NF-kappaB oscillations and cell-to-cell variability

Modeling of an immune response: Queuing network analysis of the impact of zinc and cadmium on macrophage activation

Chronic obstructive pulmonary disease is characterized by progressive, irreversible airflow obstruction resulting from an abnormal inflammatory response to noxious gases and particles. Alveolar macrophages rely on the transcription factors, nuclear factor κB and mitogen-activated protein kinase, among others, to facilitate the production of inflammatory mediators designed to help rid the lung of foreign pathogens and noxious stimuli. Building a kinetic model using queuing networks, provides a quantitative approach incorporating an initial number of individual molecules along with rates of the reactions in any given pathway. Accordingly, this model has been shown useful to model cell behavior including signal transduction, transcription, and metabolic pathways. The aim of this study was to determine whether a queuing theory model that involves lipopolysaccharide-mediated macrophage activation in tandem with changes in intracellular Cd and zinc (Zn) content or a lack thereof, would be useful to predict their impact on immune activation. We then validate our model with biologic cytokine output from human macrophages relative to the timing of innate immune activation. We believe that our results further prove the validity of the queuing theory approach to model intracellular molecular signaling and postulate that it can be useful to predict additional cell signaling pathways and the corresponding biological outcomes.

What Will B Will B: Identifying Molecular Determinants of Diverse B-Cell Fate Decisions Through Systems Biology

B-cells are the poster child for cellular diversity and heterogeneity. The diverse repertoire of B lymphocytes, each expressing unique antigen receptors, provides broad protection against pathogens. However, B-cell diversity goes beyond unique antigen receptors. Side-stepping B-cell receptor (BCR) diversity through BCR-independent stimuli or engineered organisms with monoclonal BCRs still results in seemingly identical B-cells reaching a wide variety of fates in response to the same challenge. Identifying to what extent the molecular state of a B-cell determines its fate is key to gaining a predictive understanding of B-cells and consequently the ability to control them with targeted therapies. Signals received by B-cells through transmembrane receptors converge on intracellular molecular signaling networks, which control whether each B-cell divides, dies, or differentiates into a number of antibody-secreting distinct B-cell subtypes. The signaling networks that interpret these signals are well known to be susceptible to molecular variability and noise, providing a potential source of diversity in cell fate decisions. Iterative mathematical modeling and experimental studies have provided quantitative insight into how B-cells achieve distinct fates in response to pathogenic stimuli. Here, we review how systems biology modeling of B-cells, and the molecular signaling networks controlling their fates, is revealing the key determinants of cell-to-cell variability in B-cell destiny.

An NFκB Activity Calculator to Delineate Signaling Crosstalk: Type I and II Interferons Enhance NFκB via Distinct Mechanisms

Nuclear factor kappa B (NFκB) is a transcription factor that controls inflammation and cell survival. In clinical histology, elevated NFκB activity is a hallmark of poor prognosis in inflammatory disease and cancer, and may be the result of a combination of diverse micro-environmental constituents. While previous quantitative studies of NFκB focused on its signaling dynamics in single cells, we address here how multiple stimuli may combine to control tissue level NFκB activity. We present a novel, simplified model of NFκB (SiMoN) that functions as an NFκB activity calculator. We demonstrate its utility by exploring how type I and type II interferons modulate NFκB activity in macrophages. Whereas, type I IFNs potentiate NFκB activity by inhibiting translation of IκBα and by elevating viral RNA sensor (RIG-I) expression, type II IFN amplifies NFκB activity by increasing the degradation of free IκB through transcriptional induction of proteasomal cap components (PA28). Both cross-regulatory mechanisms amplify NFκB activation in response to weaker (viral) inducers, while responses to stronger (bacterial or cytokine) inducers remain largely unaffected. Our work demonstrates how the NFκB calculator can reveal distinct mechanisms of crosstalk on NFκB activity in interferon-containing microenvironments.

Anatomy of a negative feedback loop: the case of IκBα

The magnitude, duration and oscillation of cellular signalling pathway responses are often limited by negative feedback loops, defined as an 'activator-induced inhibitor' regulatory motif. Within the NFκB signalling pathway, a key negative feedback regulator is IκBα. We show here that, contrary to current understanding, NFκB-inducible expression is not sufficient for providing effective negative feedback. We then employ computational simulations of NFκB signalling to identify IκBα molecular properties that are critical for proper negative feedback control and test the resulting predictions in biochemical and single-cell live-imaging studies. We identified nuclear import and nuclear export of IκBα and the IκBα-NFκB complex, as well as the free IκBα half-life, as key determinants of post-induction repression of NFκB and the potential for subsequent reactivation. Our work emphasizes that negative feedback is an emergent systems property determined by multiple molecular and biophysical properties in addition to the required 'activator-induced inhibitor' relationship.

