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

Distinct cellular states determine calcium signaling response

The heterogeneity in mammalian cells signaling response is largely a result of pre‐existing cell‐to‐cell variability. It is unknown whether cell‐to‐cell variability rises from biochemical stochastic fluctuations or distinct cellular states. Here, we utilize calcium response to adenosine trisphosphate as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states coexist. We use a functional definition of cellular state that is based on a mechanistic dynamical systems model of calcium signaling. Using Bayesian parameter inference, we obtain high confidence parameter value distributions for several hundred cells, each fitted individually. Clustering the inferred parameter distributions revealed three major distinct cellular states within the population. The existence of distinct cellular states raises the possibility that the observed variability in response is a result of structured heterogeneity between cells. The inferred parameter distribution predicts, and experiments confirm that variability in IP3R response explains the majority of calcium heterogeneity. Our work shows how mechanistic models and single‐cell parameter fitting can uncover hidden population structure and demonstrate the need for parameter inference at the single‐cell level.

Late-phase synthesis of IκBα insulates the TLR4-activated canonical NF-κB pathway from noncanonical NF-κB signaling in macrophages

The nuclear factor κB (NF-κB) transcription factors coordinate the inflammatory immune response during microbial infection. Pathogenic substances engage canonical NF-κB signaling through the heterodimer RelA:p50, which is subjected to rapid negative feedback by inhibitor of κBα (IκBα). The noncanonical NF-κB pathway is required for the differentiation of immune cells; however, cross-talk between both pathways can occur. Concomitantly activated noncanonical signaling generates p52 from the p100 precursor. The synthesis of p100 is induced by canonical signaling, leading to the formation of the late-acting RelA:p52 heterodimer. This cross-talk prolongs inflammatory RelA activity in epithelial cells to ensure pathogen clearance. We found that the Toll-like receptor 4 (TLR4)-activated canonical NF-κB signaling pathway is insulated from lymphotoxin β receptor (LTβR)-induced noncanonical signaling in mouse macrophage cell lines. Combined computational and biochemical studies indicated that the extent of NF-κB-responsive expression of Nfkbia, which encodes IκBα, inversely correlated with cross-talk. The Nfkbia promoter showed enhanced responsiveness to NF-κB activation in macrophages compared to that in fibroblasts. We found that this hyperresponsive promoter engaged the RelA:p52 dimer generated during costimulation of macrophages through TLR4 and LTβR to trigger synthesis of IκBα at late time points, which prevented the late-acting RelA cross-talk response. Together, these data suggest that, despite the presence of identical signaling networks in cells of diverse lineages, emergent cross-talk between signaling pathways is subject to cell type-specific regulation. We propose that the insulation of canonical and noncanonical NF-κB pathways limits the deleterious effects of macrophage-mediated inflammation.

Importins promote high-frequency NF-κB oscillations increasing information channel capacity

Background

Importins and exportins influence gene expression by enabling nucleocytoplasmic shuttling of transcription factors. A key transcription factor of innate immunity, NF-κB, is sequestered in the cytoplasm by its inhibitor, IκBα, which masks nuclear localization sequence of NF-κB. In response to TNFα or LPS, IκBα is degraded, which allows importins to bind NF-κB and shepherd it across nuclear pores. NF-κB nuclear activity is terminated when newly synthesized IκBα enters the nucleus, binds NF-κB and exportin which directs the complex to the cytoplasm. Although importins/exportins are known to regulate spatiotemporal kinetics of NF-κB and other transcription factors governing innate immunity, the mechanistic details of these interactions have not been elucidated and mathematically modelled.

Results

Based on our quantitative experimental data, we pursue NF-κB system modelling by explicitly including NF-κB–importin and IκBα–exportin binding to show that the competition between importins and IκBα enables NF-κB nuclear translocation despite high levels of IκBα. These interactions reduce the effective relaxation time and allow the NF-κB regulatory pathway to respond to recurrent TNFα pulses of 45-min period, which is about twice shorter than the characteristic period of NF-κB oscillations. By stochastic simulations of model dynamics we demonstrate that randomly appearing, short TNFα pulses can be converted to essentially digital pulses of NF-κB activity, provided that intervals between input pulses are not shorter than 1 h.

Conclusions

By including interactions involving importin-α and exportin we bring the modelling of spatiotemporal kinetics of transcription factors to a more mechanistic level. Basing on the analysis of the pursued model we estimated the information transmission rate of the NF-κB pathway as 1 bit per hour.

Reviewers

This article was reviewed by Marek Kimmel, James Faeder and William Hlavacek.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-016-0164-z) contains supplementary material.

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments

Live-cell imaging has opened an exciting window into the role cellular heterogeneity plays in dynamic, living systems. A major critical challenge for this class of experiments is the problem of image segmentation, or determining which parts of a microscope image correspond to which individual cells. Current approaches require many hours of manual curation and depend on approaches that are difficult to share between labs. They are also unable to robustly segment the cytoplasms of mammalian cells. Here, we show that deep convolutional neural networks, a supervised machine learning method, can solve this challenge for multiple cell types across the domains of life. We demonstrate that this approach can robustly segment fluorescent images of cell nuclei as well as phase images of the cytoplasms of individual bacterial and mammalian cells from phase contrast images without the need for a fluorescent cytoplasmic marker. These networks also enable the simultaneous segmentation and identification of different mammalian cell types grown in co-culture. A quantitative comparison with prior methods demonstrates that convolutional neural networks have improved accuracy and lead to a significant reduction in curation time. We relay our experience in designing and optimizing deep convolutional neural networks for this task and outline several design rules that we found led to robust performance. We conclude that deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.

