A model of TLR4 signaling and tolerance using a qualitative, particle-event-based method: introduction of spatially configured stochastic reaction chambers (SCSRC)

Introduction

There have been great advances in the examination and characterization of intracellular signaling and synthetic pathways. However, these pathways are generally represented using static diagrams when in reality they exist with considerable dynamic complexity. In addition to the expansion of existing mathematical pathway representation tools (many utilizing systems biology markup language format), there is a growing recognition that spatially explicit modeling methods may be necessary to capture essential aspects of intracellular dynamics. This paper introduces spatially configured stochastic reaction chambers (SCSRC), an agent-based modeling (ABM) framework that incorporates an abstracted molecular ‘event’ rule system with a spatially explicit representation of the relationship between signaling and synthetic compounds. Presented herein is an example of the SCSRC as applied to Toll-like receptor (TLR) 4 signaling and the inflammatory response.

Methods

The underlying rationale for the architecture of the SCSRC is described. A SCSRC model of TLR-4 signaling was developed after a review of the literature regarding TLR-4 signaling and downstream synthetic events. The TLR-4 SCSRC was implemented in the free-ware software platform, Netlogo. A series of in silico experiments were performed to evaluate the response of the TLR-4 SCSRC with respect to response to simulated administration of lipopolysaccharide (LPS). The pro-inflammatory response was represented by simulated secretion of tumor necrosis factor (TNF). Subsequent in silico experiments examined the response to of the TLR-4 SCSRC in terms of a simulated preconditioning effect represented as tolerance of pro-inflammatory signaling to a second dose of LPS.

Results

The SCSRC produces simulated dynamics of TLR-4 signaling in response to LPS stimulation that are qualitatively similar to that reported in the literature. The expression of various components of the signaling cascade demonstrated stochastic noise, consistent with molecular expression data reported in the literature. There is a dose dependent pro-inflammatory response effect seen with increasing initial doses of LPS, and there was also a dose dependent response with respect to preconditioning effect and the establishment of tolerance. Both of these dynamics are consistent with published responses to LPS.

Conclusions

The particle-based, spatially oriented SCSRC model of TLR-4 signaling captures the essential dynamics of the TLR-4 signal transduction cascade, including stochastic signal behavior, dose dependent response, negative feedback control, and preconditioning effect. This is accomplished even given a high degree of molecular event abstraction. The component detail of the SCSRC may allow for sequential parsing of various preconditioning effects, something not possible without computational modeling and simulation, and may give insight into the expected consequences and responses resulting from manipulation of one or many of these modulating factors. The SCSRC is admittedly a work in evolution, and future work will sequentially incorporate additional regulatory mechanisms, both intracellular and paracrine/autocrine, and improved mapping between the spatial chamber configuration and molecular event rules, and experimentally define biochemical reaction rate constants. However, the SCSRC has promise as a highly modular and flexible modeling method that is suited to the dynamic knowledge representation of intracellular processes.     

Escherichia coli LPS-induced LV dysfunction: role of toll-like receptor-4 in the adult heart

The precise molecular mechanisms responsible for sepsis-induced myocardial dysfunction remain undefined. Toll-like receptor-4 (TLR-4) engages lipopolysaccharide (LPS) and activates signaling pathways leading to the expression of proinflammatory cytokines implicated in myocardial dysfunction. We determined whether TLR-4 was necessary for LPS-induced myocardial dysfunction in vivo. The effects of LPS on left ventricular (LV) function were studied in mice with defective TLR-4 signaling (C3H/HeJ, TLR-4 deficient) and wild-type mice (C3HeB/FeJ). Mice (n = 5/group) were injected with LPS or diluent, and LV function was examined by using two-dimensional echocardiography and conductance catheters. LPS significantly decreased all indexes of LV function in wild-type mice when compared with controls; LV function was not depressed in the LPS-treated TLR-4-deficient mice relative to controls. LPS increased myocardial nitric oxide synthase-2 expression and cGMP only in wild-type mice. This study suggests that TLR-4 mediates the LV dysfunction that occurs in LPS-induced shock. Therefore, TLR-4 might be a therapeutic target for attenuating the effects of LPS on the heart.     

