Transient IκB Kinase Activity Mediates Temporal NF-κB Dynamics in Response to a Wide Range of Tumor Necrosis Factor-α Doses

Dual-specific autophosphorylation of kinase IKK2 enables phosphorylation of substrate IκBα through a phosphoenzyme intermediate

Rapid and high-fidelity phosphorylation of two serines (S32 and S36) of IκBα by a prototype Ser/Thr kinase IKK2 is critical for fruitful canonical NF-κB activation. Here, we report that IKK2 is a dual specificity Ser/Thr kinase that autophosphorylates itself at tyrosine residues in addition to its activation loop serines. Mutation of one such tyrosine, Y169, located in proximity to the active site, to phenylalanine, renders IKK2 inactive for phosphorylation of S32 of IκBα. Surprisingly, auto-phosphorylated IKK2 relayed phosphate group(s) to IκBα without ATP when ADP is present. We also observed that mutation of K44, an ATP-binding lysine conserved in all protein kinases, to methionine renders IKK2 inactive towards specific phosphorylation of S32 or S36 of IκBα, but not non-specific substrates. These observations highlight an unusual evolution of IKK2, in which autophosphorylation of tyrosine(s) in the activation loop and the invariant ATP-binding K44 residue define its signal-responsive substrate specificity ensuring the fidelity of NF-κB activation.

Co-imaging of RelA and c-Rel reveals features of NF-κB signaling for ligand discrimination

Individual cell sensing of external cues has evolved through the temporal patterns in signaling. Since nuclear factor κB (NF-κB) signaling dynamics have been examined using a single subunit, RelA, it remains unclear whether more information might be transmitted via other subunits. Using NF-κB double-knockin reporter mice, we monitored both canonical NF-κB subunits, RelA and c-Rel, simultaneously in single macrophages by quantitative live-cell imaging. We show that signaling features of RelA and c-Rel convey more information about the stimuli than those of either subunit alone. Machine learning is used to predict the ligand identity accurately based on RelA and c-Rel signaling features without considering the co-activated factors. Ligand discrimination is achieved through selective non-redundancy of RelA and c-Rel signaling dynamics, as well as their temporal coordination. These results suggest a potential role of c-Rel in fine-tuning immune responses and highlight the need for approaches that will elucidate the mechanisms regulating NF-κB subunit specificity.

ZC3H11A loss of function enhances NF-κB signaling through defective IκBα protein expression

ZC3H11A is a cellular protein associated with the transcription export (TREX) complex that is induced during heat-shock. Several nuclear-replicating viruses exploit the mRNA export mechanism of ZC3H11A protein for their efficient replication. Here we show that ZC3H11A protein plays a role in regulation of NF-κB signal transduction. Depletion of ZC3H11A resulted in enhanced NF-κB mediated signaling, with upregulation of numerous innate immune related mRNAs, including IL-6 and a large group of interferon-stimulated genes. IL-6 upregulation in the absence of the ZC3H11A protein correlated with an increased NF-κB transcription factor binding to the IL-6 promoter and decreased IL-6 mRNA decay. The enhanced NF-κB signaling pathway in ZC3H11A deficient cells correlated with a defect in IκBα inhibitory mRNA and protein accumulation. Upon ZC3H11A depletion The IκBα mRNA was retained in the cell nucleus resulting in failure to maintain normal levels of the cytoplasmic IκBα mRNA and protein that is essential for its inhibitory feedback loop on NF-κB activity. These findings indicate towards a previously unknown mechanism of ZC3H11A in regulating the NF-κB pathway at the level of IkBα mRNA export.

Spatiotemporal NF-κB dynamics encodes the position, amplitude, and duration of local immune inputs

Infected cells communicate through secreted signaling molecules like cytokines, which carry information about pathogens. How differences in cytokine secretion affect inflammatory signaling over space and how responding cells decode information from propagating cytokines are not understood. By computationally and experimentally studying NF-κB dynamics in cocultures of signal-sending cells (macrophages) and signal-receiving cells (fibroblasts), we find that cytokine signals are transmitted by wave-like propagation of NF-κB activity and create well-defined activation zones in responding cells. NF-κB dynamics in responding cells can simultaneously encode information about cytokine dose, duration, and distance to the cytokine source. Spatially resolved transcriptional analysis reveals that responding cells transmit local cytokine information to distance-specific proinflammatory gene expression patterns, creating "gene expression zones." Despite single-cell variability, the size and duration of the signaling zone are tightly controlled by the macrophage secretion profile. Our results highlight how macrophages tune cytokine secretion to control signal transmission distance and how inflammatory signaling interprets these signals in space and time.

Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design

BACKGROUND

Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.

METHODS

We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.

RESULTS

In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation.

CONCLUSIONS

Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter. Video Abstract.

Stimulus-specific responses in innate immunity: Multilayered regulatory circuits

Immune sentinel cells initiate immune responses to pathogens and tissue injury and are capable of producing highly stimulus-specific responses. Insight into the mechanisms underlying such specificity has come from the identification of regulatory factors and biochemical pathways, as well as the definition of signaling circuits that enable combinatorial and temporal coding of information. Here, we review the multi-layered molecular mechanisms that underlie stimulus-specific gene expression in macrophages. We categorize components of inflammatory and anti-pathogenic signaling pathways into five layers of regulatory control and discuss unifying mechanisms determining signaling characteristics at each layer. In this context, we review mechanisms that enable combinatorial and temporal encoding of information, identify recurring regulatory motifs and principles, and present strategies for integrating experimental and computational approaches toward the understanding of signaling specificity in innate immunity.

Six distinct NFκB signaling codons convey discrete information to distinguish stimuli and enable appropriate macrophage responses

Macrophages initiate inflammatory responses via the transcription factor NFκB. The temporal pattern of NFκB activity determines which genes are expressed and thus, the type of response that ensues. Here, we examined how information about the stimulus is encoded in the dynamics of NFκB activity. We generated an mVenus-RelA reporter mouse line to enable high-throughput live-cell analysis of primary macrophages responding to host- and pathogen-derived stimuli. An information-theoretic workflow identified six dynamical features-termed signaling codons-that convey stimulus information to the nucleus. In particular, oscillatory trajectories were a hallmark of responses to cytokine but not pathogen-derived stimuli. Single-cell imaging and RNA sequencing of macrophages from a mouse model of Sjögren's syndrome revealed inappropriate responses to stimuli, suggestive of confusion of two NFκB signaling codons. Thus, the dynamics of NFκB signaling classify immune threats through six signaling codons, and signal confusion based on defective codon deployment may underlie the etiology of some inflammatory diseases.