Unraveling cellular pathways contributing to drug-induced liver injury by dynamical modeling

INTRODUCTION

Drug-induced liver injury (DILI) is a significant threat to human health and a major problem in drug development. It is hard to predict due to its idiosyncratic nature and which does not show up in animal trials. Hepatic adaptive stress response pathway activation is generally observed in drug-induced liver injury. Dynamical pathway modeling has the potential to foresee adverse effects of drugs before they go in trial. Ordinary differential equation modeling can offer mechanistic insight, and allows us to study the dynamical behavior of stress pathways involved in DILI. Areas covered: This review provides an overview on the progress of the dynamical modeling of stress and death pathways pertinent to DILI, i.e. pathways relevant for oxidative stress, inflammatory stress, DNA damage, unfolded proteins, heat shock and apoptosis. We also discuss the required steps for applying such modeling to the liver. Expert opinion: Despite the strong progress made since the turn of the century, models of stress pathways have only rarely been specifically applied to describe pathway dynamics for DILI. We argue that with minor changes, in some cases only to parameter values, many of these models can be repurposed for application in DILI research. Combining both dynamical models with in vitro testing might offer novel screening methods for the harmful side-effects of drugs.

Toll-like Receptor function of murine macrophages, probed by cytokine induction, is biphasic and is not impaired globally with age

Aging is associated with a waning of normal immune function. This "immunosenescence" is characterized by a diverse repertoire of seemingly discreet and unbalanced immune alterations. A number of studies have suggested that aging-associated alterations in innate immune responsiveness, especially responsiveness dependent on Toll-like Receptor (TLR) engagement, are causally involved. We find, however, that the magnitude and dose-dependency of responsiveness to TLR engagement (assessed with respect to cytokine production) in distinct populations of murine macrophages are not altered generally with animal age or as a consequence of immunosenescence. Responses elicited with a wide array of TLR agonists were examined by extensive functional analyses, principally on the level of the individual cell. These studies reveal an intriguing "all-or-nothing" response behavior of macrophages, independent of animal age. Although reports to the contrary have been cited widely, aging-associated immune decline cannot be attributed to widespread alterations in the extents of TLR-dependent innate immune macrophage responses.

Distinct NF-κB and MAPK Activation Thresholds Uncouple Steady-State Microbe Sensing from Anti-pathogen Inflammatory Responses

The innate immune system distinguishes low-level homeostatic microbial stimuli from those of invasive pathogens, yet we lack understanding of how qualitatively similar microbial products yield context-specific macrophage functional responses. Using quantitative approaches, we found that NF-κB and MAPK signaling was activated at different concentrations of a stimulatory TLR4 ligand in both mouse and human macrophages. Above a threshold of ligand, MAPK were activated in a switch-like manner, facilitating production of inflammatory mediators. At ligand concentrations below this threshold, NF-κB signaling occurred, promoting expression of a restricted set of genes and macrophage priming. Among TLR-induced genes, we observed an inverse correlation between MAPK dependence and ligand sensitivity, highlighting the role of this signaling dichotomy in partitioning innate responses downstream of a single receptor. Our study reveals an evolutionarily conserved innate immune response system in which danger discrimination is enforced by distinct thresholds for NF-κB and MAPK activation, which provide sequential barriers to inflammatory mediator production.

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

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

Redefining Signaling Pathways with an Expanding Single-Cell Toolbox

Genetically identical cells respond heterogeneously to uniform environmental stimuli. Consequently, investigating the signaling networks that control these cell responses using 'average' bulk cell measurements can obscure underlying mechanisms and misses information emerging from cell-to-cell variability. Here we review recent technological advances including live-cell fluorescence imaging-based approaches and microfluidic devices that enable measurements of signaling networks, dynamics, and responses in single cells. We discuss how these single-cell tools have uncovered novel mechanistic insights for canonical signaling pathways that control cell proliferation (ERK), DNA-damage responses (p53), and innate immune and stress responses (NF-κB). Future improvements in throughput and multiplexing, analytical pipelines, and in vivo applicability will all significantly expand the biological information gained from single-cell measurements of signaling pathways.

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.

NF-κB oscillations translate into functionally related patterns of gene expression

Several transcription factors (TFs) oscillate, periodically relocating between the cytoplasm and the nucleus. NF-κB, which plays key roles in inflammation and cancer, displays oscillations whose biological advantage remains unclear. Recent work indicated that NF-κB displays sustained oscillations that can be entrained, that is, reach a persistent synchronized state through small periodic perturbations. We show here that for our GFP-p65 knock-in cells NF-κB behaves as a damped oscillator able to synchronize to a variety of periodic external perturbations with no memory. We imposed synchronous dynamics to prove that transcription of NF-κB-controlled genes also oscillates, but mature transcript levels follow three distinct patterns. Two sets of transcripts accumulate fast or slowly, respectively. Another set, comprising chemokine and chemokine receptor mRNAs, oscillates and resets at each new stimulus, with no memory of the past. We propose that TF oscillatory dynamics is a means of segmenting time to provide renewing opportunity windows for decision.