Regulation of signal transduction by spatial parameters: a case in NF-κB oscillation

NF-κB is a transcription factor regulating expression of more than 500 genes, and its dysfunction leads to the autoimmune and inflammatory diseases. In malignant cancer cells, NF-κB is constitutively activated. Thus the elucidation of mechanisms for NF-κB regulation is important for the establishment of therapeutic treatment caused by incorrect NF-κB responses. Cytoplasmic NF-κB translocates to the nucleus by the application of extracellular stimuli such as cytokines. Nuclear NF-κB is known to oscillate with the cycle of 1.5-4.5 h, and it is thought that the oscillation pattern regulates the expression profiles of genes. In this review, first we briefly describe regulation mechanisms of NF-κB. Next, published computational simulations on the oscillation of NF-κB are summarised. There are at least 60 reports on the computational simulation and analysis of NF-κB oscillation. Third, the importance of a 'space' for the regulation of oscillation pattern of NF-κB is discussed, showing altered oscillation pattern by the change in spatial parameters such as diffusion coefficient, nuclear to cytoplasmic volume ratio (N/C ratio), and transport through nuclear membrane. Finally, simulations in a true intracellular space (TiCS), which is an intracellular 3D space reconstructed in a computer with organelles such as nucleus and mitochondria are discussed.

Towards elucidating the connection between epithelial-mesenchymal transitions and stemness

Epithelial cells undergoing epithelial-to-mesenchymal transitions have often been shown to behave as cancer stem cells, but the precise molecular connection remains elusive. At the genetic level, stemness is governed by LIN28/let-7 double inhibition switch, whereas EMT/MET is controlled by miR-200/ZEB double inhibition circuit and LIN28 is inhibited by miR-200, coupling the two modules. Here, using a specially devised theoretical framework to investigate the dynamics of the LIN28/let-7 system, we show that it can operate as a three-way switch (between low, high and intermediate LIN28 levels termed the D, U and hybrid D/U states) similar to the three-way operation of the miR-200/ZEB circuit that allows for the existence of a hybrid epithelial/mesenchymal (E/M) phenotype. We find significant correspondence between the existence of the three states of the two circuits: E-D, M-U and E/M-D/U. Incorporating the activation of OCT4 by LIN28, we find that the hybrid E/M phenotype has high likelihood (when compared with either the E or M states) to gain stemness. Combining the LIN28/let-7 regulation by NF-κB and c-MYC, we find that NF-κB, but not c-MYC, elevates the likelihood of E/M phenotype to gain stemness. Our results are consistent with emerging concept that partial EMT can lead to stemness.

Mathematical model of the Tat-Rev regulation of HIV-1 replication in an activated cell predicts the existence of oscillatory dynamics in the synthesis of viral components

Background

The life cycle of human immunodeficiency virus type-1 (HIV-1) makes possible the realization of regulatory strategies that can lead to complex dynamical behavior of the system. We analyze the strategy which is based on two feedback mechanisms, one mediating a positive regulation of the virus replication by Tat protein via the antitermination of the genomic RNAs transcription on TAR (transactivation responsive) element of the proviral DNA and the second mechanism providing a negative regulation of the splicing of the full-length (9 kb) RNAs and incompletely spliced (4 kb) RNAs via their transport from the nucleus to the cytoplasm. Although the existence of these two regulatory feedback loops has been considered in other mathematical models, none of them examined the conditions for the emergence of complex oscillatory patterns in the intracellular dynamics of viral components.

Results

We developed a mechanistic mathematical model for the Tat-Rev mediated regulation of HIV-1 replication, which considers the activation of proviral DNA transcription, the Tat-specific antitermination of transcription on TAR-element, resulting in the synthesis of the full-length 9 kb RNA, the splicing of the 9 kb RNA down to the 4 kb RNA and the 4 kb RNA to 2 kb RNA, the transport of 2 kb mRNAs from the nucleus to the cytoplasm by the intracellular mechanisms, the multiple binding of the Rev protein to RRE (Rev Response Element) sites on 9 kb and 4 kb RNA resulting in their export to the cytoplasm and the synthesis of Tat and Rev proteins in the cytoplasm followed by their transport into the nucleus. The degradation of all viral proteins and RNAs both in the cytoplasm and the nucleus is described. The model parameters values were derived from the published literature data. The model was used to examine the dynamics of the synthesis of the viral proteins Tat and Rev, the mRNAs under the intracellular conditions specific for activated HIV-1 infected macrophages. In addition, we analyzed alternative hypotheses for the re-cycling of the Rev proteins both in the cytoplasm and the nuclear pore complex.