Mechanistic dissection of spatial organization in NF-κB signaling pathways by hybrid simulations

The nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is one of the most important transcription factors involved in the regulation of inflammatory signaling pathways. Inappropriate activation of these pathways has been linked to autoimmunity and cancers. Emerging experimental evidences have been showing the existence of elaborate spatial organizations for various molecular components in the pathways. One example is the scaffold protein tumor necrosis factor receptor associated factor (TRAF). While most TRAF proteins form trimeric quaternary structure through their coiled-coil regions, the N-terminal region of some members in the family can further be dimerized. This dimerization of TRAF trimers can drive them into higher-order clusters as a response to receptor stimulation, which functions as a spatial platform to mediate the downstream poly-ubiquitination. However, the molecular mechanism underlying the TRAF protein clustering and its functional impacts are not well-understood. In this article, we developed a hybrid simulation method to tackle this problem. The assembly of TRAF-based signaling platform at the membrane-proximal region is modeled with spatial resolution, while the dynamics of downstream signaling network, including the negative feedbacks through various signaling inhibitors, is simulated as stochastic chemical reactions. These two algorithms are further synchronized under a multiscale simulation framework. Using this computational model, we illustrated that the formation of TRAF signaling platform can trigger an oscillatory NF-κB response. We further demonstrated that the temporal patterns of downstream signal oscillations are closely regulated by the spatial factors of TRAF clustering, such as the geometry and energy of dimerization between TRAF trimers. In general, our study sheds light on the basic mechanism of NF-κB signaling pathway and highlights the functional importance of spatial regulation within the pathway. The simulation framework also showcases its potential of application to other signaling pathways in cells.

NF-κB responds to absolute differences in cytokine concentrations

Cells receive a wide range of dynamic signaling inputs during immune regulation, but how gene regulatory networks measure such dynamic inputs is not well understood. Here, we used microfluidic single-cell analysis and mathematical modeling to study how the NF-κB pathway responds to immune inputs that vary over time such as increasing, decreasing, or fluctuating cytokine signals. We found that NF-κB activity responded to the absolute difference in cytokine concentration and not to the concentration itself. Our analyses revealed that negative feedback by the regulatory proteins A20 and IκBα enabled differential responses to changes in cytokine dose by providing a short-term memory of previous cytokine concentrations and by continuously resetting kinase cycling and receptor abundance. Investigation of NF-κB target gene expression showed that cells exhibited distinct transcriptional responses under different dynamic cytokine profiles. Our results demonstrate how cells use simple network motifs and transcription factor dynamics to efficiently extract information from complex signaling environments.

Mathematical modeling of canonical and non-canonical NF-κB pathways in TNF stimulation

BACKGROUND AND OBJECTIVE

NF-κB can be activated by the canonical and non-canonical pathways. These two pathways interplay via the TRAF1|NIK complex after stimulation by TNF. However existing mathematical models of two pathways are inadequate. In this context, an improved mathematical model is constructed to simulate these two pathways and their coupling stimulated by TNF.

METHODS

A schematic description of two NF-κB pathways and their relation after TNF stimulation is constructed at first. Then twenty-eight ordinary differential equations are utilized to build the mathematical model. Model equations are solved via the ordinary differential equation solver (ode23).

RESULTS

The proposed model firstly reconstructs the changes in concentrations of NF-κB pathway related biochemical factors with time, and further investigates the underlying mechanism of interaction between two pathways through the TRAF1|NIK complex after stimulation.

CONCLUSIONS

The model is validated through good agreement between simulation results and published experimental observations. This study helps to well understand the canonical and non-canonical pathways and their interaction. It also provides a potential tool to investigate how the dysregulated pathways act in pathological conditions.

Immune Differentiation Regulator p100 Tunes NF-κB Responses to TNF

Tumor necrosis factor (TNF) is a pleiotropic cytokine whose primary physiological function involves coordinating inflammatory and adaptive immune responses. However, uncontrolled TNF signaling causes aberrant inflammation and has been implicated in several human ailments. Therefore, an understanding of the molecular mechanisms underlying dynamical and gene controls of TNF signaling bear significance for human health. As such, TNF engages the canonical nuclear factor kappa B (NF-κB) pathway to activate RelA:p50 heterodimers, which induce expression of specific immune response genes. Brief and chronic TNF stimulation produces transient and long-lasting NF-κB activities, respectively. Negative feedback regulators of the canonical pathway, including IκBα, are thought to ensure transient RelA:p50 responses to short-lived TNF signals. The non-canonical NF-κB pathway mediates RelB activity during immune differentiation involving p100. We uncovered an unexpected role of p100 in TNF signaling. Brief TNF stimulation of p100-deficient cells triggered an additional late NF-κB activity consisting of RelB:p50 heterodimers, which modified the TNF-induced gene-expression program. In p100-deficient cells subjected to brief TNF stimulation, RelB:p50 not only sustained the expression of a subset of RelA-target immune response genes but also activated additional genes that were not normally induced by TNF in WT mouse embryonic fibroblasts (MEFs) and were related to immune differentiation and metabolic processes. Despite this RelB-mediated distinct gene control, however, RelA and RelB bound to mostly overlapping chromatin sites in p100-deficient cells. Repeated TNF pulses strengthened this RelB:p50 activity, which was supported by NF-κB-driven RelB synthesis. Finally, brief TNF stimulation elicited late-acting expressions of NF-κB target pro-survival genes in p100-deficient myeloma cells. In sum, our study suggests that the immune-differentiation regulator p100 enforces specificity of TNF signaling and that varied p100 levels may provide for modifying TNF responses in diverse physiological and pathological settings.

