Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing

A global assessment of stem cell engineering

Over the last 2 years a global assessment of stem cell engineering (SCE) was conducted with the sponsorship of the National Science Foundation, the National Cancer Institute at the National Institutes of Health, and the National Institute of Standards and Technology. The purpose was to gather information on the worldwide status and trends in SCE, that is, the involvement of engineers and engineering approaches in the stem cell field, both in basic research and in the translation of research into clinical applications and commercial products. The study was facilitated and managed by the World Technology Evaluation Center. The process involved site visits in both Asia and Europe, and it also included several different workshops. From this assessment, the panel concluded that there needs to be an increased role for engineers and the engineering approach. This will provide a foundation for the generation of new markets and future economic growth. To do this will require an increased investment in engineering, applied research, and commercialization as it relates to stem cell research and technology. It also will require programs that support interdisciplinary teams, new innovative mechanisms for academic-industry partnerships, and unique translational models. In addition, the global community would benefit from forming strategic partnerships between countries that can leverage existing and emerging strengths in different institutions. To implement such partnerships will require multinational grant programs with appropriate review mechanisms.

Fold change of nuclear NF-κB determines TNF-induced transcription in single cells

In response to tumor necrosis factor (TNF), NF-κB enters the nucleus and promotes inflammatory and stress-responsive gene transcription. Because NF-κB deregulation is associated with disease, one might expect strict control of NF-κB localization. However, nuclear NF-κB levels exhibit considerable cell-to-cell variability, even in unstimulated cells. To resolve this paradox and determine how transcription-inducing signals are encoded, we quantified single-cell NF-κB translocation dynamics and transcription in the same cells. We show that TNF-induced transcription correlates best with fold change in nuclear NF-κB, not absolute nuclear NF-κB abundance. Using computational modeling, we find that an incoherent feedforward loop, from competition for binding to κB motifs, could provide memory of the preligand state necessary for fold-change detection. Experimentally, we observed three gene-specific transcriptional patterns that our model recapitulates by modulating competition strength alone. Fold-change detection buffers against stochastic variation in signaling molecules and explains how cells tolerate variability in NF-κB abundance and localization.

Overexpression of heat shock protein 72 attenuates NF-κB activation using a combination of regulatory mechanisms in microglia

Overexpression of the inducible heat shock protein 70, Hsp72, has broadly cytoprotective effects and improves outcome following stroke. A full understanding of how Hsp72 protects cells against injury is elusive, though several distinct mechanisms are implicated. One mechanism is its anti-inflammatory effects. We study the effects of Hsp72 overexpression on activation of the transcription factor NF-κB in microglia combining experimentation and mathematical modeling, using TNFα to stimulate a microglial cell line stably overexpressing Hsp72. We find that Hsp72 overexpression reduces the amount of NF-κB DNA binding activity, activity of the upstream kinase IKK, and amount of IκBα inhibitor phosphorylated following TNFα application. Simulations evaluating several proposed mechanisms suggest that inhibition of IKK activation is an essential component of its regulatory activities. Unexpectedly we find that Hsp72 overexpression reduces the initial amount of the RelA/p65 NF-κB subunit in cells, contributing to the attenuated response. Neither mechanism in isolation, however, is sufficient to attenuate the response, providing evidence that Hsp72 relies upon multiple mechanisms to attenuate NF-κB activation. An additional observation from our study is that the induced expression of IκBα is altered significantly in Hsp72 expressing cells. While the mechanism responsible for this observation is not known, it points to yet another means by which Hsp72 may alter the NF-κB response. This study illustrates the multi-faceted nature of Hsp72 regulation of NF-κB activation in microglia and offers further clues to a novel mechanism by which Hsp72 may protect cells against injury.

