelial cells. Under these conditions NF-κB remains constitutively active and turns into a pro-apoptotic factor by selectively repressing anti-apoptotic genes. Two different mechanisms have been separately proposed to explain UV-induced lack of IκBα recurrence: global translational inhibition as well as deactivation of the Ser/Thr phosphatase PP2Ac. Using mathematical modelling, we show that the systems behaviour requires a combination of both mechanisms, and we quantify their contribution in different settings. A mathematical model including both mechanisms is developed and fitted to various experimental data sets. A comparison of the model results and predictions with model variants lacking one of the mechanisms shows that both mechanisms are present in our experimental setting. The model is successfully validated by the prediction of independent data. Weak constitutive IKKβ phosphorylation is shown to be a decisive process in IκBα degradation induced by UVB stimulation alone, but irrelevant for (co-)stimulations with IL-1. In silico knockout experiments show that translational inhibition is predominantly responsible for lack of IκBα recurrence following IL-1+UVB stimulation. In case of UVB stimulation alone, cooperation of both processes causes the observed decrease of IκBα. This shows that the processes leading to activation of transcription factor NF-κB upon stimulation with ultraviolet B radiation with and without interleukin-1 costimulation are more complex than previously thought, involving both a cross talk of UVB induced translational inhibition and PP2Ac deactivation. The importance of each of the mechanisms depends on the specific cellular setting.

A linear framework for time-scale separation in nonlinear biochemical systems

Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level.

A systematic modeling study on the pathogenic role of p38 MAPK activation in myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are a group of clonal hematopoietic stem cell diseases. In addition to intrinsic genetic alterations, the effects of the extrinsic microenvironment also play a pathological role in MDS development. The presence of increased inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), in marrow and abnormal activation of the p38 mitogen-activated protein kinase (MAPK) signaling pathway in hematopoietic cells are associated with the ineffective hematopoiesis in MDS. However, the molecular mechanism of p38 MAPK activation triggered by microenvironment cytokines remains poorly understood. To address this question, we combined computational modeling analysis and molecular biology studies to perform a systematic investigation of signaling events regulated by microenvironment cytokines in hematopoietic cells from MDS patients. We examined dynamic changes of key signaling events, including the p38 MAPK and the c-Jun N-terminal kinase (JNK) pathway in bone marrow mononuclear cells from MDS patients or normal donors in response to TNF-α stimulation using reverse phase protein array technology. The results were analyzed by a novel computational model and preliminarily validated by immunohistochemistry analysis of the bone marrow tissues from twelve MDS patients and normal donors. Our systematic model revealed that the dynamic response patterns of p38 MAPK and JNK to TNF-α stimulation in MDS were different from that observed in normal marrow cells. Particularly, B-cell lymphoma-X (BCL-XL) protein degradation was regulated by the JNK pathway in normal cells, but by p38 MAPK in MDS cells. By immunohistochemistry, BCL-XL was highly expressed in hematopoietic cells from normal marrow, but was minimally expressed in MDS marrow. Additionally, immunostaining for phosphorylated p38 MAPKα showed much higher p38 MAPK activation in MDS marrows, supporting over-activation of p38 MAPK-enhanced degradation of BCL-XL in MDS. The degradation of BCL-XL triggered by p38 MAPK over-activation may contribute to the increasing apoptosis of marrow cells, a phenomenon commonly observed in MDS, and lead to ineffective hematopoiesis. Our study suggests that the combination of molecular biological studies and systematic modeling is a powerful tool for comprehensive investigation of the complex cellular mechanisms involved in MDS pathogenesis.