The effects of IKK-beta inhibition on early NF-kappa-B activation and transcription of downstream genes

Small molecule approaches targeting the nuclear factor kappa B (NF-kB) pathway, a regulator of inflammation, have thus far proven unsuccessful in the clinic in part due to the complex pleiotropic nature of this network. Downstream effects depend on multiple factors including stimulus-specific temporal patterns of NF-kB activity. Despite considerable advances, genome-level impact of changes in temporal NF-kB activity caused by inhibitors and their stimulus dependency remains unexplored. This study evaluates the effects of pathway inhibitors on early NF-κB activity and downstream gene transcription. 3T3 fibroblasts were treated with SC-514, an inhibitor targeted to the NF-kB pathway, prior to stimulation with interleukin 1 beta (IL-1β) or tumor necrosis factor alpha (TNF-α). Stimulus induced NF-κB activation was quantified using immunofluorescence imaging over 90-minutes and gene expression tracked over 6-hours using mRNA TagSeq. When stimulated with IL-1β or TNF-α, significant differences (P < 0.05, two-way ANOVA), were observed in the temporal profiles of NF-κB activation between treated and untreated cells. Increasing numbers of differentially expressed genes (P < 0.01) were observed at higher inhibitor concentrations. Individual gene expression profiles varied in an inhibitor concentration and stimulus-dependent manner. The results in this study demonstrate small molecule inhibitors acting on pleiotropic pathway components can alter signal dynamics in a stimulus-dependent manner and affect gene response in complex ways.

Lipopolysaccharide-induced NF-κB nuclear translocation is primarily dependent on MyD88, but TNFα expression requires TRIF and MyD88

TLR4 signalling through the MyD88 and TRIF-dependent pathways initiates translocation of the transcription factor NF-κB into the nucleus. In cell population studies using mathematical modeling and functional analyses, Cheng et al. suggested that LPS-driven activation of MyD88, in the absence of TRIF, impairs NF-κB translocation. We tested the model proposed by Cheng et al. using real-time single cell analysis in macrophages expressing EGFP-tagged p65 and a TNFα promoter-driven mCherry. Following LPS stimulation, cells lacking TRIF show a pattern of NF-κB dynamics that is unaltered from wild-type cells, but activation of the TNFα promoter is impaired. In macrophages lacking MyD88, there is minimal NF-κB translocation to the nucleus in response to LPS stimulation, and there is no activation of the TNFα promoter. These findings confirm that signalling through MyD88 is the primary driver for LPS-dependent NF-κB translocation to the nucleus. The pattern of NF-κB dynamics in TRIF-deficient cells does not, however, directly reflect the kinetics of TNFα promoter activation, supporting the concept that TRIF-dependent signalling plays an important role in the transcription of this cytokine.

Sensitivity of signaling pathway dynamics to plasmid transfection and its consequences

This paper deals with development of signaling pathways models and using plasmid-based experiments to support parameter estimation. We show that if cells transfected with plasmids are used in experiments, the models should include additional components that describe explicitly effects induced by plasmids. Otherwise, when the model is used to analyze responses of wild type, i.e. non-transfected cells, it may not capture their dynamics properly or even lead to false conclusions. In order to illustrate this, an original mathematical model of miRNA-mediated control of gene expression in the NFκB pathway is presented. The paper shows what artifacts might appear due to experimental procedures and how to develop the models in order to avoid pursuing these artifacts instead of real kinetics.

Mathematical Models for Immunology: Current State of the Art and Future Research Directions

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years.

Dynamic NF-κB and E2F interactions control the priority and timing of inflammatory signalling and cell proliferation

Dynamic cellular systems reprogram gene expression to ensure appropriate cellular fate responses to specific extracellular cues. Here we demonstrate that the dynamics of Nuclear Factor kappa B (NF-κB) signalling and the cell cycle are prioritised differently depending on the timing of an inflammatory signal. Using iterative experimental and computational analyses, we show physical and functional interactions between NF-κB and the E2 Factor 1 (E2F-1) and E2 Factor 4 (E2F-4) cell cycle regulators. These interactions modulate the NF-κB response. In S-phase, the NF-κB response was delayed or repressed, while cell cycle progression was unimpeded. By contrast, activation of NF-κB at the G1/S boundary resulted in a longer cell cycle and more synchronous initial NF-κB responses between cells. These data identify new mechanisms by which the cellular response to stress is differentially controlled at different stages of the cell cycle.

DOI:http://dx.doi.org/10.7554/eLife.10473.001

Investigating how cells adapt to the constantly changing environment inside the body is vitally important for understanding how the body responds to an injury or infection. One of the ways in which human cells adapt is by dividing to produce new cells. This takes place in a repeating pattern of events, known as the cell cycle, through which a cell copies its DNA (in a stage known as S-phase) and then divides to make two daughter cells. Each stage of the cell cycle is tightly controlled; for example, a family of proteins called E2 factors control the entry of the cell into S phase.

“Inflammatory” signals produced by a wound or during an infection can activate a protein called Nuclear Factor-kappaB (NF-κB), which controls the activity of genes that allow cells to adapt to the situation. Research shows that the activity of NF-κB is also regulated by the cell cycle, but it has not been clear how this works. Here, Ankers et al. investigated whether the stage of the cell cycle might affect how NF-κB responds to inflammatory signals.

The experiments show that the NF-κB response was stronger in cells that were just about to enter S-phase than in cells that were already copying their DNA. An E2 factor called E2F-1 –which accumulates in the run up to S-phase – interacts with NF-κB and can alter the activity of certain genes. However, during S-phase, another E2 factor family member called E2F-4 binds to NF-κB and represses its activation. Next, Ankers et al. used a mathematical model to understand how these protein interactions can affect the response of cells to inflammatory signals.

These findings suggest that direct interactions between E2 factor proteins and NF-κB enable cells to decide whether to divide or react in different ways to inflammatory signals. The research tools developed in this study, combined with other new experimental techniques, will allow researchers to accurately predict how cells will respond to inflammatory signals at different points in the cell cycle.