Digital signaling decouples activation probability and population heterogeneity

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

Distinct single-cell signaling characteristics are conferred by the MyD88 and TRIF pathways during TLR4 activation

Toll-like receptors (TLRs) recognize specific pathogen-associated molecular patterns and initiate innate immune responses through signaling pathways that depend on the adaptor proteins MyD88 (myeloid differentiation marker 88) or TRIF (TIR domain-containing adaptor protein-inducing interferon-β). TLR4, in particular, uses both adaptor proteins to activate the transcription factor nuclear factor κB (NF-κB); however, the specificity and redundancy of these two pathways remain to be elucidated. We developed a mathematical model to show how each pathway encodes distinct dynamical features of NF-κB activity and makes distinct contributions to the high variability observed in single-cell measurements. The assembly of a macromolecular signaling platform around MyD88 associated with receptors at the cell surface determined the timing of initial responses to generate a reliable, digital NF-κB signal. In contrast, ligand-induced receptor internalization into endosomes produced noisy, delayed, yet sustained NF-κB signals through TRIF. With iterative mathematical model development, we predicted the molecular mechanisms by which the MyD88- and TRIF-mediated pathways provide ligand concentration-dependent signaling dynamics that transmit information about the pathogen threat.

Visualization of RelB expression and activation at the single-cell level during dendritic cell maturation in Relb-Venus knock-in mice

RelB is activated by the non-canonical NF-κB pathway, which is crucial for immunity by establishing lymphoid organogenesis and B-cell and dendritic cell (DC) maturation. To elucidate the mechanism of the RelB-mediated immune cell maturation, a precise understanding of the relationship between cell maturation and RelB expression and activation at the single-cell level is required. Therefore, we generated knock-in mice expressing a fusion protein between RelB and fluorescent protein (RelB-Venus) from the Relb locus. The Relb(Venus/Venus) mice developed without any abnormalities observed in the Relb(-/-) mice, allowing us to monitor RelB-Venus expression and nuclear localization as RelB expression and activation. Relb(Venus/Venus) DC analyses revealed that DCs consist of RelB(-), RelB(low) and RelB(high) populations. The RelB(high) population, which included mature DCs with projections, displayed RelB nuclear localization, whereas RelB in the RelB(low) population was in the cytoplasm. Although both the RelB(low) and RelB(-) populations barely showed projections, MHC II and co-stimulatory molecule expression were higher in the RelB(low) than in the RelB(-) splenic conventional DCs. Taken together, our results identify the RelB(low) population as a possible novel intermediate maturation stage of cDCs and the Relb(Venus/Venus) mice as a useful tool to analyse the dynamic regulation of the non-canonical NF-κB pathway.

Analysis of single-cell cytokine secretion reveals a role for paracrine signaling in coordinating macrophage responses to TLR4 stimulation

Macrophages not only produce multiple cytokines but also respond to multiple cytokines, which likely shapes the ultimate response of the population. To determine the role of paracrine signaling in shaping the profile of inflammatory cytokines secreted by macrophages in response to stimulation of Toll-like receptor 4 (TLR4) with lipopolysaccharide (LPS), we combined multiplexed, microwell-based measurements of cytokine secretion by single cells with analysis of cytokine secretion by cell populations. Loss of paracrine signaling as a result of cell isolation reduced the secretion by macrophage-like U937 cells and human monocyte-derived macrophages (MDMs) of a subset of LPS-stimulated cytokines, including interleukin-6 (IL-6) and IL-10. Graphical Gaussian modeling (GGM) of the single-cell data defined a regulatory network of paracrine signals, which was validated experimentally in the population through antibody-mediated neutralization of individual cytokines. Tumor necrosis factor-α (TNF-α) was the most influential cytokine in the GGM network. Paracrine signaling by TNF-α secreted from a small subpopulation of "high-secreting" cells was necessary, but not sufficient, for the secretion of large amounts of IL-6 and IL-10 by the cell population. Decreased relative IL-10 secretion by isolated MDMs was linked to increased TNF-α secretion, suggesting that inhibition of the inflammatory response also depends on paracrine signaling. Our results reveal a previously uncharacterized role for cell-to-cell communication within a population in coordinating a rapid innate immune response despite underlying cell-to-cell heterogeneity.

Noise facilitates transcriptional control under dynamic inputs

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments.

Stimulus-selective crosstalk via the NF-κB signaling system reinforces innate immune response to alleviate gut infection

Tissue microenvironment functions as an important determinant of the inflammatory response elicited by the resident cells. Yet, the underlying molecular mechanisms remain obscure. Our systems-level analyses identified a duration code that instructs stimulus specific crosstalk between TLR4-activated canonical NF-κB pathway and lymphotoxin-β receptor (LTβR) induced non-canonical NF-κB signaling. Indeed, LTβR costimulation synergistically enhanced the late RelA/NF-κB response to TLR4 prolonging NF-κB target gene-expressions. Concomitant LTβR signal targeted TLR4-induced newly synthesized p100, encoded by Nfkb2, for processing into p52 that not only neutralized p100 mediated inhibitions, but potently generated RelA:p52/NF-κB activity in a positive feedback loop. Finally, Nfkb2 connected lymphotoxin signal within the intestinal niche in reinforcing epithelial innate inflammatory RelA/NF-κB response to Citrobacter rodentium infection, while Nfkb2^−/− mice succumbed to gut infections owing to stromal defects. In sum, our results suggest that signal integration via the pleiotropic NF-κB system enables tissue microenvironment derived cues in calibrating physiological responses.