Inducing heat shock or overexpressing certain heat shock proteins (HSPs) is known to protect against brain injury, such as that resulting from stroke. Understanding the mechanisms underlying protection at the cellular and molecular level is a subject of intense research, as such knowledge may prove beneficial in designing future therapies. Regulation of the activation of the key inflammatory transcription factor Nuclear Factor κB (NF-κB) is believed to be one critical mechanism. However how its activation is altered by Hsp72 remains unresolved. Here we examine NF-κB signaling in microglia cells overexpressing Hsp72, combining experimentation and mathematical modeling. We show that Hsp72 affects signaling using at least two essential and distinct mechanisms: attenuation of upstream kinase (IKK) activity and reduction of steady state NF-κB protein levels. We provide numerical evidence suggesting that neither mechanism in isolation is sufficient to account for the observed signaling. Furthermore, our observations suggest an intriguing additional level of regulation of gene expression and protein synthesis of the IκBα inhibitor, which opens interesting new avenues of research. These results provide novel insight into the mechanisms by which Hsp72 may regulate inflammation and protect brain cells from injury.

A model for the epigenetic switch linking inflammation to cell transformation: deterministic and stochastic approaches

Recently, a molecular pathway linking inflammation to cell transformation has been discovered. This molecular pathway rests on a positive inflammatory feedback loop between NF-κB, Lin28, Let-7 microRNA and IL6, which leads to an epigenetic switch allowing cell transformation. A transient activation of an inflammatory signal, mediated by the oncoprotein Src, activates NF-κB, which elicits the expression of Lin28. Lin28 decreases the expression of Let-7 microRNA, which results in higher level of IL6 than achieved directly by NF-κB. In turn, IL6 can promote NF-κB activation. Finally, IL6 also elicits the synthesis of STAT3, which is a crucial activator for cell transformation. Here, we propose a computational model to account for the dynamical behavior of this positive inflammatory feedback loop. By means of a deterministic model, we show that an irreversible bistable switch between a transformed and a non-transformed state of the cell is at the core of the dynamical behavior of the positive feedback loop linking inflammation to cell transformation. The model indicates that inhibitors (tumor suppressors) or activators (oncogenes) of this positive feedback loop regulate the occurrence of the epigenetic switch by modulating the threshold of inflammatory signal (Src) needed to promote cell transformation. Both stochastic simulations and deterministic simulations of a heterogeneous cell population suggest that random fluctuations (due to molecular noise or cell-to-cell variability) are able to trigger cell transformation. Moreover, the model predicts that oncogenes/tumor suppressors respectively decrease/increase the robustness of the non-transformed state of the cell towards random fluctuations. Finally, the model accounts for the potential effect of competing endogenous RNAs, ceRNAs, on the dynamics of the epigenetic switch. Depending on their microRNA targets, the model predicts that ceRNAs could act as oncogenes or tumor suppressors by regulating the occurrence of cell transformation.

An increasing amount of evidence demonstrates a close relation between inflammation and cancer development, which reveals the importance of the tumor microenvironment for the development of cancers. Recently, a molecular pathway linking inflammation to cell transformation, which is a prerequisite to cancer development, has been discovered. This molecular pathway is based on a positive inflammatory feedback loop between NF-κB, Lin28, Let-7 microRNA and IL6, allowing the occurrence of an epigenetic switch leading to cell transformation. Here, we propose a computational model to account for the dynamics of this epigenetic switch. We show that an irreversible bistable switch is at the core of the dynamics of the system. The model further indicates that oncogenes (activators of the switch) and tumor suppressors (inhibitors of the switch) regulate the occurrence of cell transformation by modulating the threshold of inflammatory signal needed to induce the switch. Stochastic simulations of the model suggest that molecular fluctuations are able to trigger cell transformation, highlighting possible links between stochasticity and cancer development. Finally, the model predicts a crucial role of competing endogenous RNAs (ceRNAs) for the dynamics of the epigenetic switch and the occurrence of cell transformation.

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.

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.

Digital response in T cells: to be or not to be

A recent study published in Immunity shows that foreign antigens elicit all-or-nothing T cell responses and that a single antigen is enough to trigger this digital cytokine secretion.