Proteasome inhibition can impair caspase-8 activation upon submaximal stimulation of apoptotic tumor necrosis factor-related apoptosis inducing ligand (TRAIL) signaling

Tumor necrosis factor-related apoptosis inducing ligand (TRAIL) can induce extrinsic apoptosis, resulting in caspase-8 activation, but may also initiate transcription-dependent prosurvival signaling. Proteasome inhibitors were suggested to promote TRAIL signal transduction through the death-inducing signaling complex (DISC) by modulating the relative abundance of core DISC components, thereby enhancing caspase-8 activation and apoptosis. To test this hypothesis, we quantified the changes in DISC protein levels as an early consequence of proteasome inhibition in HeLa cervical cancer cells and, based on these data, mathematically modeled the proapoptotic TRAIL signaling toward caspase-8 activation. Modeling results surprisingly suggested that caspase-8 activation might be delayed in presence of proteasome inhibitors, in particular at submaximal TRAIL doses. Subsequent FRET-based single cell time-lapse imaging at conditions where transcription dependent prosurvival signaling was blocked confirmed this hypothesis: caspase-8 activity was delayed by hours in the presence of proteasome inhibitors epoxomicin or bortezomib. Corresponding delays were detected for effector caspase processing and cell death. Contrary to current models, we therefore provide evidence that synergies between TRAIL and proteasome inhibitors do not result from changes in the levels of core DISC signaling proteins.

Cellular FLICE-like inhibitory proteins (c-FLIPs): fine-tuners of life and death decisions

c-FLIP proteins (isoforms: c-FLIP(L), c-FLIP(S), and c-FLIP(R)) play an essential role in the regulation of death receptor (DR)-induced apoptosis and NF-κB activation. Here, we discuss multiple mechanisms by which c-FLIPs control NF-κB activation and the life/death decision made in cancer and immune cells. We focus on the role of c-FLIP in cellular signaling. We concentrate on c-FLIP protein modifications as well as on the regulation of c-FLIP expression levels. Furthermore, we discuss in detail how the exact quantity and dynamics of different c-FLIP isoforms in the cell influence the induction of pro- versus anti-apoptotic pathways.

A modular model of the apoptosis machinery

Using a modular principle of computer hardware as a metaphor, we defined and implemented in the BioUML platform a module concept for biological pathways. BioUML provides a user interface to create modular models and convert them automatically into plain models for further simulations. Using this approach, we created the apoptosis model including 13 modules: death stimuli (TRAIL, CD95L, and TNF-α)-induced activation of caspase-8; survival stimuli (p53, EGF, and NF-κB) regulation; the mitochondria level; cytochrome C- and Smac-induced activation of caspase-3; direct activation of effector caspases by caspase-8 and - 12; PARP and apoptosis execution phase modules. Each module is based on earlier published models and extended by data from the Reactome and TRANSPATH databases. The model ability to simulate the apoptosis-related processes was checked; the modules were validated using experimental data.

AVAILABILITY

http://www.biouml.org/apoptosis.shtml .

Heterogeneity reduces sensitivity of cell death for TNF-stimuli

Background

Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation, but at the same time also stimulates nuclear factor κB (NF-κB)-mediated survival pathways. Differential dose-response relationships of these two major TNF signaling pathways have been described experimentally and using mathematical modeling. However, the quantitative analysis of the complex interplay between pro- and anti-apoptotic signaling pathways is an open question as it is challenging for several reasons: the overall signaling network is complex, various time scales are present, and cells respond quantitatively and qualitatively in a heterogeneous manner.

Results

This study analyzes the complex interplay of the crosstalk of TNF-R1 induced pro- and anti-apoptotic signaling pathways based on an experimentally validated mathematical model. The mathematical model describes the temporal responses on both the single cell level as well as the level of a heterogeneous cell population, as observed in the respective quantitative experiments using TNF-R1 stimuli of different strengths and durations. Global sensitivity of the heterogeneous population was quantified by measuring the average gradient of time of death versus each population parameter. This global sensitivity analysis uncovers the concentrations of Caspase-8 and Caspase-3, and their respective inhibitors BAR and XIAP, as key elements for deciding the cell's fate. A simulated knockout of the NF-κB-mediated anti-apoptotic signaling reveals the importance of this pathway for delaying the time of death, reducing the death rate in the case of pulse stimulation and significantly increasing cell-to-cell variability.