DOI:http://dx.doi.org/10.7554/eLife.05648.001

The innate immune system is the body's first line of defense against infection and disease. Innate immune cells are found in every tissue type, poised to respond immediately to damaged, stressed, or infected host cells. When innate immune cells recognize any injury or infection, one of the first things they do is trigger the inflammatory response. Fluid and other immune cells then move from the blood into the injured tissues. This movement can cause redness and swelling. But the response helps to establish a physical barrier against the spread of infection, promotes the elimination of both invading microbes and damaged host cells, and encourages the repair of the tissue.

Inflammation is tightly controlled. If the response is too weak, it could leave an individual prone to serious infection. On the other hand, excessive inflammation can severely damage healthy cells and tissues. Inflammation is regulated differently in different tissue types, and the environment within the tissue itself influences the activity of local innate immune cells and the inflammatory response. However, the molecular mechanisms responsible for receiving and interpreting the signals derived from the host tissue remain unknown.

Now, Banoth et al., have revealed that the integration of inflammation-provoking signals, such as injury or infection and cues from the tissue environment occurs via the so-called ‘NF-κB signaling system’. NF-κB is a protein found in almost all cell types, and when activated it is able to switch on the expression of many different genes. Banoth et al. explain that signal integration via the NF-κB system enables cues from the tissue environment to tune a cell's responses. Further experiments confirmed the importance of this signal integration by showing how a signal coming from intestinal tissue can influence the activity of innate immune cells and inflammation in the gut.

These findings suggest that a breakdown in the NF-κB signaling system's ability to integrate multiple signals, including those derived from the tissue environment, may be responsible for many inflammatory disorders, and in particular those that involve the gut. Future work is now needed to explore this possibility.

DOI:http://dx.doi.org/10.7554/eLife.05648.002

Controlling the origins of inflammation with a photoactive lipopeptide immunopotentiator

Inflammatory immune responses are mediated by signaling molecules that are both produced by and recognized across highly heterogeneous cell populations. As such, the study of inflammation using traditional immunostimulants is complicated by paracrine and autocrine signaling, which obscures the origin of a propagating response. To address this challenge, we developed a small-molecule probe that can photosensitize immune cells, thus allowing light-mediated inflammation. This probe was used to control the origin of inflammation using light. Following this motif, inflammation was initiated from fibroblasts or dendritic cells. The contributions of fibroblasts and dendritic cells in initiating inflammation in heterogeneous co-culture are reported, thus providing insights into the future development of vaccines and treatment of inflammation.

Sources of dynamic variability in NF-κB signal transduction: a mechanistic model

The transcription factor NF-κB (p65/p50) plays a central role in the coordination of cellular responses by activating the transcription of numerous target genes. The precise role of the dynamics of NF-κB signalling in regulating gene expression is still an open question. Here, we show that besides external stimulation intracellular parameters can influence the dynamics of NF-κB. By applying mathematical modelling and bifurcation analyses, we show that NF-κB is capable of exhibiting different types of dynamics in response to the same stimulus. We identified the total NF-κB concentration and the IκBα transcription rate constant as two critical parameters that modulate the dynamics and the fold change of NF-κB. Both parameters might vary as a result of cell-to-cell variability. The regulation of the IκBα transcription rate constant, e.g. by co-factors, provides the possibility of regulating the NF-κB dynamics by crosstalk.

Single-cell variation leads to population invariance in NF-κB signaling dynamics

Most features of NF-κB activation dynamics vary significantly with respect to ligand type and concentration. The distribution of the time between two nuclear entries is an invariant feature in populations but not individual cells, suggesting an additional level of control, which regulates the overall distribution of translocation timing.

The activation dynamics of nuclear factor (NF)-κB have been shown to affect downstream gene expression. On activation, NF-κB shuttles back and forth across the nuclear envelope. Many dynamic features of this shuttling have been characterized, and most features vary significantly with respect to ligand type and concentration. Here, we report an invariant feature with regard to NF-κB dynamics in cellular populations: the distribution—the average, as well as the variance—of the time between two nuclear entries (the period). We find that this period is conserved, regardless of concentration and across several different ligands. Intriguingly, the distributions observed at the population level are not observed in individual cells over 20-h time courses. Instead, the average period of NF-κB nuclear translocation varies considerably among single cells, and the variance is much smaller within a cell than that of the population. Finally, analysis of daughter-cell pairs and isogenic populations indicates that the dynamics of the NF-κB response is heritable but diverges over multiple divisions, on the time scale of weeks to months. These observations are contrary to the existing theory of NF-κB dynamics and suggest an additional level of control that regulates the overall distribution of translocation timing at the population level.