A Dynamic Analysis of IRS-PKR Signaling in Liver Cells: A Discrete Modeling Approach

A major challenge in systems biology is to develop a detailed dynamic understanding of the functions and behaviors in a particular cellular system, which depends on the elements and their inter-relationships in a specific network. Computational modeling plays an integral part in the study of network dynamics and uncovering the underlying mechanisms. Here we proposed a systematic approach that incorporates discrete dynamic modeling and experimental data to reconstruct a phenotype-specific network of cell signaling. A dynamic analysis of the insulin signaling system in liver cells provides a proof-of-concept application of the proposed methodology. Our group recently identified that double-stranded RNA-dependent protein kinase (PKR) plays an important role in the insulin signaling network. The dynamic behavior of the insulin signaling network is tuned by a variety of feedback pathways, many of which have the potential to cross talk with PKR. Given the complexity of insulin signaling, it is inefficient to experimentally test all possible interactions in the network to determine which pathways are functioning in our cell system. Our discrete dynamic model provides an in silico model framework that integrates potential interactions and assesses the contributions of the various interactions on the dynamic behavior of the signaling network. Simulations with the model generated testable hypothesis on the response of the network upon perturbation, which were experimentally evaluated to identify the pathways that function in our particular liver cell system. The modeling in combination with the experimental results enhanced our understanding of the insulin signaling dynamics and aided in generating a context-specific signaling network.     

Bacterial lipopolysaccharide activates NF-kappaB through toll-like receptor 4 (TLR-4) in cultured human dermal endothelial cells. Differential expression of TLR-4 and TLR-2 in endothelial cells

A missense mutation in the cytoplasmic domain of the Toll-like receptor-4 (TLR-4) has been identified as the defect responsible for lipopolysaccharide (LPS) hyporesponsiveness in C3H/HeJ mice. TLR-4 and TLR-2 have recently been implicated in LPS signaling in studies where these receptors were overexpressed in LPS non-responsive 293 human embryonic kidney cells. However, the signaling role of TLR-4 or TLR-2 in human cells with natural LPS response remains largely undefined. Here we show that human dermal microvessel endothelial cells (HMEC) and human umbilical vein endothelial cells express predominantly TLR-4 but very weak TLR-2 and respond vigorously to LPS but not to Mycobacterium tuberculosis 19-kDa lipoprotein. Transient transfection of non-signaling mutant forms of TLR-4 and anti-TLR-4 monoclonal antibody inhibited LPS-induced NF-kappaB activation in HMEC, while a monoclonal antibody against TLR-2 was ineffective. In contrast to LPS responsiveness, the ability of HMEC to respond to 19-kDa lipoprotein correlated with the expression of TLR-2. Transfection of TLR-2 into HMEC conferred responsiveness to 19-kDa lipoprotein. These data indicate that TLR-4 is the LPS signaling receptor in HMEC and that human endothelial cells (EC) express predominantly TLR-4 and weak TLR-2, which may explain why they do not respond to 19-kDa lipoprotein. The differential expression of TLRs on human EC may have important implications in the participation of vascular EC in innate immune defense mechanisms against various infectious pathogens, which may use different TLRs to signal.     

Lipopolysaccharide, tumor necrosis factor alpha, or interleukin-1beta triggers reactivation of latent cytomegalovirus in immunocompetent mice

We have previously shown that cytomegalovirus (CMV) can reactivate in lungs of nonimmunosuppressed patients during critical illness. Our recent work has shown that polymicrobial bacterial sepsis can trigger reactivation of latent murine CMV (MCMV). We hypothesize that MCMV reactivation following bacterial sepsis may be caused by inflammatory mediators. To test this hypothesis, BALB/c mice latently infected with Smith strain MCMV received sublethal intraperitoneal doses of lipopolysaccharide (LPS), tumor necrosis factor alpha (TNF-alpha), interleukin-1beta (IL-1beta), or saline. Lung tissue homogenates were evaluated for viral reactivation 3 weeks after mediator injection. Because LPS is known to signal via Toll-like receptor 4 (TLR-4) in mice, further studies blocking this signaling mechanism were performed using monoclonal MTS510. Finally, mice were tested with intravenous TNF-alpha to determine whether this would cause reactivation. All mice receiving sublethal intraperitoneal doses of LPS, TNF-alpha, or IL-1beta had pulmonary reactivation of latent MCMV 3 weeks following injection, and LPS caused MCMV reactivation with kinetics similar to those for sepsis. When TLR-4 signaling was blocked, exogenous LPS did not reactivate latent MCMV. Intravenous TNF-alpha administration at near-lethal doses did not reactivate MCMV. Exogenous intraperitoneal LPS, TNF-alpha, and IL-1beta are all capable of reactivating CMV from latency in lungs of previously healthy mice. LPS reactivation of MCMV appears dependent on TLR-4 signaling. Interestingly, intravenous TNF-alpha did not trigger reactivation, suggesting possible mechanistic differences that are discussed. We conclude that inflammatory disease states besides sepsis may be capable of reactivating CMV from latency.     