DOI:http://dx.doi.org/10.7554/eLife.10473.002

Methamphetamine abuse affects gene expression in brain-derived microglia of SIV-infected macaques to enhance inflammation and promote virus targets

BACKGROUND

Methamphetamine (Meth) abuse is a major health problem linked to the aggravation of HIV- associated complications, especially within the Central Nervous System (CNS). Within the CNS, Meth has the ability to modify the activity/function of innate immune cells and increase brain viral loads. Here, we examined changes in the gene expression profile of neuron-free microglial cell preparations isolated from the brain of macaques infected with the Simian Immunodeficiency Virus (SIV), a model of neuroAIDS, and exposed to Meth. We aimed to identify molecular patterns triggered by Meth that could explain the detection of higher brain viral loads and the development of a pro-inflammatory CNS environment in the brain of infected drug abusers.

RESULTS

We found that Meth alone has a strong effect on the transcription of genes associated with immune pathways, particularly inflammation and chemotaxis. Systems analysis led to a strong correlation between Meth exposure and enhancement of molecules associated with chemokines and chemokine receptors, especially CXCR4 and CCR5, which function as co-receptors for viral entry. The increase in CCR5 expression was confirmed in the brain in correlation with increased brain viral load.

CONCLUSIONS

Meth enhances the availability of CCR5-expressing cells for SIV in the brain, in correlation with increased viral load. This suggests that Meth is an important factor in the susceptibility to the infection and to the aggravated CNS inflammatory pathology associated with SIV in macaques and HIV in humans.

High-Content Quantification of Single-Cell Immune Dynamics

Cells receive time-varying signals from the environment and generate functional responses by secreting their own signaling molecules. Characterizing dynamic input-output relationships in single cells is crucial for understanding and modeling cellular systems. We developed an automated microfluidic system that delivers precisely defined dynamical inputs to individual living cells and simultaneously measures key immune parameters dynamically. Our system combines nanoliter immunoassays, microfluidic input generation, and time-lapse microscopy, enabling study of previously untestable aspects of immunity by measuring time-dependent cytokine secretion and transcription factor activity from single cells stimulated with dynamic inflammatory inputs. Employing this system to analyze macrophage signal processing under pathogen inputs, we found that the dynamics of TNF secretion are highly heterogeneous and surprisingly uncorrelated with the dynamics of NF-κB, the transcription factor controlling TNF production. Computational modeling of the LPS/TLR4 pathway shows that post-transcriptional regulation by TRIF is a key determinant of noisy and uncorrelated TNF secretion dynamics in single macrophages.

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Dynamic stimulation of single immune cells with a versatile microfluidic device

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Coupled longitudinal measurements of NF-κB localization and TNF secretion on the same cell

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Single-cell harvesting, staining, and mRNA quantification on the same device

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High-content dataset, and modeling of TRIF-based noise in TNF secretion

Signaling via the NFκB system

The nuclear factor kappa B (NFκB) family of transcription factors is a key regulator of immune development, immune responses, inflammation, and cancer. The NFκB signaling system (defined by the interactions between NFκB dimers, IκB regulators, and IKK complexes) is responsive to a number of stimuli, and upon ligand-receptor engagement, distinct cellular outcomes, appropriate to the specific signal received, are set into motion. After almost three decades of study, many signaling mechanisms are well understood, rendering them amenable to mathematical modeling, which can reveal deeper insights about the regulatory design principles. While other reviews have focused on upstream, receptor proximal signaling (Hayden MS, Ghosh S. Signaling to NF-κB. Genes Dev 2004, 18:2195-2224; Verstrepen L, Bekaert T, Chau TL, Tavernier J, Chariot A, Beyaert R. TLR-4, IL-1R and TNF-R signaling to NF-κB: variations on a common theme. Cell Mol Life Sci 2008, 65:2964-2978), and advances through computational modeling (Basak S, Behar M, Hoffmann A. Lessons from mathematically modeling the NF-κB pathway. Immunol Rev 2012, 246:221-238; Williams R, Timmis J, Qwarnstrom E. Computational models of the NF-KB signalling pathway. Computation 2014, 2:131), in this review we aim to summarize the current understanding of the NFκB signaling system itself, the molecular mechanisms, and systems properties that are key to its diverse biological functions, and we discuss remaining questions in the field. WIREs Syst Biol Med 2016, 8:227-241. doi: 10.1002/wsbm.1331 For further resources related to this article, please visit the WIREs website.

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.

Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features

Cell signaling dynamics and transcriptional regulatory activities are variable within specific cell types responding to an identical stimulus. In addition to studying the network interactions, there is much interest in utilizing single cell scale data to elucidate the non-random aspects of the variability involved in cellular decision making. Previous studies have considered the information transfer between the signaling and transcriptional domains based on an instantaneous relationship between the molecular activities. These studies predict a limited binary on/off encoding mechanism which underestimates the complexity of biological information processing, and hence the utility of single cell resolution data. Here we pursue a novel strategy that reformulates the information transfer problem as involving dynamic features of signaling rather than molecular abundances. We pursue a computational approach to test if and how the transcriptional regulatory activity patterns can be informative of the temporal history of signaling. Our analysis reveals (1) the dynamic features of signaling that significantly alter transcriptional regulatory patterns (encoding), and (2) the temporal history of signaling that can be inferred from single cell scale snapshots of transcriptional activity (decoding). Immediate early gene expression patterns were informative of signaling peak retention kinetics, whereas transcription factor activity patterns were informative of activation and deactivation kinetics of signaling. Moreover, the information processing aspects varied across the network, with each component encoding a selective subset of the dynamic signaling features. We developed novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components. Unsupervised clustering of the maps revealed two groups that aligned with network motifs distinguished by transcriptional feedforward vs feedback interactions. Our new computational methodology impacts the single cell scale experiments by identifying downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses.

Single cell studies have shown that differential patterns in the dynamics of signaling proteins, transcription factor activity, gene expression, etc. produce distinct downstream outcomes. The opposite also holds true where particular cellular outcomes have been found to be associated with the dynamical pattern of one or more signaling molecules. Signaling pathways, therefore, serve as signal processing units to inform specific downstream regulation. However, the functional capabilities of the dynamic aspects of signaling are not well understood. To address this issue, we developed a new approach that evaluates information processing between dynamic features in signaling patterns and transcriptional regulatory activity. Our work demonstrates that the information transfer occur through decoding of temporal history of signals rather than only through instantaneous correlations. Moreover, our results identify regulatory network motifs as the critical components in the information processing and filtering of variability in signaling dynamics to produce distinct patterns of downstream transcriptional responses. Our methodology can be broadly applied to single cell scale data on experimentally accessible downstream measures to infer dynamic aspects of upstream signaling.