Network dynamics determine the autocrine and paracrine signaling functions of TNF

A hallmark of the inflammatory response to pathogen exposure is the production of tumor necrosis factor (TNF) that coordinates innate and adaptive immune responses by functioning in an autocrine or paracrine manner. Numerous molecular mechanisms contributing to TNF production have been identified, but how they function together in macrophages remains unclear. Here, we pursued an iterative systems biology approach to develop a quantitative understanding of the regulatory modules that control TNF mRNA synthesis and processing, mRNA half-life and translation, and protein processing and secretion. By linking the resulting model of TNF production to models of the TLR-, the TNFR-, and the NFκB signaling modules, we were able to study TNF's functions during the inflammatory response to diverse TLR agonists. Contrary to expectation, we predicted and then experimentally confirmed that in response to lipopolysaccaride, TNF does not have an autocrine function in amplifying the NFκB response, although it plays a potent paracrine role in neighboring cells. However, in response to CpG DNA, autocrine TNF extends the duration of NFκB activity and shapes CpG-induced gene expression programs. Our systems biology approach revealed that network dynamics of MyD88 and TRIF signaling and of cytokine production and response govern the stimulus-specific autocrine and paracrine functions of TNF.

Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters

Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic-intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.

Computational analysis of signaling patterns in single cells

Signaling proteins are flexible in both form and function. They can bind to multiple molecular partners and integrate diverse types of cellular information. When imaged by time-lapse microscopy, many signaling proteins show complex patterns of activity or localization that vary from cell to cell. This heterogeneity is so prevalent that it has spurred the development of new computational strategies to analyze single-cell signaling patterns. A collective observation from these analyses is that cells appear less heterogeneous when their responses are normalized to, or synchronized with, other single-cell measurements. In many cases, these transformed signaling patterns show distinct dynamical trends that correspond with predictable phenotypic outcomes. When signaling mechanisms are unclear, computational models can suggest putative molecular interactions that are experimentally testable. Thus, computational analysis of single-cell signaling has not only provided new ways to quantify the responses of individual cells, but has helped resolve longstanding questions surrounding many well-studied human signaling proteins including NF-κB, p53, ERK1/2, and CDK2. A number of specific challenges lie ahead for single-cell analysis such as quantifying the contribution of non-cell autonomous signaling as well as the characterization of protein signaling dynamics in vivo.

Single-cell RNA-seq reveals dynamic paracrine control of cellular variation

High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis and function of gene expression variation between seemingly identical cells. Here we sequence single-cell RNA-seq libraries prepared from over 1,700 primary mouse bone-marrow-derived dendritic cells spanning several experimental conditions. We find substantial variation between identically stimulated dendritic cells, in both the fraction of cells detectably expressing a given messenger RNA and the transcript's level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a 'core' module of antiviral genes is expressed very early by a few 'precocious' cells in response to uniform stimulation with a pathogenic component, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analysing dendritic cells from knockout mice, and modulating secretion and extracellular signalling, we show that this response is coordinated by interferon-mediated paracrine signalling from these precocious cells. Notably, preventing cell-to-cell communication also substantially reduces variability between cells in the expression of an early-induced 'peaked' inflammatory module, suggesting that paracrine signalling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations can use to establish complex dynamic responses.

The future of whole-cell modeling

Integrated whole-cell modeling is poised to make a dramatic impact on molecular and systems biology, bioengineering, and medicine--once certain obstacles are overcome. From our group's experience building a whole-cell model of Mycoplasma genitalium, we identified several significant challenges to building models of more complex cells. Here we review and discuss these challenges in seven areas: first, experimental interrogation; second, data curation; third, model building and integration; fourth, accelerated computation; fifth, analysis and visualization; sixth, model validation; and seventh, collaboration and community development. Surmounting these challenges will require the cooperation of an interdisciplinary group of researchers to create increasingly sophisticated whole-cell models and make data, models, and simulations more accessible to the wider community.

A simple model of NF-κB dynamics reproduces experimental observations

The mathematical modeling of the NF-κB oscillations has attracted considerable attention in recent times, but there is a lack of simple models in the literature that can capture the main features of the dynamics of this important transcription factor. For this reason we propose a simple model that summarizes the key steps of the NF-κB pathway. We show that the resulting 5-dimensional dynamical system can reproduce different phenomena observed in experiments. Our model can display smooth and spiky oscillations in the amount of nuclear NF-κB and can reproduce the variety of dynamics observed when different stimulations such as TNF-α and LPS are used. Furthermore we show that the model can be easily extended to reproduce the expression of early, intermediate and late genes upon stimulation. As a final example we show that our simple model can mimic the different transcriptional outputs observed when cells are treated with two different drugs leading to nuclear localization of NF-κB: Leptomycin B and Cycloheximide.

Switching of the relative dominance between feedback mechanisms in lipopolysaccharide-induced NF-κB signaling

A fundamental goal in biology is to gain a quantitative understanding of how appropriate cell responses are achieved amid conflicting signals that work in parallel. Through live, single-cell imaging, we monitored both the dynamics of nuclear factor κB (NF-κB) signaling and inflammatory cytokine transcription in macrophages exposed to the bacterial product lipopolysaccharide (LPS). Our analysis revealed a previously uncharacterized positive feedback loop involving induction of the expression of Rela, which encodes the RelA (p65) NF-κB subunit. This positive feedback loop rewired the regulatory network when cells were exposed to LPS above a distinct concentration. Paradoxically, this rewiring of NF-κB signaling in macrophages (a myeloid cell type) required the transcription factor Ikaros, which promotes the development of lymphoid cells. Mathematical modeling and experimental validation showed that the RelA positive feedback overcame existing negative feedback loops and enabled cells to discriminate between different concentrations of LPS to mount an effective innate immune response only at higher concentrations. We suggest that this switching in the relative dominance of feedback loops ("feedback dominance switching") may be a general mechanism in immune cells to integrate opposing feedback on a key transcriptional regulator and to set a response threshold for the host.