An autowave model of the bifurcation behavior of transformed cells in response to polysaccharide

Isolated Helianthus tuberosus L. polysaccharide (HTLP) with a molecular weight of 1–2 MDa has a wide range of biological activities, including the ability to switch transformed cells to an apoptotic pathway. A qualitative explanation for this effect has previously been proposed on the basis of the interactions among components of intracellular signaling pathways associated with the Dectin-1, TLR-6, and TNFR1 receptors and intracellular factors involved in regulating apoptosis. In this work, an autowave model is proposed to explain the switch between alternative modes of cell behavior in response to polysaccharide. The model is based on the modified FitzHugh–Nagumo system of equations. The parameters of the model were estimated numerically.     

Bistability analyses of a caspase activation model for receptor-induced apoptosis

Apoptosis is an important physiological process crucially involved in development and homeostasis of multicellular organisms. Although the major signaling pathways have been unraveled, a detailed mechanistic understanding of the complex underlying network remains elusive. We have translated here the current knowledge of the molecular mechanisms of the death-receptor-activated caspase cascade into a mathematical model. A reduction down to the apoptotic core machinery enables the application of analytical mathematical methods to evaluate the system behavior within a wide range of parameters. Using parameter values from the literature, the model reveals an unstable status of survival indicating the need for further control. Based on recent publications we tested one additional regulatory mechanism at the level of initiator caspase activation and demonstrated that the resulting system displays desired characteristics such as bistability. In addition, the results from our model studies allowed us to reconcile the fast kinetics of caspase 3 activation observed at the single cell level with the much slower kinetics found at the level of a cell population.     

Toll-like receptors pathway in common variable immune deficiency (CVID) and X-linked agammaglobulinemia (XLA)

Common variable immunodeficiency (CVID) and X-linked agammaglobulinemia (XLA) are two major humoral immunodeficiencies, causing a high rate of early age mortality in children. In order to identifiy the possible factors involved in the pathogenesis of CVID and XLA, recent studies have focused on Toll-like receptors (TLRs) and demonstrate the defects in different TLR pathways in immune cells of CVID and XLA patients. Herein, we measured TLR-4 and TLR-9 RNA levels and consequently TNF-α and IFN-α production in peripheral blood mononuclear cells (PBMCs) of patients with CVID and XLA. Contrary to healthy individuals, TLR-9 expression was not significantly increased after ligand stimulation, whereas ligand-induced TLR-4 expression was not significantly different from that in healthy control PBMCs. Lipopolysaccharide (LPS)-stimulated TNF-α production was significantly reduced in patients compared to controls, whereas IFN-α production was increased in all groups after CpG stimulation without any significant inter-group difference. Our data suggest that defects in TLR-9 activated pathways may be a result of the decreased TLR-9 expression, although TLR-9 is not the only modulator of IFN-α production in these patients. On the other hand, impaired signaling in TLR-4 activated pathways which results in significant reduction in TNF-α production are not related to a defect in TLR-4 expression.     