Conclusions

The quantitative mathematical model of the Tat-Rev regulation of HIV-1 replication predicts the existence of oscillatory dynamics which depends on the efficacy of the Tat and TAR interaction as well as on the Rev-mediated transport processes. The biological relevance of the oscillatory regimes for the HIV-1 life cycle is discussed.

NF-κB-induced IL-6 ensures STAT3 activation and tumor aggressiveness in glioblastoma

Glioblastoma (GBM) is the most aggressive, neurologically destructive and deadly tumor of the central nervous system (CNS). In GBM, the transcription factors NF-κB and STAT3 are aberrantly activated and associated with tumor cell proliferation, survival, invasion and chemoresistance. In addition, common activators of NF-κB and STAT3, including TNF-α and IL-6, respectively, are abundantly expressed in GBM tumors. Herein, we sought to elucidate the signaling crosstalk that occurs between the NF-κB and STAT3 pathways in GBM tumors. Using cultured GBM cell lines as well as primary human GBM xenografts, we elucidated the signaling crosstalk between the NF-κB and STAT3 pathways utilizing approaches that either a) reduce NF-κB p65 expression, b) inhibit NF-κB activation, c) interfere with IL-6 signaling, or d) inhibit STAT3 activation. Using the clinically relevant human GBM xenograft model, we assessed the efficacy of inhibiting NF-κB and/or STAT3 alone or in combination in mice bearing intracranial xenograft tumors in vivo. We demonstrate that TNF-α-induced activation of NF-κB is sufficient to induce IL-6 expression, activate STAT3, and elevate STAT3 target gene expression in GBM cell lines and human GBM xenografts in vitro. Moreover, the combined inhibition of NF-κB and STAT3 signaling significantly increases survival of mice bearing intracranial tumors. We propose that in GBM, the activation of NF-κB ensures subsequent STAT3 activation through the expression of IL-6. These data verify that pharmacological interventions to effectively inhibit the activity of both NF-κB and STAT3 transcription factors must be used in order to reduce glioma size and aggressiveness.

RECEPTOR-DEPENDENT SENSITIVITY OF NF-κB TO LOW PHYSIOLOGICAL LEVEL

In the NFκB signaling pathway, cells respond to different concentrations of the TNFα signal by means of NFκB transcription factors. Previous studies showed that most cells are activated under high-dose stimulations and NFκB activation results in oscillations in nuclear NFκB abundance. Here, by analyzing sensitivity gain for the response of the nuclear NFκB to the number of cell-surface receptors under low-dose stimulations, we show that changes in the receptor number can give rise to significant changes in the nonsaturation part of the dose–response curve, where the receptor activation rates are very sensitive to stimulations. In addition, the number of the activated receptors tends to increase in a large range of stimulation dose and can significantly influence the expression of the downstream genes. These results imply that the number of cell-surface receptors plays a role of information encoding like frequency or amplitude encoding described in previous studies.

Statistical ensemble analysis for simulating extrinsic noise-driven response in NF-κB signaling networks

Background

Gene expression profiles and protein dynamics in single cells have a large cell-to-cell variability due to intracellular noise. Intracellular fluctuations originate from two sources: intrinsic noise due to the probabilistic nature of biochemical reactions and extrinsic noise due to randomized interactions of the cell with other cellular systems or its environment. Presently, there is no systematic parameterization and modeling scheme to simulate cellular response at the single cell level in the presence of extrinsic noise.

Results

In this paper, we propose a novel statistical ensemble method to simulate the distribution of heterogeneous cellular responses in single cells. We capture the effects of extrinsic noise by randomizing values of the model parameters. In this context, a statistical ensemble is a large number of system replicates, each with randomly sampled model parameters from biologically feasible intervals. We apply this statistical ensemble approach to the well-studied NF-κB signaling system. We predict several characteristic dynamic features of NF-κB response distributions; one of them is the dosage-dependent distribution of the first translocation time of NF-κB.