Spontaneous NF-κB activation by autocrine TNFα signaling: a computational analysis

NF-κB is a key transcription factor that regulates innate immune response. Its activity is tightly controlled by numerous feedback loops, including two negative loops mediated by NF-κB inducible inhibitors, IκBα and A20, which assure oscillatory responses, and by positive feedback loops arising due to the paracrine and autocrine regulation via TNFα, IL-1 and other cytokines. We study the NF-κB system of interlinked negative and positive feedback loops, combining bifurcation analysis of the deterministic approximation with stochastic numerical modeling. Positive feedback assures the existence of limit cycle oscillations in unstimulated wild-type cells and introduces bistability in A20-deficient cells. We demonstrated that cells of significant autocrine potential, i.e., cells characterized by high secretion of TNFα and its receptor TNFR1, may exhibit sustained cytoplasmic-nuclear NF-κB oscillations which start spontaneously due to stochastic fluctuations. In A20-deficient cells even a small TNFα expression rate qualitatively influences system kinetics, leading to long-lasting NF-κB activation in response to a short-pulsed TNFα stimulation. As a consequence, cells with impaired A20 expression or increased TNFα secretion rate are expected to have elevated NF-κB activity even in the absence of stimulation. This may lead to chronic inflammation and promote cancer due to the persistent activation of antiapoptotic genes induced by NF-κB. There is growing evidence that A20 mutations correlate with several types of lymphomas and elevated TNFα secretion is characteristic of many cancers. Interestingly, A20 loss or dysfunction also leaves the organism vulnerable to septic shock and massive apoptosis triggered by the uncontrolled TNFα secretion, which at high levels overcomes the antiapoptotic action of NF-κB. It is thus tempting to speculate that some cancers of deregulated NF-κB signaling may be prone to the pathogen-induced apoptosis.

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.

A checklist for successful quantitative live cell imaging in systems biology

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology.

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.

Single-cell measurements of IgE-mediated FcεRI signaling using an integrated microfluidic platform

Heterogeneity in responses of cells to a stimulus, such as a pathogen or allergen, can potentially play an important role in deciding the fate of the responding cell population and the overall systemic response. Measuring heterogeneous responses requires tools capable of interrogating individual cells. Cell signaling studies commonly do not have single-cell resolution because of the limitations of techniques used such as Westerns, ELISAs, mass spectrometry, and DNA microarrays. Microfluidics devices are increasingly being used to overcome these limitations. Here, we report on a microfluidic platform for cell signaling analysis that combines two orthogonal single-cell measurement technologies: on-chip flow cytometry and optical imaging. The device seamlessly integrates cell culture, stimulation, and preparation with downstream measurements permitting hands-free, automated analysis to minimize experimental variability. The platform was used to interrogate IgE receptor (FcεRI) signaling, which is responsible for triggering allergic reactions, in RBL-2H3 cells. Following on-chip crosslinking of IgE-FcεRI complexes by multivalent antigen, we monitored signaling events including protein phosphorylation, calcium mobilization and the release of inflammatory mediators. The results demonstrate the ability of our platform to produce quantitative measurements on a cell-by-cell basis from just a few hundred cells. Model-based analysis of the Syk phosphorylation data suggests that heterogeneity in Syk phosphorylation can be attributed to protein copy number variations, with the level of Syk phosphorylation being particularly sensitive to the copy number of Lyn.

Tunable signal processing through modular control of transcription factor translocation

Signaling pathways can induce different dynamics of transcription factor (TF) activation. We explored how TFs process signaling inputs to generate diverse dynamic responses. The budding yeast general stress-responsive TF Msn2 acted as a tunable signal processor that could track, filter, or integrate signals in an input-dependent manner. This tunable signal processing appears to originate from dual regulation of both nuclear import and export by phosphorylation, as mutants with one form of regulation sustained only one signal-processing function. Versatile signal processing by Msn2 is crucial for generating distinct dynamic responses to different natural stresses. Our findings reveal how complex signal-processing functions are integrated into a single molecule and provide a guide for the design of TFs with "programmable" signal-processing functions.

Noisy transcription factor NF-κB oscillations stabilize and sensitize cytokine signaling in space

NF-κB is a major transcription factor mediating inflammatory response. In response to a pro-inflammatory stimulus, it exhibits a characteristic response-a pulse followed by noisy oscillations in concentrations of considerably smaller amplitude. NF-κB is an important mediator of cellular communication, as it is both activated by and upregulates production of cytokines, signals used by white blood cells to find the source of inflammation. While the oscillatory dynamics of NF-κB has been extensively investigated both experimentally and theoretically, the role of the noise and the lower secondary amplitude has not been addressed. We use a cellular automaton model to address these issues in the context of spatially distributed communicating cells. We find that noisy secondary oscillations stabilize concentric wave patterns, thus improving signal quality. Furthermore, both lower secondary amplitude as well as noise in the oscillation period might be working against chronic inflammation, the state of self-sustained and stimulus-independent excitations. Our findings suggest that the characteristic irregular secondary oscillations of lower amplitude are not accidental. On the contrary, they might have evolved to increase robustness of the inflammatory response and the system's ability to return to a pre-stimulated state.