Multi-layered representation for cell signaling pathways

To understand complex signaling pathways and networks, it is necessary to develop a formal and structured representation of the available information in a format suitable for analysis by software tools. Due to the complexity and incompleteness of the current biological knowledge about cell signaling, such a device must be able to represent cellular pathways at differing levels of details, one level of information abstract enough to convey an essential signaling flow while hiding its details and another level of information detailed enough to explain the underlying mechanisms that account for the signaling flow described at a more abstract level. We have defined a formal ontology for cell-signaling events that allows us to describe these cellular pathways at various levels of abstraction. Using this formal representation, ROSPath (reactive oxygen species-mediated signaling pathway) database system has been implemented and made available on the web (rospath.ewha.ac.kr). ROSPath is a database system for reactive oxygen species (ROS)-mediated cell signaling pathways and signaling processes in molecular detail, which facilitates a comprehensive understanding of the regulatory mechanisms in signaling pathways. ROSPath includes growth factor-, stress-, and cytokine-induced signaling pathways containing about 500 unique proteins (mostly mammalian) and their related protein states, protein complexes, protein complex states, signaling interactions, signaling steps, and pathways. It is a web-based structured repository of information on the signaling pathways of interest and provides a means for managing data produced by large-scale and high-throughput techniques such as proteomics. Also, software tools are provided for querying, displaying, and analyzing pathways, thus furnishing an integrated web environment for visualizing and manipulating ROS-mediated cell-signaling events.     

Bistability and oscillations in the Huang-Ferrell model of MAPK signaling

Physicochemical models of signaling pathways are characterized by high levels of structural and parametric uncertainty, reflecting both incomplete knowledge about signal transduction and the intrinsic variability of cellular processes. As a result, these models try to predict the dynamics of systems with tens or even hundreds of free parameters. At this level of uncertainty, model analysis should emphasize statistics of systems-level properties, rather than the detailed structure of solutions or boundaries separating different dynamic regimes. Based on the combination of random parameter search and continuation algorithms, we developed a methodology for the statistical analysis of mechanistic signaling models. In applying it to the well-studied MAPK cascade model, we discovered a large region of oscillations and explained their emergence from single-stage bistability. The surprising abundance of strongly nonlinear (oscillatory and bistable) input/output maps revealed by our analysis may be one of the reasons why the MAPK cascade in vivo is embedded in more complex regulatory structures. We argue that this type of analysis should accompany nonlinear multiparameter studies of stationary as well as transient features in network dynamics.     

A simple mathematical model of signaling resulting from the binding of lipopolysaccharide with Toll-like receptor 4 demonstrates inherent preconditioning behavior

The complex biology of Gram-negative bacterial lipopolysaccharide (LPS) is central to the acute inflammatory response in sepsis and related diseases. Repeated treatment with LPS can lead to desensitization or enhancement of subsequent responses both in vitro and in vivo (a phenomenon known as preconditioning). Previous computational studies have demonstrated a role for anti-inflammatory influences in this process (J. Day, J. Rubin, Y. Vodovotz, C.C. Chow, A. Reynolds, G. Clermont, A reduced mathematical model of the acute inflammatory response: II. Capturing scenarios of repeated endotoxin administration. J. Theor. Biol. 242 (2006) 237). Since LPS signals via Toll-like receptor 4 (TLR4), we created a simple mathematical model in order to address the role of this receptor in both the normal and preconditioned response to LPS. We created a non-linear system of ordinary differential equations, consisting of free LPS, free TLR4, bound complex LPS-TLR4, and an intracellular signaling cascade (lumped into a single variable). We simulate the effects of preconditioning by small and large repeated doses of LPS on the system, varying the timing of the doses as well as the rate of expression of TLR4. Our simulations suggest that a simplified model of LPS/TLR4 signaling can account for complex preconditioning phenomena without invoking a specific signaling inhibition mechanism, but rather based on the dynamics of the signaling response itself, as well as the timing and magnitude of the LPS stimuli.     

Data-Derived Modeling Characterizes Plasticity of MAPK Signaling in Melanoma

The majority of melanomas have been shown to harbor somatic mutations in the RAS-RAF-MEK-MAPK and PI3K-AKT pathways, which play a major role in regulation of proliferation and survival. The prevalence of these mutations makes these kinase signal transduction pathways an attractive target for cancer therapy. However, tumors have generally shown adaptive resistance to treatment. This adaptation is achieved in melanoma through its ability to undergo neovascularization, migration and rearrangement of signaling pathways. To understand the dynamic, nonlinear behavior of signaling pathways in cancer, several computational modeling approaches have been suggested. Most of those models require that the pathway topology remains constant over the entire observation period. However, changes in topology might underlie adaptive behavior to drug treatment. To study signaling rearrangements, here we present a new approach based on Fuzzy Logic (FL) that predicts changes in network architecture over time. This adaptive modeling approach was used to investigate pathway dynamics in a newly acquired experimental dataset describing total and phosphorylated protein signaling over four days in A375 melanoma cell line exposed to different kinase inhibitors. First, a generalized strategy was established to implement a parameter-reduced FL model encoding non-linear activity of a signaling network in response to perturbation. Next, a literature-based topology was generated and parameters of the FL model were derived from the full experimental dataset. Subsequently, the temporal evolution of model performance was evaluated by leaving time-defined data points out of training. Emerging discrepancies between model predictions and experimental data at specific time points allowed the characterization of potential network rearrangement. We demonstrate that this adaptive FL modeling approach helps to enhance our mechanistic understanding of the molecular plasticity of melanoma.     