Regulation of NF-κB Oscillation by Nuclear Transport: Mechanisms Determining the Persistency and Frequency of Oscillation

The activated transcription factor NF-κB shuttles between the cytoplasm and the nucleus resulting in the oscillation of nuclear NF-κB (NF-κB_n). The oscillation pattern of NF-κB_n is implicated in the regulation of gene expression profiles. Using computational models, we previously reported that spatial parameters, such as the diffusion coefficient, nuclear to cytoplasmic volume ratio, transport through the nuclear envelope, and the loci of translation of IκB protein, modified the oscillation pattern of NF-κB_n. In a subsequent report, we elucidated the importance of the “reset” of NF-κB_n (returning of NF-κB to the original level) and of a “reservoir” of IκB in the cytoplasm. When the diffusion coefficient of IκB was large, IκB stored at a distant location from the nucleus diffused back to the nucleus and “reset” NF-κB_n. Herein, we report mechanisms that regulate the persistency and frequency of NF-κB_n oscillation by nuclear transport. Among the four parameters of nuclear transport tested in our spatio-temporal computational model, the export of IκB mRNA from the nucleus regulated the persistency of oscillation. The import of IκB to the nucleus regulated the frequency of oscillation. The remaining two parameters, import and export of NF-κB to and from the nucleus, had virtually no effect on the persistency or frequency. Our analyses revealed that lesser export of IκB mRNA allowed NF-κB_n to transcript greater amounts of IκB mRNA, which was retained in the nucleus, and was subsequently exported to the cytoplasm, where large amounts of IκB were synthesized to “reset” NF-κB_n and drove the persistent oscillation. On the other hand, import of greater amounts of IκB led to an increase in the influx and the efflux of NF-κB to and from the nucleus, resulting in an increase in the oscillation frequency. Our study revealed the importance of nuclear transport in regulating the oscillation pattern of NF-κB_n.

A strategy to passively reduce neuroinflammation surrounding devices implanted chronically in brain tissue by manipulating device surface permeability

Available evidence indicates that pro-inflammatory cytokines produced by immune cells are likely responsible for the negative sequela associated with the foreign body response (FBR) to chronic indwelling implants in brain tissue. In this study a computational modeling approach was used to design a diffusion sink placed at the device surface that would retain pro-inflammatory cytokines for sufficient time to passively antagonize their impact on the FBR. Using quantitative immunohistochemistry, we examined the FBR to such engineered devices after a 16-week implantation period in the cortex of adult male Sprague-Dawley rats. Our results indicate that thick permeable surface coatings, which served as diffusion sinks, significantly reduced the FBR compared to implants either with no coating or with a thinner coating. The results suggest that increasing surface permeability of solid implanted devices to create a diffusion sink can be used to reduce the FBR and improve biocompatibility of chronic indwelling devices in brain tissue.

The primary cilium influences interleukin-1β-induced NFκB signalling by regulating IKK activity

The primary cilium is an organelle acting as a master regulator of cellular signalling. We have previously shown that disruption of primary cilia assembly, through targeting intraflagellar transport, is associated with muted nitric oxide and prostaglandin responses to the inflammatory cytokine interleukin-1β (IL-1β). Here, we show that loss of the primary cilium disrupts specific molecular signalling events in cytosolic NFκB signalling. The induction of cyclooxygenase 2 (COX2) and inducible nitrous oxide synthase (iNOS) protein is abolished. Cells unable to assemble cilia exhibit unaffected activation of IκB kinase (IKK), but delayed and reduced degradation of IκB, due to diminished phosphorylation of inhibitor of kappa B (IκB) by IKK. This results in both delayed and reduced NFκB p65 nuclear translocation and nuclear transcript binding. We also demonstrate that heat shock protein 27 (hsp27), an established regulator of IKK, is localized to the ciliary axoneme and cellular levels are dramatically disrupted with loss of the primary cilium. These results suggest that the primary cilia compartment exerts influence over NFκB signalling. We propose that the cilium is a locality for regulation of the molecular events defining NFκB signalling events, tuning signalling as appropriate.

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Hypermorphic mutation of IFT88 results in partial loss of the primary cilium.

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Cilia loss leads to inhibition of COX2 and iNOS induction in response to IL-1.

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In cells without cilia, IKK is activated but does not phosphorylate IκB.

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This leads to sustained IκB expression, and reduced and mistimed NFκB signalling.

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We propose the cilium to be a location for hsp27 regulation of IKK activity.

Identification of new IκBα complexes by an iterative experimental and mathematical modeling approach

The transcription factor nuclear factor kappa-B (NFκB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFκB activity may contribute to the development of severe diseases when the regulatory system is impaired. Since NFκB can be triggered by a huge variety of inflammatory, pro-and anti-apoptotic stimuli, its activation underlies a complex and tightly regulated signaling network that also includes multi-layered negative feedback mechanisms. Detailed understanding of this complex signaling network is mandatory to identify sensitive parameters that may serve as targets for therapeutic interventions. While many details about canonical and non-canonical NFκB activation have been investigated, less is known about cellular IκBα pools that may tune the cellular NFκB levels. IκBα has so far exclusively been described to exist in two different forms within the cell: stably bound to NFκB or, very transiently, as unbound protein. We created a detailed mathematical model to quantitatively capture and analyze the time-resolved network behavior. By iterative refinement with numerous biological experiments, we yielded a highly identifiable model with superior predictive power which led to the hypothesis of an NFκB-lacking IκBα complex that contains stabilizing IKK subunits. We provide evidence that other but canonical pathways exist that may affect the cellular IκBα status. This additional IκBα:IKKγ complex revealed may serve as storage for the inhibitor to antagonize undesired NFκB activation under physiological and pathophysiological conditions.