Conclusion

The distributions of heterogeneous cellular responses that our statistical ensemble formulation generates reveal the effect of different cellular conditions, e.g., effects due to wild type versus mutant cells or between different dosages of external stimulants. Distributions generated in the presence of extrinsic noise yield valuable insight into underlying regulatory mechanisms, which are sometimes otherwise hidden.

Heterogeneous kinetics of AKT signaling in individual cells are accounted for by variable protein concentration

In most solid cancers, cells harboring oncogenic mutations represent only a sub-fraction of the entire population. Within this sub-fraction the expression level of mutated proteins can vary significantly due to cellular variability limiting the efficiency of targeted therapy. To address the causes of the heterogeneity, we performed a systematic analysis of one of the most frequently mutated pathways in cancer cells, the phosphatidylinositol 3 kinase (PI3K) signaling pathway. Among others PI3K signaling is activated by the hepatocyte growth factor (HGF) that regulates proliferation of hepatocytes during liver regeneration but also fosters tumor cell proliferation. HGF-mediated responses of PI3K signaling were monitored both at the single cell and cell population level in primary mouse hepatocytes and in the hepatoma cell line Hepa1_6. Interestingly, we observed that the HGF-mediated AKT responses at the level of individual cells is rather heterogeneous. However, the overall average behavior of the single cells strongly resembled the dynamics of AKT activation determined at the cell population level. To gain insights into the molecular cause for the observed heterogeneous behavior of individual cells, we employed dynamic mathematical modeling in a stochastic framework. Our analysis demonstrated that intrinsic noise was not sufficient to explain the observed kinetic behavior, but rather the importance of extrinsic noise has to be considered. Thus, distinct from gene expression in the examined signaling pathway fluctuations of the reaction rates has only a minor impact whereas variability in the concentration of the various signaling components even in a clonal cell population is a key determinant for the kinetic behavior.

Roles of spatial parameters on the oscillation of nuclear NF-κB: computer simulations of a 3D spherical cell

Transcription factor NF-κB resides in the cytoplasm and translocates to the nucleus by application of extracellular stimuli. It is known that the nuclear NF-κB oscillates and different oscillation patterns lead to different gene expression. Nearly forty reports on modeling and simulation of nuclear NF-κB have been published to date. The computational models reported so far are temporal or two-dimensional, and the discussions on spatial parameters have not been involved or limited. Since spatial parameters in cancer cells such as nuclear to cytoplasmic volume (N/C) ratio are different from normal cells, it is important to understand the relationship between oscillation patterns and spatial parameters. Here we report simulations of a 3D computational model for the oscillation of nuclear NF-κB using A-Cell software. First, we found that the default biochemical kinetic constants used in the temporal model cannot replicate the experimentally observed oscillation in the 3D model. Thus, the default parameters should be changed in the 3D model. Second, spatial parameters such as N/C ratio, nuclear transport, diffusion coefficients, and the location of IκB synthesis were found to alter the oscillation pattern. Third, among them, larger N/C ratios resulted in persistent oscillation of nuclear NF-κB, and larger nuclear transport resulted in faster oscillation frequency. Our simulation results suggest that the changes in spatial parameters seen in cancer cells is one possible mechanism for alteration in the oscillation pattern of nuclear NF-κB and lead to the altered gene expression in these cells.

Lessons from mathematically modeling the NF-κB pathway

Mathematical modeling has proved to be a critically important approach in the study of many complex networks and dynamic systems in physics, engineering, chemistry, and biology. The nuclear factor κB (NF-κB) system consists of more than 50 proteins and protein complexes and is both a highly networked and dynamic system. To date, mathematical modeling has only addressed a small fraction of the molecular species and their regulation, but when employed in conjunction with experimental analysis has already led to important insights. Here, we provide a personal account of studying how the NF-κB signaling system functions using mathematical descriptions of the molecular mechanisms. We focus on the insights gained about some of the key regulatory components: the control of the steady state, the signaling dynamics, and signaling crosstalk. We also discuss the biological relevance of these regulatory systems properties.

Communicating oscillatory networks: frequency domain analysis

Background

Constructing predictive dynamic models of interacting signalling networks remains one of the great challenges facing systems biology. While detailed dynamical data exists about individual pathways, the task of combining such data without further lengthy experimentation is highly nontrivial. The communicating links between pathways, implicitly assumed to be unimportant and thus excluded, are precisely what become important in the larger system and must be reinstated. To maintain the delicate phase relationships between signals, signalling networks demand accurate dynamical parameters, but parameters optimised in isolation and under varying conditions are unlikely to remain optimal when combined. The computational burden of estimating parameters increases exponentially with increasing system size, so it is crucial to find precise and efficient ways of measuring the behaviour of systems, in order to re-use existing work.