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties.     

Elementary signaling modes predict the essentiality of signal transduction network components

Background  

Understanding how signals propagate through signaling pathways and networks is a central goal in systems biology. Quantitative dynamic models help to achieve this understanding, but are difficult to construct and validate because of the scarcity of known mechanistic details and kinetic parameters. Structural and qualitative analysis is emerging as a feasible and useful alternative for interpreting signal transduction.     

5-Lipoxygenase Activating Protein (FLAP) Dependent Leukotriene Biosynthesis Inhibition (MK591) Attenuates Lipid A Endotoxin-Induced Inflammation

The Lipid A moiety of endotoxin potently activates TLR-4 dependent host innate immune responses. We demonstrate that Lipid-A mediated leukotriene biosynthesis regulates pathogen-associated molecular patterns (PAMP)-dependent macrophage activation. Stimulation of murine macrophages (RAW264.7) with E. coli 0111:B4 endotoxin (LPS) or Kdo2-lipid A (Lipid A) induced inflammation and Lipid A was sufficient to induce TLR-4 mediated macrophage inflammation and rapid ERK activation. The contribution of leukotriene biosynthesis was evaluated with a 5-lipoxygenase activating protein (FLAP) inhibitor, MK591. MK591 pre-treatment not only enhanced but also sustained ERK activation for up to 4 hours after LPS and Lipid A stimulation while inhibiting cell proliferation and enhancing cellular apoptosis. Leukotriene biosynthesis inhibition attenuated inflammation induced by either whole LPS or the Lipid A fraction. These responses were regulated by inhibition of the key biosynthesis enzymes for the proinflammatory eicosanoids, 5-lipoxygenase (5-LO), and cyclooxygenase-2 (COX-2) quantified by immunoblotting. Inhibition of leukotriene biosynthesis differentially regulated TLR-2 and TLR-4 cell surface expression assessed by flow cytometry, suggesting a close mechanistic association between TLR expression and 5-LO associated eicosanoid activity in activated macrophages. Furthermore, MK591 pre-treatment enhanced ERK activation and inhibited cell proliferation after LPS or Lipid A stimulation. These effects were regulated in part by increased apoptosis and modulation of cell surface TLR expression. Together, these data clarify the mechanistic association between 5-lipoxygenase activating protein-mediated leukotriene biosynthesis and 5-LO dependent eicosanoid metabolites in mediating the TLR-dependent inflammatory response after endotoxin exposure typical of bacterial sepsis.     

Synthetic Toll like receptor-4 (TLR-4) agonist peptides as a novel class of adjuvants

Background

Adjuvants serve as catalysts of the innate immune response by initiating a localized site of inflammation that is mitigated by the interactions between antigens and toll like receptor (TLR) proteins. Currently, the majority of vaccines are formulated with aluminum based adjuvants, which are associated with various side effects. In an effort to develop a new class of adjuvants, agonists of TLR proteins, such as bacterial products, would be natural candidates. Lipopolysaccharide (LPS), a major structural component of gram negative bacteria cell walls, induces the systemic inflammation observed in septic shock by interacting with TLR-4. The use of synthetic peptides of LPS or TLR-4 agonists, which mimic the interaction between TLR-4 and LPS, can potentially regulate cellular signal transduction pathways such that a localized inflammatory response is achieved similar to that generated by adjuvants.

Methodology/Principal Findings

We report the identification and activity of several peptides isolated using phage display combinatorial peptide technology, which functionally mimicked LPS. The activity of the LPS-TLR-4 interaction was assessed by NF-κB nuclear translocation analyses in HEK-BLUE™-4 cells, a cell culture model that expresses only TLR-4, and the murine macrophage cell line, RAW264.7. Furthermore, the LPS peptide mimics were capable of inducing inflammatory cytokine secretion from RAW264.7 cells. Lastly, ELISA analysis of serum from vaccinated BALB/c mice revealed that the LPS peptide mimics act as a functional adjuvant.