Regulation of transcriptional bursting by a naturally oscillating signal

Transcription is highly stochastic, occurring in irregular bursts. For temporal and spatial precision of gene expression, cells must somehow deal with this noisy behavior. To address how this is achieved, we investigated how transcriptional bursting is entrained by a naturally oscillating signal, by direct measurement of transcription together with signal dynamics in living cells. We identify a Dictyostelium gene showing rapid transcriptional oscillations with the same period as extracellular cAMP signaling waves. Bursting approaches antiphase to cAMP waves, with accelerating transcription cycles during differentiation. Although coupling between signal and transcription oscillations was clear at the population level, single-cell transcriptional bursts retained considerable heterogeneity, indicating that transcription is not governed solely by signaling frequency. Previous studies implied that burst heterogeneity reflects distinct chromatin states. Here we show that heterogeneity is determined by multiple intrinsic and extrinsic cues and is maintained by a transcriptional persistence. Unusually for a persistent transcriptional behavior, the lifetime was only 20 min, with rapid randomization of transcriptional state by the response to oscillatory signaling. Linking transcription to rapid signaling oscillations allows reduction of gene expression heterogeneity by temporal averaging, providing a mechanism to generate precision in cell choices during development.

Parallel measurement of dynamic changes in translation rates in single cells

Protein concentrations are often regulated by dynamic changes in translation rates. Nevertheless, it has been challenging to directly monitor changes in translation in living cells. We have developed a reporter system to measure real-time changes of translation rates in human or mouse individual cells by conjugating translation regulatory motifs to sequences encoding a nuclear targeted fluorescent protein and a controllable destabilization domain. Application of the method showed that individual cells undergo marked fluctuations in the translation rate of mRNAs whose 5' terminal oligopyrimidine (5' TOP) motif regulates the synthesis of ribosomal proteins. Furthermore, we show that small reductions in amino acid levels signal through different mTOR-dependent pathways to control TOP mRNA translation, whereas larger reductions in amino acid levels control translation through eIF2A. Our study demonstrates that dynamic measurements of single-cell activities of translation regulatory motifs can be used to identify and investigate fundamental principles of translation.

Functional roles of pulsing in genetic circuits

A fundamental problem in biology is to understand how genetic circuits implement core cellular functions. Time-lapse microscopy techniques are beginning to provide a direct view of circuit dynamics in individual living cells. Unexpectedly, we are discovering that key transcription and regulatory factors pulse on and off repeatedly, and often stochastically, even when cells are maintained in constant conditions. This type of spontaneous dynamic behavior is pervasive, appearing in diverse cell types from microbes to mammalian cells. Here, we review recent work showing how pulsing is generated and controlled by underlying regulatory circuits and how it provides critical capabilities to cells in stress response, signaling, and development. A major theme is the ability of pulsing to enable time-based regulation analogous to strategies used in engineered systems. Thus, pulsatile dynamics is emerging as a central, and still largely unexplored, layer of temporal organization in the cell.

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.

Advances in high-throughput single-cell microtechnologies

Micro-scale biological tools that have allowed probing of individual cells--from the genetic, to proteomic, to phenotypic level--have revealed important contributions of single cells to direct normal and diseased body processes. In analyzing single cells, sample heterogeneity between and within specific cell types drives the need for high-throughput and quantitative measurement of cellular parameters. In recent years, high-throughput single-cell analysis platforms have revealed rare genetic subpopulations in growing tumors, begun to uncover the mechanisms of antibiotic resistance in bacteria, and described the cell-to-cell variations in stem cell differentiation and immune cell response to activation by pathogens. This review surveys these recent technologies, presenting their strengths and contributions to the field, and identifies needs still unmet toward the development of high-throughput single-cell analysis tools to benefit life science research and clinical diagnostics.

RACK1 modulates NF-κB activation by interfering with the interaction between TRAF2 and the IKK complex

The transcription factor NF-κB plays a pivotal role in innate immunity in response to a variety of stimuli, and the coordinated regulation of this pathway determines the proper host responses to extracellular signals. In this study, we identified RACK1 as a novel negative regulator of NF-κB signaling, NF-κB-mediated cytokine induction and inflammatory reactions. RACK1 physically associates with the IKK complex in a TNF-triggered manner. This interaction interferes with the recruitment of the IKK complex to TRAF2, which is a critical step for IKK phosphorylation and subsequent activation triggered by TNF. By modulating the interaction between TRAF2 and IKK, RACK1 regulates the levels of NF-κB activation in response to different intensities of stimuli. Our findings suggest that RACK1 plays an important role in controlling the sensitivity of TNF-triggered NF-κB signaling by regulating IKK activation and provide new insight into the negative regulation of inflammatory reactions.