Results

Motivated by the above, we present a new frequency domain-based systematic analysis technique that attempts to address the challenge of network assembly by defining a rigorous means to quantify the behaviour of stochastic systems. As our focus we construct a novel coupled oscillatory model of p53, NF-kB and the mammalian cell cycle, based on recent experimentally verified mathematical models. Informed by online databases of protein networks and interactions, we distilled their key elements into simplified models containing the most significant parts. Having coupled these systems, we constructed stochastic models for use in our frequency domain analysis. We used our new technique to investigate the crosstalk between the components of our model and measure the efficacy of certain network-based heuristic measures.

Conclusions

We find that the interactions between the networks we study are highly complex and not intuitive: (i) points of maximum perturbation do not necessarily correspond to points of maximum proximity to influence; (ii) increased coupling strength does not necessarily increase perturbation; (iii) different perturbations do not necessarily sum and (iv) overall, susceptibility to perturbation is amplitude and frequency dependent and cannot easily be predicted by heuristic measures.

Our methodology is particularly relevant for oscillatory systems, though not limited to these, and is most revealing when applied to the results of stochastic simulation. The technique is able to characterise precisely the distance in behaviour between different models, different systems and different parts within the same system. It can also measure the difference between different simulation algorithms used on the same system and can be used to inform the choice of dynamic parameters. By measuring crosstalk between subsystems it can also indicate mechanisms by which such systems may be controlled in experiments and therapeutics. We have thus found our technique of frequency domain analysis to be a valuable benchmark systems-biological tool.

MicroRNAs modulate the dynamics of the NF-κB signaling pathway

BACKGROUND

NF-κB, a major transcription factor involved in mammalian inflammatory signaling, is primarily involved in regulation of response to inflammatory cytokines and pathogens. Its levels are tightly regulated since uncontrolled inflammatory response can cause serious diseases. Mathematical models have been useful in revealing the underlying mechanisms, the dynamics, and other aspects of regulation in NF-κB signaling. The recognition that miRNAs are important regulators of gene expression, and that a number of miRNAs target different components of the NF-κB network, motivate the incorporation of miRNA regulated steps in existing mathematical models to help understand the quantitative aspects of miRNA mediated regulation.

METHODOLOGY/PRINCIPAL FINDINGS

In this study, two separate scenarios of miRNA regulation within an existing model are considered. In the first, miRNAs target adaptor proteins involved in the synthesis of IKK that serves as the NF-κB activator. In the second, miRNAs target different isoforms of IκB that act as NF-κB inhibitors. Simulations are carried out under two different conditions: when all three isoforms of IκB are present (wild type), and when only one isoform (IκBα) is present (knockout type). In both scenarios, oscillations in the NF-κB levels are observed and are found to be dependent on the levels of miRNAs.

CONCLUSIONS/SIGNIFICANCE

Computational modeling can provide fresh insights into intricate regulatory processes. The introduction of miRNAs affects the dynamics of the NF-κB signaling pathway in a manner that depends on the role of the target. This "fine-tuning" property of miRNAs helps to keep the system in check and prevents it from becoming uncontrolled. The results are consistent with earlier experimental findings.

Nuclear factor-kappa B localization and function within intrauterine tissues from term and preterm labor and cultured fetal membranes

BACKGROUND

The objective of this study was to quantify the nuclear localization and DNA binding activity of p65, the major transactivating nuclear factor-kappa B (NF-kappaB) subunit, in full-thickness fetal membranes (FM) and myometrium in the absence or presence of term or preterm labor.

METHODS

Paired full-thickness FM and myometrial samples were collected from women in the following cohorts: preterm no labor (PNL, N = 22), spontaneous preterm labor (PTL, N = 21), term no labor (TNL, N = 23), and spontaneous term labor (STL, N = 21). NF-kappaB p65 localization was assessed by immunohistochemistry, and DNA binding activity was evaluated using an enzyme-linked immunosorbent assay (ELISA)-based method.