Conclusions

Cell ensemble modeling of a heterogeneous cell population including a global sensitivity analysis presented here allowed us to illuminate the role of the different elements and parameters on apoptotic signaling. The receptors serve to transmit the external stimulus; procaspases and their inhibitors control the switching from life to death, while NF-κB enhances the heterogeneity of the cell population. The global sensitivity analysis of the cell population model further revealed an unexpected impact of heterogeneity, i.e. the reduction of parametric sensitivity.

Regulation of CD95/Fas signaling at the DISC

CD95 (APO-1/Fas) is a member of the death receptor (DR) family. Stimulation of CD95 leads to induction of apoptotic and non-apoptotic signaling pathways. The formation of the CD95 death-inducing signaling complex (DISC) is the initial step of CD95 signaling. Activation of procaspase-8 at the DISC leads to the induction of DR-mediated apoptosis. The activation of procaspase-8 is blocked by cellular FLICE-inhibitory proteins (c-FLIP). This review is focused on the role in the CD95-mediated signaling of the death effector domain-containing proteins procaspase-8 and c-FLIP. We discuss how dynamic cross-talk between procaspase-8 and c-FLIP at the DISC regulates life/death decisions at CD95.

Caspase-8 activity has an essential role in CD95/Fas-mediated MAPK activation

Stimulation of CD95/Fas/APO-1 results in the induction of both apoptotic and non-apoptotic signaling pathways. The processes regulating these two opposing pathways have not been thoroughly elucidated to date. In this study, using quantitative immunoblots, imaging, and mathematical modeling, we addressed the dynamics of the DED proteins of the death-inducing signaling complex (DISC), procaspase-8, and cellular FLICE inhibitory proteins (c-FLIPs) to the onset of CD95-mediated ERK1/2 and p38 mitogen-activated protein kinase (MAPK) activation. We found that CD95 DISC-induced caspase-8 activity is important for the initiation of ERK1/2 and p38 MAPK activation. The long c-FLIP isoform, c-FLIP(L), and the short c-FLIP isoform, c-FLIP(R), inhibited MAPK induction by blocking caspase-8 processing at the DISC. Furthermore, we built a mathematical model describing CD95 DISC-mediated MAPK activation and apoptosis. The model quantitatively defined the dynamics of DED proteins, procaspase-8, and c-FLIP, which lead to caspase-8 activation and induction of apoptotic and non-apoptotic signaling pathways. In conclusion, the combination of biochemical analysis with mathematical modeling provides evidence for an important role of caspase-8 in CD95-mediated activation of MAPKs, while c-FLIP exerts a regulatory function in this process.

Antioxidant c-FLIP inhibits Fas ligand-induced NF-kappaB activation in a phosphatidylinositol 3-kinase/Akt-dependent manner

Fas ligand (FasL) belongs to the TNF family of death ligands, and its binding to the FasR leads to activation of several downstream signaling pathways and proteins, including NF-κB and PI3K/Akt. However, it is not known whether cross-talk exists between NF-κB and PI3K/Akt in the context of FasL signaling. We demonstrate using both human renal epithelial 293T cells and Jurkat T-lymphocyte cells that although FasL activates both Akt and NF-κB, Akt inhibits FasL-dependent NF-κB activity in a reactive oxygen species-dependent manner. Cellular FLICE-inhibitory protein (c-FLIP), an antioxidant and an important component of the death-inducing signaling complex, also represses NF-κB upstream of the regulatory IκB kinase-γ protein subunit in the NF-κB signaling pathway, and positive cross-talk exists between Akt and c-FLIP in the context of inhibition of FasL-induced NF-κB activity. The presence of two death effector domains of c-FLIP and S-nitrosylation of its caspase-like domain were found to be important for mediating c-FLIP-dependent downregulation of NF-κB activity. Taken together, our study reveals a novel link between NF-κB and PI3K/Akt and establishes c-FLIP as an important regulator of FasL-mediated cell death.