Conclusions/Significance

Our data demonstrate the identification of synthetic peptides that mimic LPS by interacting with TLR-4. This LPS mimotope-TLR-4 interaction will allow for the development and use of these peptides as a new class of adjuvants, namely TLR-4 agonists.     

Lipopolysaccharide Preconditioning Protects Hepatocytes from Ischemia/Reperfusion Injury (IRI) through Inhibiting ATF4-CHOP Pathway in Mice

Background

Low-dose lipopolysaccharide (LPS) preconditioning-induced liver protection has been demonstrated during ischemia-reperfusion injury (IRI) in several organs but has not been sufficiently elucidated underlying causal mechanism. This study investigated the role of low-dose LPS preconditioning on ATF4-CHOP pathway as well as the effects of the pathway on tissue injury and inflammation in a mouse model of liver partial-warm IRI.

Methods

LPS (100 µg/kg/d) was injected intraperitoneally two days before ischemia. Hepatic injury was evaluated based on serum alanine aminotransferase levels, histopathology, and caspase-3 activity. The ATF4-CHOP pathway and its related apoptotic molecules were investigated after reperfusion. The role of LPS preconditioning on apoptosis and ATF4-CHOP pathway was examined in vitro. Moreover, the effects of the ATF4-CHOP pathway on apoptosis, Caspase-12, and Caspase-3 were determined with ATF4 small interfering RNA (siRNA). Inflammatory cytokine expression was also checked after reperfusion. Inflammatory cytokines and related signaling pathways were analyzed in vitro in macrophages treated by LPS preconditioning or ATF4 siRNA.

Results

LPS preconditioning significantly attenuated liver injury after IRI. As demonstrated by in vitro experiments, LPS preconditioning significantly reduced the upregulation of the ATF4-CHOP pathway and inhibited Caspase-12 and Caspase-3 activation after IRI. Later experiments showed that ATF4 knockdown significantly suppressed CHOP, cleaved caspase-12 and caspase-3 expression, as well as inhibited hepatocellular apoptosis. In addition, in mice pretreated with LPS, TNF-α and IL-6 were inhibited after reperfusion, whereas IL-10 was upregulated. Similarly, low-dose LPS significantly inhibited TNF-α, IL-6, ATF4-CHOP pathway, NF-κB pathway, and ERK1/2 in high-dose LPS-stimulated macrophages, whereas IL-10 and cytokine signaling (SOCS)-3 suppressor were induced. Importantly, ATF4 siRNA is consistent with results of LPS preconditioning in macrophages.

Conclusions

This work is the first time to provide evidence for LPS preconditioning protects hepatocytes from IRI through inhibiting ATF4-CHOP pathway, which may be critical to reducing related apoptosis molecules and modulating innate inflammation.     

The intrinsic apoptotic pathway is required for lipopolysaccharide-induced lung endothelial cell death

LPS has been implicated in the pathogenesis of endothelial cell death associated with Gram-negative bacterial sepsis. The binding of LPS to the TLR-4 on the surface of endothelial cells initiates the formation of a death-inducing signaling complex at the cell surface. The subsequent signaling pathways that result in apoptotic cell death remain unclear and may differ among endothelial cells in different organs. We sought to determine whether LPS and cycloheximide-induced cell death in human lung microvascular endothelial cells (HmVECs) was dependent upon activation of the intrinsic apoptotic pathway and the generation of reactive oxygen species. We found that cells overexpressing the anti-apoptotic protein Bcl-X(L) were resistant to LPS and cycloheximide-induced death and that the proapoptotic Bcl-2 protein Bid was cleaved following treatment with LPS. The importance of Bid was confirmed by protection of Bid-deficient (bid(-/-)) mice from LPS-induced lung injury. Neither HmVECs treated with the combined superoxide dismutase/catalase mimetic EUK-134 nor HmVECs depleted of mitochondrial DNA (rho(0) cells) were protected against LPS and cycloheximide-induced death. We conclude that LPS and cycloheximide-induced death in HmVECs requires the intrinsic cell death pathway, but not the generation of reactive oxygen species.