In unstimulated cells, the transcription factor NFκB resides in the cytosol bound to its inhibitor IκBα. Canonical activation of NFκB by numerous stimuli leads to proteasomal depletion of IκBα, thereby liberating NFκB to translocate into the nucleus to induce transcription of genes leading to proliferation, angiogenesis, metastasis, or chronic inflammation. Consequently, only transient activity needs to be warranted by immediate NFκB-dependent induction of negative regulatory mechanisms, including up-regulation of its inhibitor IκBα. Resynthesized IκBα consequently terminates NFκB activity by binding to its nuclear localization sequence. However, under physiological or pathophysiological conditions, random NFκB activation may occur, which needs to be avoided in order to guarantee proper cellular function. Using detailed dynamical modeling, we have now identified an additional IκBα containing complex to exist in un-stimulated cells which lacks NFκB but includes IKKγ (IκBα:IKKγ complex). This additional IκBα is not depleted from cells in the canonical fashion and may therefore serve as a cellular backup to avoid random NFκB activation.

The role of spatial organization of cells in erythropoiesis

Erythropoiesis, the process of red blood cell production, occurs mainly in the bone marrow. The functional unit of mammalian erythropoiesis, the erythroblastic island, consists of a central macrophage surrounded by adherent erythroid progenitor cells (CFU-E/Pro-EBs) and their differentiating progeny, the erythroblasts. Central macrophages display on their surface or secrete various growth or inhibitory factors that influence the fate of the surrounding erythroid cells. CFU-E/Pro-EBs have three possible fates: (a) expansion of their numbers without differentiation, (b) differentiation into reticulocytes that are released into the blood, (c) death by apoptosis. CFU-E/Pro-EB fate is under the control of a complex molecular network, that is highly dependent upon environmental conditions in the erythroblastic island. In order to assess the functional role of space coupled with the complex network behavior in erythroblastic islands, we developed hybrid discrete-continuous models of erythropoiesis. A model was developed in which cells are considered as individual physical objects, intracellular regulatory networks are modeled with ordinary differential equations and extracellular concentrations by partial differential equations. We used the model to investigate the impact of an important difference between humans and mice in which mature late-stage erythroblasts produce the most Fas-ligand in humans, whereas early-stage erythroblasts produce the most Fas-ligand in mice. Although the global behaviors of the erythroblastic islands in both species were similar, differences were found, including a relatively slower response time to acute anemia in humans. Also, our modeling approach was very consistent with in vitro culture data, where the central macrophage in reconstituted erythroblastic islands has a strong impact on the dynamics of red blood cell production. The specific spatial organization of erythroblastic islands is key to the normal, stable functioning of mammalian erythropoiesis, both in vitro and in vivo. Our model of a simplified molecular network controlling cell decision provides a realistic functional unit of mammalian erythropoiesis that integrates multiple microenvironmental influences within the erythroblastic island with those of circulating regulators of erythropoiesis, such as EPO and glucocorticosteroids, that are produced at remote sites.

Tunable signal processing through a kinase control cycle: the IKK signaling node

The transcription factor NFκB, a key component of the immune system, shows intricate stimulus-specific temporal dynamics. Those dynamics are thought to play a role in controlling the physiological response to cytokines and pathogens. Biochemical evidence suggests that the NFκB inducing kinase, IKK, a signaling hub onto which many signaling pathways converge, is regulated via a regulatory cycle comprising a poised, an active, and an inactive state. We hypothesize that it operates as a modulator of signal dynamics, actively reshaping the signals generated at the receptor proximal level. Here we show that a regulatory cycle can function in at least three dynamical regimes, tunable by regulating a single kinetic parameter. In particular, the simplest three-state regulatory cycle can generate signals with two well-defined phases, each with distinct coding capabilities in terms of the information they can carry about the stimulus. We also demonstrate that such a kinase cycle can function as a signal categorizer classifying diverse incoming signals into outputs with a limited set of temporal activity profiles. Finally, we discuss the extension of the results to other regulatory motifs that could be understood in terms of the regimes of the three-state cycle.

Probing cellular heterogeneity in cytokine-secreting immune cells using droplet-based microfluidics

Here, we present a platform to detect cytokine (IL-2, IFN-γ, TNF-α) secretion of single, activated T-cells in droplets over time. We use a novel droplet-based microfluidic approach to encapsulate cells in monodisperse agarose droplets together with functionalized cytokine-capture beads for subsequent binding and detection of secreted cytokines from single cells. This method allows high-throughput detection of cellular heterogeneity and maps subsets within cell populations with specific functions.

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.

Polymer-conjugated inhibitors of tumor necrosis factor-α for local control of inflammation

Burns, chronic wounds, osteoarthritis, and uveitis are examples of conditions characterized by local, intense inflammatory responses that can impede healing or even further tissue degradation. The most powerful anti-inflammatory drugs available are often administered systemically, but these carry significant side effects and are not compatible for patients that have underlying complications associated with their condition. Conjugation of monoclonal antibodies that neutralize pro-inflammatory cytokines to high molecular weight hydrophilic polymers has been shown to be an effective strategy for local control of inflammation. Lead formulations are based on antibody inhibitors of tumor necrosis factor-α conjugated to hyaluronic acid having molecular weight greater than 1 MDa. This review will discuss fundamental aspects of medical conditions that could be treated with these conjugates and design principles for preparing these cytokine-neutralizing polymer conjugates. Results demonstrating that infliximab, an approved inhibitor of tumor necrosis factor-α, can be incorporated into the conjugates using a broad range of water-soluble polymers are also presented, along with a prospectus for clinical translation.

Effects of hyaluronic acid conjugation on anti-TNF-α inhibition of inflammation in burns

Biomaterials capable of neutralizing specific cytokines could form the basis for treating a broad range of conditions characterized by intense, local inflammation. Severe burns, spanning partial- to full-thickness of the dermis, can result in complications due to acute inflammation that contributes to burn progression, and early mediation may be a key factor in rescuing thermally injured tissue from secondary necrosis to improve healing outcomes. In this work, we examined the effects on burn progression and influence on the inflammatory microenvironment of topical application of anti-tumor necrosis factor-α (anti-TNF-α) alone, mixed with hyaluronic acid (HA) or conjugated to HA. We found that non-conjugated anti-TNF-α decreased macrophage infiltration to a greater extent than that conjugated to HA; however, there was little effect on the degree of progression or IL-1β levels. A simple transport model is proposed to analyze the results, which predicts qualitative and quantitative differences between untreated burn sites and those treated with the conjugates. Our results indicate that conjugation of anti-TNF-α to high molecular weight HA provides sustained, local modulation of the post-injury inflammatory responses compared to direct administration of non-conjugated antibodies.