RESULTS

Nuclear p65 labeling was rare in amnion and chorion, irrespective of clinical context. In decidua, nuclear p65 labeling was greater in the STL group relative to the TNL cohort, but there were no differences among the TNL, PTL, and PNL cohorts. In myometrium, diffuse p65 nuclear labeling was significantly associated with both term and preterm labor. There were no significant differences in ELISA-based p65 binding activity in amnion, choriodecidual, and myometrial specimens in the absence or presence of term labor. However, parallel experiments using cultured term fetal membranes demonstrated high levels of p65-like binding even the absence of cytokine stimulation, suggesting that this assay may be of limited value when applied to tissue specimens.

CONCLUSIONS

These results suggest that the decidua is an important site of NF-kappaB regulation in fetal membranes, and that mechanisms other than cytoplasmic sequestration may limit NF-kappaB activation prior to term.

A noisy paracrine signal determines the cellular NF-kappaB response to lipopolysaccharide

Nearly identical cells can exhibit substantially different responses to the same stimulus. We monitored the nuclear localization dynamics of nuclear factor kappaB (NF-kappaB) in single cells stimulated with tumor necrosis factor-alpha (TNF-alpha) and lipopolysaccharide (LPS). Cells stimulated with TNF-alpha have quantitative differences in NF-kappaB nuclear localization, whereas LPS-stimulated cells can be clustered into transient or persistent responders, representing two qualitatively different groups based on the NF-kappaB response. These distinct behaviors can be linked to a secondary paracrine signal secreted at low concentrations, such that not all cells undergo a second round of NF-kappaB activation. From our single-cell data, we built a computational model that captures cell variability, as well as population behaviors. Our findings show that mammalian cells can create "noisy" environments to produce diversified responses to stimuli.

Multiple roles of the NF-kappaB signaling pathway regulated by coupled negative feedback circuits

The NF-kappaB signaling pathway can perform multiple functional roles depending on specific cellular environments and cell types. Even in the same cell clones, the pathway can show different kinetic and phenotypic properties. It is believed that the complex networks controlling the NF-kappaB signaling pathway can generate these diverse and sometimes ambiguous phenomena. We noted, however, that the dynamics of NF-kappaB signaling pathway is highly stochastic and that the NF-kappaB signaling pathway contains multiple negative feedback circuits formed by IkappaB isoform proteins, IkappaBalpha and IkappaBepsilon in particular. Considering the topological similarity, their functional roles seem to be redundant, raising the question why different types of IkappaB isoforms need to exist. From extensive stochastic simulations of the NF-kappaB signaling pathway, we found that each IkappaB isoform actually conducts a different regulatory role through its own negative feedback. Specifically, our data suggest that IkappaBalpha controls the dynamic patterns of nuclear NF-kappaB, while IkappaBepsilon induces cellular heterogeneity of the NF-kappaB activities. These results may provide an answer to the question of how a single NF-kappaB signaling pathway can perform multiple biological functions even in the same clonal populations.

Pulsatile stimulation determines timing and specificity of NF-kappaB-dependent transcription

The nuclear factor kappaB (NF-kappaB) transcription factor regulates cellular stress responses and the immune response to infection. NF-kappaB activation results in oscillations in nuclear NF-kappaB abundance. To define the function of these oscillations, we treated cells with repeated short pulses of tumor necrosis factor-alpha at various intervals to mimic pulsatile inflammatory signals. At all pulse intervals that were analyzed, we observed synchronous cycles of NF-kappaB nuclear translocation. Lower frequency stimulations gave repeated full-amplitude translocations, whereas higher frequency pulses gave reduced translocation, indicating a failure to reset. Deterministic and stochastic mathematical models predicted how negative feedback loops regulate both the resetting of the system and cellular heterogeneity. Altering the stimulation intervals gave different patterns of NF-kappaB-dependent gene expression, which supports the idea that oscillation frequency has a functional role.

Understanding NF-kappaB signaling via mathematical modeling

Mammalian inflammatory signaling, for which NF-kappaB is a principal transcription factor, is an exquisite example of how cellular signaling pathways can be regulated to produce different yet specific responses to different inflammatory insults. Mathematical models, tightly linked to experiment, have been instrumental in unraveling the forms of regulation in NF-kappaB signaling and their underlying molecular mechanisms. Our initial model of the IkappaB-NF-kappaB signaling module highlighted the role of negative feedback in the control of NF-kappaB temporal dynamics and gene expression. Subsequent studies sparked by this work have helped to characterize additional feedback loops, the input-output behavior of the module, crosstalk between multiple NF-kappaB-activating pathways, and NF-kappaB oscillations. We anticipate that computational techniques will enable further progress in the NF-kappaB field, and the signal transduction field in general, and we discuss potential upcoming developments.