'Particle genetics': treating every cell as unique

Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the 'particles' of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations.

Moving H5N1 studies into the era of systems biology

The dynamics of H5N1 influenza virus pathogenesis are multifaceted and can be seen as an emergent property that cannot be comprehended without looking at the system as a whole. In past years, most of the high-throughput studies on H5N1-host interactions have focused on the host transcriptomic response, at the cellular or the lung tissue level. These studies pointed out that the dynamics and magnitude of the innate immune response and immune cell infiltration is critical to H5N1 pathogenesis. However, viral-host interactions are multidimensional and advances in technologies are creating new possibilities to systematically measure additional levels of 'omic data (e.g. proteomic, metabolomic, and RNA profiling) at each temporal and spatial scale (from the single cell to the organism) of the host response. Natural host genetic variation represents another dimension of the host response that determines pathogenesis. Systems biology models of H5N1 disease aim at understanding and predicting pathogenesis through integration of these different dimensions by using intensive computational modeling. In this review, we describe the importance of 'omic studies for providing a more comprehensive view of infection and mathematical models that are being developed to integrate these data. This review provides a roadmap for what needs to be done in the future and what computational strategies should be used to build a global model of H5N1 pathogenesis. It is time for systems biology of H5N1 pathogenesis to take center stage as the field moves toward a more comprehensive view of virus-host interactions.

Stimulus-induced modulation of transcriptional bursting in a single mammalian gene

Mammalian genes are often transcribed discontinuously as short bursts of RNA synthesis followed by longer silent periods. However, how these "on" and "off" transitions, together with the burst sizes, are modulated in single cells to increase gene expression upon stimulation is poorly characterized. By combining single-cell time-lapse luminescence imaging with stochastic modeling of the time traces, we quantified the transcriptional responses of the endogenous connective tissue growth factor gene to different physiological stimuli: serum and TGF-β1. Both stimuli caused a rapid and acute increase in burst sizes. Whereas TGF-β1 showed prolonged transcriptional activation mediated by an increase of transcription rate, serum stimulation resulted in a large and temporally tight first transcriptional burst, followed by a refractory period in the range of hours. Our study thus reveals how different physiological stimuli can trigger kinetically distinct transcriptional responses of the same gene.

The p53 response in single cells is linearly correlated to the number of DNA breaks without a distinct threshold

BACKGROUND

The tumor suppressor protein p53 is activated by cellular stress. DNA double strand breaks (DSBs) induce the activation of the kinase ATM, which stabilizes p53 and activates its transcriptional activity. Single cell analysis revealed that DSBs induced by gamma irradiation trigger p53 accumulation in a series of pulses that vary in number from cell to cell. Higher levels of irradiation increase the number of p53 pulses suggesting that they arise from periodic examination of the damage by ATM. If damage persists, additional pulses of p53 are triggered. The threshold of damage required for activating a p53 pulse is unclear. Previous studies that averaged the response across cell populations suggested that one or two DNA breaks are sufficient for activating ATM and p53. However, it is possible that by averaging over a population of cells important features of the dependency between DNA breaks and p53 dynamics are missed.

RESULTS

Using fluorescent reporters we developed a system for following in individual cells the number of DSBs, the kinetics of repair and the p53 response. We found a large variation in the initial number of DSBs and the rate of repair between individual cells. Cells with higher number of DSBs had higher probability of showing a p53 pulse. However, there was no distinct threshold number of breaks for inducing a p53 pulse. We present evidence that the decision to activate p53 given a specific number of breaks is not entirely stochastic, but instead is influenced by both cell-intrinsic factors and previous exposure to DNA damage. We also show that the natural variations in the initial amount of p53, rate of DSB repair and cell cycle phase do not affect the probability of activating p53 in response to DNA damage.

CONCLUSIONS

The use of fluorescent reporters to quantify DNA damage and p53 levels in live cells provided a quantitative analysis of the complex interrelationships between both processes. Our study shows that p53 activation differs even between cells that have a similar number of DNA breaks. Understanding the origin and consequences of such variability in normal and cancerous cells is crucial for developing efficient and selective therapeutic interventions.