Encoding and decoding cellular information through signaling dynamics

A growing number of studies are revealing that cells can send and receive information by controlling the temporal behavior (dynamics) of their signaling molecules. In this Review, we discuss what is known about the dynamics of various signaling networks and their role in controlling cellular responses. We identify general principles that are emerging in the field, focusing specifically on how the identity and quantity of a stimulus is encoded in temporal patterns, how signaling dynamics influence cellular outcomes, and how specific dynamical patterns are both shaped and interpreted by the structure of molecular networks. We conclude by discussing potential functional roles for transmitting cellular information through the dynamics of signaling molecules and possible applications for the treatment of disease.

Flow-switching allows independently programmable, extremely stable, high-throughput diffusion-based gradients

An automated microfluidic cell culture platform that creates and maintains independently programmable diffusion-based gradients is reported. Temporal modulation of the source and sink flow patterns allow generation of extremely stable spatial gradients. We developed a system that integrates 30 parallel gradients in a single device, with 10 different chemical formulations and 3 replicates. Mammalian fibroblast and macrophage cells were screened for NFκB pathway activity under gradients of TNFα, PDGF, and LPS, and multiparameter measurements were performed to demonstrate the capability of the device in dynamic single-cell analysis.

Single-cell and population NF-κB dynamic responses depend on lipopolysaccharide preparation

Background

Lipopolysaccharide (LPS), found in the outer membrane of gram-negative bacteria, elicits a strong response from the transcription factor family Nuclear factor (NF)-κB via Toll-like receptor (TLR) 4. The cellular response to lipopolysaccharide varies depending on the source and preparation of the ligand, however. Our goal was to compare single-cell NF-κB dynamics across multiple sources and concentrations of LPS.

Methodology/Principal Findings

Using live-cell fluorescence microscopy, we determined the NF-κB activation dynamics of hundreds of single cells expressing a p65-dsRed fusion protein. We used computational image analysis to measure the nuclear localization of the fusion protein in the cells over time. The concentration range spanned up to nine orders of magnitude for three E. coli LPS preparations. We find that the LPS preparations induce markedly different responses, even accounting for potency differences. We also find that the ability of soluble TNF receptor to affect NF-κB dynamics varies strikingly across the three preparations.

Conclusions/Significance

Our work strongly suggests that the cellular response to LPS is highly sensitive to the source and preparation of the ligand. We therefore caution that conclusions drawn from experiments using one preparation may not be applicable to LPS in general.

A Systems Biology Study on NFκB Signaling in Primary Mouse Hepatocytes

The cytokine tumor necrosis factor-alpha (TNFα) is one of the key factors during the priming phase of liver regeneration as well as in hepatocarcinogenesis. TNFα activates the nuclear factor κ-light-chain-enhancer of activated B cells (NFκB) signaling pathway and contributes to the conversion of quiescent hepatocytes to activated hepatocytes that are able to proliferate in response to growth factor stimulation. Different mathematical models have been previously established for TNFα/NFκB signaling in the context of tumor cells. Combining these mathematical models with time-resolved measurements of expression and phosphorylation of TNFα/NFκB pathway constituents in primary mouse hepatocytes revealed that an additional phosphorylation step of the NFκB isoform p65 has to be considered in the mathematical model in order to sufficiently describe the dynamics of pathway activation in the primary cells. Also, we addressed the role of basal protein turnover by experimentally measuring the degradation rate of pivotal players in the absence of TNFα and including this information in the model. To elucidate the impact of variations in the protein degradation rates on TNFα/NFκB signaling on the overall dynamic behavior we used global sensitivity analysis that accounts for parameter uncertainties and showed that degradation and translation of p65 had a major impact on the amplitude and the integral of p65 phosphorylation. Finally, our mathematical model of TNFα/NFκB signaling was able to predict the time-course of the complex formation of p65 and of the inhibitor of NFκB (IκB) in primary mouse hepatocytes, which was experimentally verified. Hence, we here present a mathematical model for TNFα/NFκB signaling in primary mouse hepatocytes that provides an important basis to quantitatively disentangle the complex interplay of multiple factors in liver regeneration and tumorigenesis.

Measurement and modeling of signaling at the single-cell level

It has long been recognized that a deeper understanding of cell function, with respect to execution of phenotypic behaviors and their regulation by the extracellular environment, is likely to be achieved by analyzing the underlying molecular processes for individual cells selected from across a population, rather than averages of many cells comprising that population. In recent years, experimental and computational methods for undertaking these analyses have advanced rapidly. In this review, we provide a perspective on both measurement and modeling facets of biochemistry at a single-cell level. Our central focus is on receptor-mediated signaling networks that regulate cell phenotypic functions.

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.

Regulation of NF-κB by ubiquitination and degradation of the IκBs

The nuclear factor-κB (NF-κB) signaling pathway is a busy ground for the action of the ubiquitin-proteasome system; many of the signaling steps are coordinated by protein ubiquitination. The end point of this pathway is to induce transcription, and to this end, there is a need to overcome a major obstacle, a set of inhibitors (IκBs) that bind NF-κB and prohibit either the nuclear entry or the DNA binding of the transcription factor. Two major signaling steps are required for the elimination of the inhibitors: activation of the IκB kinase (IKK) and degradation of the phosphorylated inhibitors. IKK activation and IκB degradation involve different ubiquitination modes; the latter is mediated by a specific E3 ubiquitin ligase SCF(β-TrCP) . The F-box component of this E3, β-TrCP, recognizes the IκB degron formed following phosphorylation by IKK and thus couples IκB phosphorylation to ubiquitination. SCF(β-TrCP) -mediated IκB ubiquitination and degradation is a very efficient process, often resulting in complete degradation of the key inhibitor IκBα within a few minutes of cell stimulation. In vivo ablation of β-TrCP results in accumulation of all the IκBs and complete NF-κB inhibition. As many details of IκB-β-TrCP interaction have been worked out, the development of β-TrCP inhibitors might be a feasible therapeutic approach for NF-κB-associated human disease. However, we may still need to advance our understanding of the mechanism of IκB degradation as well as of the diverse functions of β-TrCP in vivo.