Integrating high-content imaging and chemical genetics to probe host cellular pathways critical for Yersinia pestis infection

The molecular machinery that regulates the entry and survival of Yersinia pestis in host macrophages is poorly understood. Here, we report the development of automated high-content imaging assays to quantitate the internalization of virulent Y. pestis CO92 by macrophages and the subsequent activation of host NF-κB. Implementation of these assays in a focused chemical screen identified kinase inhibitors that inhibited both of these processes. Rac-2-ethoxy-3 octadecanamido-1-propylphosphocholine (a protein Kinase C inhibitor), wortmannin (a PI3K inhibitor), and parthenolide (an IκB kinase inhibitor), inhibited pathogen-induced NF-κB activation and reduced bacterial entry and survival within macrophages. Parthenolide inhibited NF-κB activation in response to stimulation with Pam3CSK4 (a TLR2 agonist), E. coli LPS (a TLR4 agonist) or Y. pestis infection, while the PI3K and PKC inhibitors were selective only for Y. pestis infection. Together, our results suggest that phagocytosis is the major stimulus for NF-κB activation in response to Y. pestis infection, and that Y. pestis entry into macrophages may involve the participation of protein kinases such as PI3K and PKC. More importantly, the automated image-based screening platform described here can be applied to the study of other bacteria in general and, in combination with chemical genetic screening, can be used to identify host cell functions facilitating the identification of novel antibacterial therapeutics.

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.

Automated analysis of NF-κB nuclear translocation kinetics in high-throughput screening

Nuclear entry and exit of the NF-κB family of dimeric transcription factors plays an essential role in regulating cellular responses to inflammatory stress. The dynamics of this nuclear translocation can vary significantly within a cell population and may dramatically change e.g. upon drug exposure. Furthermore, there is significant heterogeneity in individual cell response upon stress signaling. In order to systematically determine factors that define NF-κB translocation dynamics, high-throughput screens that enable the analysis of dynamic NF-κB responses in individual cells in real time are essential. Thus far, only NF-κB downstream signaling responses of whole cell populations at the transcriptional level are in high-throughput mode. In this study, we developed a fully automated image analysis method to determine the time-course of NF-κB translocation in individual cells, suitable for high-throughput screenings in the context of compound screening and functional genomics. Two novel segmentation methods were used for defining the individual nuclear and cytoplasmic regions: watershed masked clustering (WMC) and best-fit ellipse of Voronoi cell (BEVC). The dynamic NFκB oscillatory response at the single cell and population level was coupled to automated extraction of 26 analogue translocation parameters including number of peaks, time to reach each peak, and amplitude of each peak. Our automated image analysis method was validated through a series of statistical tests demonstrating computational efficient and accurate NF-κB translocation dynamics quantification of our algorithm. Both pharmacological inhibition of NF-κB and short interfering RNAs targeting the inhibitor of NFκB, IκBα, demonstrated the ability of our method to identify compounds and genetic players that interfere with the nuclear transition of NF-κB.

TWEAK and cIAP1 regulate myoblast fusion through the noncanonical NF-κB signaling pathway

The fusion of mononucleated muscle progenitor cells (myoblasts) into multinucleated muscle fibers is a critical aspect of muscle development and regeneration. We identified the noncanonical nuclear factor κB (NF-κB) pathway as a signaling axis that drives the recruitment of myoblasts into new muscle fibers. Loss of cellular inhibitor of apoptosis 1 (cIAP1) protein led to constitutive activation of the noncanonical NF-κB pathway and an increase in the number of nuclei per myotube. Knockdown of essential mediators of NF-κB signaling, such as p100, RelB, inhibitor of κB kinase α, and NF-κB-inducing kinase, attenuated myoblast fusion in wild-type myoblasts. In contrast, the extent of myoblast fusion was increased when the activity of the noncanonical NF-κB pathway was enhanced by increasing the abundance of p52 and RelB or decreasing the abundance of tumor necrosis factor (TNF) receptor-associated factor 3, an inhibitor of this pathway. Low concentrations of the cytokine TNF-like weak inducer of apoptosis (TWEAK), which preferentially activates the noncanonical NF-κB pathway, also increased myoblast fusion, without causing atrophy or impairing myogenesis. These results identify roles for TWEAK, cIAP1, and noncanonical NF-κB signaling in the regulation of myoblast fusion and highlight a role for cytokine signaling during adult skeletal myogenesis.

p53 dynamics control cell fate

Cells transmit information through molecular signals that often show complex dynamical patterns. The dynamic behavior of the tumor suppressor p53 varies depending on the stimulus; in response to double-strand DNA breaks, it shows a series of repeated pulses. Using a computational model, we identified a sequence of precisely timed drug additions that alter p53 pulses to instead produce a sustained p53 response. This leads to the expression of a different set of downstream genes and also alters cell fate: Cells that experience p53 pulses recover from DNA damage, whereas cells exposed to sustained p53 signaling frequently undergo senescence. Our results show that protein dynamics can be an important part of a signal, directly influencing cellular fate decisions.