Requirements for two proximal NF-kappaB binding sites and IkappaB-zeta in IL-17A-induced human beta-defensin 2 expression by conducting airway epithelium

Among a panel of 21 cytokines (IL-1α, -1β, -2–13, and -15–18; interferon-γ; granulocyte-macrophage colony-stimulating factor; and tumor necrosis factor α), we have recently observed that IL-17A is the most potent inducer for human β-defensin 2 (hBD-2) in conducting airway epithelial cells (Kao, C. Y., Chen, Y., Thai, P., Wachi, S., Huang, F., Kim, C., Harper, R. W., and Wu, R. (2004) J. Immunol. 173, 3482–3491). The molecular basis of this regulation is not known. In this study, we demonstrated a coordinated degradation of inhibitory κB(IκB)-α followed by a nuclear translocation of p50 and p65 NF-κB subunits and their binding to NF-κB sites of hBD-2 promoter region. With site-directed mutagenesis, we demonstrated the requirement of two proximal NF-κB binding sites (pκB1, -205 to -186; pκB2, -596 to -572) but not the distal site (dκB, -2193 to -2182) in supporting IL-17A-induced hBD-2 promoter activity. These results are consistent with the data of the chromatin immunoprecipitation assay, which showed enhanced p50 binding to these pκB sites but not the dκB site in cells after IL-17A treatment. We also found that the NF-κB binding cofactor, IκB-ζ, was up-regulated by IL-17A, and the knockdown of IκB-ζ significantly diminished the IL-17A-induced hBD-2 expression. This is the first demonstration of the involvement of two proximal NF-κB sites and IκB-ζ in the regulation of hBD-2 by IL-17A, two important genes responsible for host defense.

Wires in the soup: quantitative models of cell signaling

Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of challenges. The underlying signal transduction networks enabling this response can be quite complex, and so sophisticated computational modeling coupled with precise experimentation is required to unravel them. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. Quantitative models of signaling pathways (e.g. NF-kappaB) can be gradually constructed through continuous experimental validation, and important lessons can be learnt from such exercises.

Deterministic and stochastic models of NFkappaB pathway

In the article, we discuss the state of art and perspectives in deterministic and stochastic models of NFkappaB regulatory module. The NFkappaB is a transcription factor controlling various immune responses including inflammation and apoptosis. It is tightly regulated by at least two negative feedback loops involving IkappaBalpha and A20. This mode of regulation results in nucleus-to-cytoplasm oscillations in NFkappaB localization, which induce subsequent waves of NFkappaB responsive genes. Single cell experiments carried by several groups provided comprehensive evidence that stochastic effects play an important role in NFkappaB regulation. From modeling point of view, living cells might be considered noisy or stochastic biochemical reactors. In eukaryotic cells, in which the number of protein or mRNA molecules is relatively large, stochastic effects primarily originate in regulation of gene activity. Transcriptional activity of a gene can be initiated by trans-activator molecules binding to the specific regulatory site(s) in the target gene. The stochastic event of gene activation is amplified by transcription and translation, since it results in a burst of mRNA molecules, and each copy of mRNA then serves as a template for numerous protein molecules. Another potential source of variability can be receptors activation. At low-dose stimulation, important in cell-to-cell signaling, the number of active receptors can be low enough to introduce substantial noise to downstream signaling. Stochastic modeling confirms the large variability in cell responses and shows that no cell behaves like an "average" cell. This high cell-to-cell variability can be one of the weapons of the immune defense. Such non-deterministic defense may be harder to overcome by relatively simple programs coded in viruses and other pathogens.

Single TNFalpha trimers mediating NF-kappaB activation: stochastic robustness of NF-kappaB signaling

Background

The NF-κB regulatory network controls innate immune response by transducing variety of pathogen-derived and cytokine stimuli into well defined single-cell gene regulatory events.

Results

We analyze the network by means of the model combining a deterministic description for molecular species with large cellular concentrations with two classes of stochastic switches: cell-surface receptor activation by TNFα ligand, and IκBα and A20 genes activation by NF-κB molecules. Both stochastic switches are associated with amplification pathways capable of translating single molecular events into tens of thousands of synthesized or degraded proteins. Here, we show that at a low TNFα dose only a fraction of cells are activated, but in these activated cells the amplification mechanisms assure that the amplitude of NF-κB nuclear translocation remains above a threshold. Similarly, the lower nuclear NF-κB concentration only reduces the probability of gene activation, but does not reduce gene expression of those responding.