Interrogation of inhibitor of nuclear factor κB α/nuclear factor κB (IκBα/NF-κB) negative feedback loop dynamics: from single cells to live animals in vivo

Full understanding of the biological significance of negative feedback processes requires interrogation at multiple scales as follows: in single cells, cell populations, and live animals in vivo. The transcriptionally coupled IκBα/NF-κB negative feedback loop, a pivotal regulatory node of innate immunity and inflammation, represents a model system for multiscalar reporters. Using a κB(5)→IκBα-FLuc bioluminescent reporter, we rigorously evaluated the dynamics of ΙκBα degradation and subsequent NF-κB transcriptional activity in response to diverse modes of TNFα stimulation. Modulating TNFα concentration or pulse duration yielded complex, reproducible, and differential ΙκBα dynamics in both cell populations and live single cells. Tremendous heterogeneity in the transcriptional amplitudes of individual responding cells was observed, which was greater than the heterogeneity in the transcriptional kinetics of responsive cells. Furthermore, administration of various TNFα doses in vivo generated ΙκBα dynamic profiles in the liver resembling those observed in single cells and populations of cells stimulated with TNFα pulses. This suggested that dose modulation of circulating TNFα was perceived by hepatocytes in vivo as pulses of increasing duration. Thus, a robust bioluminescent reporter strategy enabled rigorous quantitation of NF-κB/ΙκBα dynamics in both live single cells and cell populations and furthermore, revealed reproducible behaviors that informed interpretation of in vivo studies.

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.

NF-κB Signaling Dynamics Play a Key Role in Infection Control in Tuberculosis

The NF-κB signaling pathway is central to the body’s response to many pathogens. Mathematical models based on cell culture experiments have identified important molecular mechanisms controlling the dynamics of NF-κB signaling, but the dynamics of this pathway have never been studied in the context of an infection in a host. Here, we incorporate these dynamics into a virtual infection setting. We build a multi-scale model of the immune response to the pathogen Mycobacterium tuberculosis (Mtb) to explore the impact of NF-κB dynamics occurring across molecular, cellular, and tissue scales in the lung. NF-κB signaling is triggered via tumor necrosis factor-α (TNF) binding to receptors on macrophages; TNF has been shown to play a key role in infection dynamics in humans and multiple animal systems. Using our multi-scale model, we predict the impact of TNF-induced NF-κB-mediated responses on the outcome of infection at the level of a granuloma, an aggregate of immune cells and bacteria that forms in response to infection and is key to containment of infection and clinical latency. We show how the stability of mRNA transcripts corresponding to NF-κB-mediated responses significantly controls bacterial load in a granuloma, inflammation level in tissue, and granuloma size. Because we incorporate intracellular signaling pathways explicitly, our analysis also elucidates NF-κB-associated signaling molecules and processes that may be new targets for infection control.

NEMO ensures signaling specificity of the pleiotropic IKKβ by directing its kinase activity toward IκBα

Besides activating NFκB by phosphorylating IκBs, IKKα/IKKβ kinases are also involved in regulating metabolic insulin signaling, the mTOR pathway, Wnt signaling, and autophagy. How IKKβ enzymatic activity is targeted to stimulus-specific substrates has remained unclear. We show here that NEMO, known to be essential for IKKβ activation by inflammatory stimuli, is also a specificity factor that directs IKKβ activity toward IκBα. Physical interaction and functional competition studies with mutant NEMO and IκB proteins indicate that NEMO functions as a scaffold to recruit IκBα to IKKβ. Interestingly, expression of NEMO mutants that allow for IKKβ activation by the cytokine IL-1, but fail to recruit IκBs, results in hyperphosphorylation of alternative IKKβ substrates. Furthermore IKK's function in autophagy, which is independent of NFκB, is significantly enhanced without NEMO as IκB scaffold. Our work establishes a role for scaffolds such as NEMO in determining stimulus-specific signal transduction via the pleiotropic signaling hub IKK.

Differential risk of tuberculosis reactivation among anti-TNF therapies is due to drug binding kinetics and permeability

Increased rates of tuberculosis (TB) reactivation have been reported in humans treated with TNF-α (TNF)-neutralizing drugs, and higher rates are observed with anti-TNF Abs (e.g., infliximab) as compared with TNF receptor fusion protein (etanercept). Mechanisms driving differential reactivation rates and differences in drug action are not known. We use a computational model of a TB granuloma formation that includes TNF/TNF receptor dynamics to elucidate these mechanisms. Our analyses yield three important insights. First, drug binding to membrane-bound TNF critically impairs granuloma function. Second, a higher risk of reactivation induced from Ab-type treatments is primarily due to differences in TNF/drug binding kinetics and permeability. Apoptotic and cytolytic activities of Abs and pharmacokinetic fluctuations in blood concentration of drug are not essential to inducing TB reactivation. Third, we predict specific host factors that, if augmented, would improve granuloma function during anti-TNF therapy. Our findings have implications for the development of safer anti-TNF drugs to treat inflammatory diseases.

Observing single cell NF-κB dynamics under stimulant concentration gradient

Study of cell signaling often requires examination of the cellular dynamics under variation in the stimulant concentration. Such variation has typically been conducted by dispensing cell populations in a number of chambers or wells containing discrete concentrations. Such practice adds to the complexity associated with experimental or device design and requires substantial labor for implementation. Furthermore, there is also potential risk of missing important results due to the often arbitrary selection of discrete concentration values for testing. In this Letter, we study NF-κB activation and translocation at the single cell level using a microfluidic device that generates continuously varying concentration gradient. We use only three device settings to cover stimulant (interleukin-1β) concentrations of 4 orders of magnitude (0.001-10 ng/mL). Such device allows us to study temporal dynamics of NF-κB in single cells under different stimulant concentrations by real-time imaging. Interestingly, our results reveal that, while the percent of cells with NF-κB translocation decreases with lower stimulant concentration in the range of 0.1-0.001 ng/mL, the response time of such translocation remains constant, reflected by the single cell data.

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.