Modeling reveals that dynamic regulation of c-FLIP levels determines cell-to-cell distribution of CD95-mediated apoptosis

The expression levels of caspase-8 inhibitory c-FLIP proteins play an important role in regulating death receptor-mediated apoptosis, as their concentration at the moment when the death-inducing signaling complex (DISC) is formed determines the outcome of the DISC signal. Experimental studies have shown that c-FLIP proteins are subject to dynamic turnover and that their stability and expression levels can be rapidly altered. Even though the influence of c-FLIP on the apoptotic behavior of a single cell has been captured in mathematical simulation studies, the effect of c-FLIP turnover and stability has not been investigated. In this study, a mathematical model of apoptosis was developed to analyze how the dynamic turnover and stability of the c-FLIP isoforms regulate apoptotic signaling for both individual cells and cell populations. Intercellular parameter and concentration distributions were used to describe the behavior of cell populations. Monte-Carlo simulations of cell populations showed that c-FLIP turnover is a key determinant of death receptor responses. The fact that the developed model simulates the state of whole cell populations makes it possible to validate it by comparison with empirical data. The proposed modeling approach can be used to further determine limiting factors in the DISC signaling process.

Modulation of the CD95-induced apoptosis: the role of CD95 N-glycosylation

Protein modifications of death receptor pathways play a central role in the regulation of apoptosis. It has been demonstrated that O-glycosylation of TRAIL-receptor (R) is essential for sensitivity and resistance towards TRAIL-mediated apoptosis. In this study we ask whether and how glycosylation of CD95 (Fas/APO-1), another death receptor, influences DISC formation and procaspase-8 activation at the CD95 DISC and thereby the onset of apoptosis. We concentrated on N-glycostructure since O-glycosylation of CD95 was not found. We applied different approaches to analyze the role of CD95 N-glycosylation on the signal transduction: in silico modeling of CD95 DISC, generation of CD95 glycosylation mutants (at N136 and N118), modulation of N-glycosylation by deoxymannojirimycin (DMM) and sialidase from Vibrio cholerae (VCN). We demonstrate that N-deglycosylation of CD95 does not block DISC formation and results only in the reduction of the procaspase-8 activation at the DISC. These findings are important for the better understanding of CD95 apoptosis regulation and reveal differences between apoptotic signaling pathways of the TRAIL and CD95 systems.

Pro- and anti-apoptotic CD95 signaling in T cells

The TNF receptor superfamily member CD95 (Fas, APO-1, TNFRSF6) is known as the prototypic death receptor in and outside the immune system. In fact, many mechanisms involved in apoptotic signaling cascades were solved by addressing consequences and pathways initiated by CD95 ligation in activated T cells or other "CD95-sensitive" cell populations. As an example, the binding of the inducible CD95 ligand (CD95L) to CD95 on activated T lymphocytes results in apoptotic cell death. This activation-induced cell death was implicated in the control of immune cell homeostasis and immune response termination. Over the past years, however, it became evident that CD95 acts as a dual function receptor that also exerts anti-apoptotic effects depending on the cellular context. Early observations of a potential non-apoptotic role of CD95 in the growth control of resting T cells were recently reconsidered and revealed quite unexpected findings regarding the costimulatory capacity of CD95 for primary T cell activation. It turned out that CD95 engagement modulates TCR/CD3-driven signal initiation in a dose-dependent manner. High doses of immobilized CD95 agonists or cellular CD95L almost completely silence T cells by blocking early TCR-induced signaling events. In contrast, under otherwise unchanged conditions, lower amounts of the same agonists dramatically augment TCR/CD3-driven activation and proliferation. In the present overview, we summarize these recent findings with a focus on the costimulatory capacity of CD95 in primary T cells and discuss potential implications for the T cell compartment and the interplay between T cells and CD95L-expressing cells including antigen-presenting cells.