Modelling the interactions between TLR4 and IFNβ pathways

Bacterial lipopolysaccharide (LPS) association with their connate receptor TLR4 triggers Type I interferon signaling cascade through its MyD88 independent downstream. Compared to plethora of reported empirical data on both TLR4 and Type I interferon pathways, there is no known model to decipher crosstalk mechanisms between these two crucial innate immune pathogen activated pathways regulating vital transcriptional factors such as nuclear factor-κB (NFκB), IFNβ, the interferon-stimulated gene factor-3 (ISGF3) and an important cancer drug target protein kinase-R (PKR). Innate immune system is based on a sensitive balance of intricate interactions. In elucidating these interactions, in silico integration of pathways has great potential. Attempts confined to single pathway may not be effective in truly addressing source of real systems behavior. This is the first report combining toll-like receptor-4 (TLR4) and interferon beta (IFNβ) pathways in a single in silico model, analyzing their interactions, pinpointing the source of delay in PKR late phase activity and limiting the transcription of IFN and PKR by using a method including an statistical physics technique in reaction equations. The model quite successfully recapitulates published interferon regulatory factor-3 (IRF3) and IFNβ data from mouse macrophages and PKR data from mouse embryonic fibroblast cell lines. The simulations end up with an estimate of IRF3, IFNβ, ISGF3 dose dependent profiles mimicking nonlinear dose response characteristic of the system. Involvement of concomitant PKR downstream can unravel elusive mechanisms in specific profiles like NFκB regulation.

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.

Exploring the contextual sensitivity of factors that determine cell-to-cell variability in receptor-mediated apoptosis

Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand) variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions.

Spatiotemporal inhibition of innate immunity signaling by the Tbc1d23 RAB-GAP

We previously identified Tbc1d23 as a candidate novel regulator of innate immunity using comparative genomics RNA interference screens in Caenorhabditis elegans and mouse macrophages. Using Tbc1d23 knockout mice and macrophages engineered to overexpress Tbc1d23, we now show that Tbc1d23 is a general inhibitor of innate immunity signaling, strongly inhibiting multiple TLR and dectin-signaling pathways. Tbc1d23 likely acts downstream of the TLR-signaling adaptors MyD88 and Trif and upstream of the transcription factor XBP1. Importantly, like XBP1, Tbc1d23 affects the maintenance, but not the initiation, of inflammatory cytokine production induced by LPS. Tbc1d23 acts as a RAB-GAP to regulate innate immunity signaling. Thus, Tbc1d23 exerts its inhibitory effect on innate immunity signaling in a spatiotemporal fashion. The identification of a novel spatiotemporal regulator of innate immunity signaling validates the comparative genomics approach for innate immunity gene discovery.

Myrislignan attenuates lipopolysaccharide-induced inflammation reaction in murine macrophage cells through inhibition of NF-κB signalling pathway activation

Myrislignan is a new kind of lignan isolated from Myristica fragrans Houtt. Its antiinflammatory effects have not yet been reported. In the present study, the antiinflammatory effects and the underlying mechanisms of myrislignan in lipopolysaccharide (LPS)-induced inflammation in murine RAW 264.7 macrophage cells were investigated. Myrislignan significantly inhibited LPS-induced production of nitric oxide (NO) in a dose-dependent manner. It inhibited mRNA expression and release of interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α). This compound significantly inhibited mRNA and protein expressions of inducible NO synthase (iNOS) and cyclooxygenase-2 (COX-2) dose-dependently in LPS-stimulated macrophage cells. Further study showed that myrislignan decreased the cytoplasmic loss of inhibitor κB-α (IκB-α) protein and the translocation of NF-κB from cytoplasm to the nucleus. Our results suggest that myrislignan may exert its antiinflammatory effects in LPS-stimulated macrophages cells by inhibiting the NF-κB signalling pathway activation.

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.

Signal-dependent dynamics of transcription factor translocation controls gene expression

Information about environmental stimuli is often transmitted using common signaling molecules, but the mechanisms that ensure signaling specificity are not entirely known. Here we show that the identities and intensities of different stresses are transmitted by modulation of the amplitude, duration or frequency of nuclear translocation of the Saccharomyces cerevisiae general stress response transcription factor Msn2. Through artificial control of the dynamics of Msn2 translocation, we reveal how distinct dynamical schemes differentially affect reporter gene expression. Using a simple model, we predict stress-induced reporter gene expression from single-cell translocation dynamics. We then demonstrate that the response of natural target genes to dynamical modulation of Msn2 translocation is influenced by differences in the kinetics of promoter transitions and transcription factor binding properties. Thus, multiple environmental signals can trigger qualitatively different dynamics of a single transcription factor and influence gene expression patterns.

A Retrospective on Nuclear Receptor Regulation of Inflammation: Lessons from GR and PPARs

Members of the nuclear receptor superfamily have vital roles in regulating immunity and inflammation. The founding member, glucocorticoid receptor (GR), is the prototype to demonstrate immunomodulation via transrepression of the AP-1 and NF-κB signaling pathways. Peroxisome proliferator-activated receptors (PPARs) have emerged as key regulators of inflammation. This review examines the history and current advances in nuclear receptor regulation of inflammation by the crosstalk with AP-1 and NF-κB signaling, focusing on the roles of GR and PPARs. A better understanding of the molecular mechanism by which nuclear receptors inhibit proinflammatory signaling pathways will enable novel therapies to treat chronic inflammation.