Conclusion

These two effects provide a particular stochastic robustness in cell regulation, allowing cells to respond differently to the same stimuli, but causing their individual responses to be unequivocal. Both effects are likely to be crucial in the early immune response: Diversity in cell responses causes that the tissue defense is harder to overcome by relatively simple programs coded in viruses and other pathogens. The more focused single-cell responses help cells to choose their individual fates such as apoptosis or proliferation. The model supports the hypothesis that binding of single TNFα ligands is sufficient to induce massive NF-κB translocation and activation of NF-κB dependent genes.

Survival and apoptotic pathways initiated by TNF-alpha: modeling and predictions

We present a mathematical model which includes TNF-alpha initiated survival and apoptotic cascades, as well as nuclear transcription of IkappaB. These pathways play a crucial role in deciding cell fate in response to inflammation and infection. Our model incorporates known specific protein-protein interactions as identified by experiments. Using these biochemical interactions, we develop a mathematical model of the NF-kappaB-mediated survival and caspase-mediated apoptosis pathways. Using mass action kinetics, we follow the formation of the survival and late complexes as well as the dynamics of DNA fragmentation. The effect of TNF-alpha concentration on DNA fragmentation is modeled and compares well with experiment. Nuclear transcription is also modeled phenomenologically by means of time lagged cytosolic concentrations. This results in transcription related concentrations undergoing under-damped oscillations, in qualitative and quantitative agreement with experiment. Using a tumor cell as a hypothetical model, we explore the interplay between the components of the survival and apoptotic pathways. Results are presented which make predictions on the limits of cellular oscillations in terms of time delay, initial concentration ratios and other features of the model. The model also makes clear predictions on cell viability in terms of DNA damage within the framework of TNF-alpha stimulus duration.

Oscillations and temporal signalling in cells

The development of new techniques to quantitatively measure gene expression in cells has shed light on a number of systems that display oscillations in protein concentration. Here we review the different mechanisms which can produce oscillations in gene expression or protein concentration using a framework of simple mathematical models. We focus on three eukaryotic genetic regulatory networks which show 'ultradian' oscillations, with a time period of the order of hours, and involve, respectively, proteins important for development (Hes1), apoptosis (p53) and immune response (NF-kappaB). We argue that underlying all three is a common design consisting of a negative feedback loop with time delay which is responsible for the oscillatory behaviour.

Oscillations in the immune system

Oscillations are surprisingly common in the immune system, both in its healthy state and in disease. The most famous example is that of periodic fevers caused by the malaria parasite. A number of hereditary disorders, which also cause periodic fevers, have also been known for a long time. Various reports of oscillations in cytokine concentrations following antigen challenge have been published over at least the past three decades. Oscillations can also occur at the intracellular level. Calcium oscillations following T-cell activation are familiar to all immunologists, and metabolic and reactive oxygen species oscillations in neutrophils have been well documented. More recently, oscillations in nuclear factor kappaB activity following stimulation by tumor necrosis factor alpha have received considerable publicity. However, despite all of these examples, oscillations in the immune system still tend to be considered mainly as pathological aberrations, and their causes and significance remained largely unknown. This is partly because of a lack of awareness within the immunological community of the appropriate theoretical frameworks for describing and analyzing such behavior. We provide an introduction to these frameworks and give a survey of the currently known oscillations that occur within the immune system.

Minimal model of spiky oscillations in NF-kappaB signaling

The NF-kappaB signaling system is involved in a variety of cellular processes including immune response, inflammation, and apoptosis. Recent experiments have found oscillations in the nuclear-cytoplasmic translocation of the NF-kappaB transcription factor [Hoffmann, A., et al. (2002) Science 298, ; Nelson, D. E., et al. (2004) Science 306, .] How the cell uses the oscillations to differentiate input conditions and send specific signals to downstream genes is an open problem. We shed light on this issue by examining the small core network driving the oscillations, which we show is designed to produce periodic spikes in nuclear NF-kappaB concentration. The presence of oscillations is extremely robust to variation of parameters, depending mainly on the saturation of the active degradation rate of IkappaB, an inhibitor of NF-kappaB. The oscillations can be used to regulate downstream genes in a variety of ways. In particular, we show that genes to whose operator sites NF-kappaB binds and dissociates fast can respond very sensitively to changes in the input signal, with effective Hill coefficients of >20.