Topical hypochlorite ameliorates NF-κB-mediated skin diseases in mice

Nuclear factor-κB (NF-κB) regulates cellular responses to inflammation and aging, and alterations in NF-κB signaling underlie the pathogenesis of multiple human diseases. Effective clinical therapeutics targeting this pathway remain unavailable. In primary human keratinocytes, we found that hypochlorite (HOCl) reversibly inhibited the expression of CCL2 and SOD2, two NF-κB-dependent genes. In cultured cells, HOCl inhibited the activity of inhibitor of NF-κB kinase (IKK), a key regulator of NF-κB activation, by oxidizing cysteine residues Cys114 and Cys115. In NF-κB reporter mice, topical HOCl reduced LPS-induced NF-κB signaling in skin. We further evaluated topical HOCl use in two mouse models of NF-κB-driven epidermal disease. For mice with acute radiation dermatitis, topical HOCl inhibited the expression of NF-κB-dependent genes, decreased disease severity, and prevented skin ulceration. In aged mice, topical HOCl attenuated age-dependent production of p16INK4a and expression of the DNA repair gene Rad50. Additionally, skin of aged HOCl-treated mice acquired enhanced epidermal thickness and proliferation, comparable to skin in juvenile animals. These data suggest that topical HOCl reduces NF-κB-mediated epidermal pathology in radiation dermatitis and skin aging through IKK modulation and motivate the exploration of HOCl use for clinical aims.

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.

Promoter decoding of transcription factor dynamics involves a trade-off between noise and control of gene expression

Numerous transcription factors (TFs) encode information about upstream signals in the dynamics of their activation, but how downstream genes decode these dynamics remains poorly understood. Using microfluidics to control the nucleocytoplasmic translocation dynamics of the budding yeast TF Msn2, we elucidate the principles that govern how different promoters convert dynamical Msn2 input into gene expression output in single cells. Combining modeling and experiments, we classify promoters according to their signal-processing behavior and reveal that multiple, distinct gene expression programs can be encoded in the dynamics of Msn2. We show that both oscillatory TF dynamics and slow promoter kinetics lead to higher noise in gene expression. Furthermore, we show that the promoter activation timescale is related to nucleosome remodeling. Our findings imply a fundamental trade-off: although the cell can exploit different promoter classes to differentially control gene expression using TF dynamics, gene expression noise fundamentally limits how much information can be encoded in the dynamics of a single TF and reliably decoded by promoters.

Industrial lab-on-a-chip: design, applications and scale-up for drug discovery and delivery

Microfluidics is an emerging and promising interdisciplinary technology which offers powerful platforms for precise production of novel functional materials (e.g., emulsion droplets, microcapsules, and nanoparticles as drug delivery vehicles- and drug molecules) as well as high-throughput analyses (e.g., bioassays, detection, and diagnostics). In particular, multiphase microfluidics is a rapidly growing technology and has beneficial applications in various fields including biomedicals, chemicals, and foods. In this review, we first describe the fundamentals and latest developments in multiphase microfluidics for producing biocompatible materials that are precisely controlled in size, shape, internal morphology and composition. We next describe some microfluidic applications that synthesize drug molecules, handle biological substances and biological units, and imitate biological organs. We also highlight and discuss design, applications and scale up of droplet- and flow-based microfluidic devices used for drug discovery and delivery.

On the effect of circadian oscillations on biochemical cell signaling by NF-κB

We report the results of a numerical investigation of a mathematical model for NF-κB oscillations, described by a set of ordinary nonlinear differential equations, when perturbed by a circadian oscillation. The main result is that a circadian rhythm, even when it represents a weak perturbation, enhances the signaling capabilities of NF-κB oscillations. This is done by turning rest states into periodic oscillations, and periodic oscillations into quasiperiodic oscillations. Strong perturbations result in complex periodic oscillations and even in chaos. Circadian rhythms would then result in a NF-κB dynamics that is more complex than the simple oscillations and rest states, initially reported for this model. This renders it more amenable for information coding.

Fluctuating vs. continuous exposure to H₂O₂: the effects on mitochondrial membrane potential, intracellular calcium, and NF-κB in astroglia

The effects of H2O2 are widely studied in cell cultures and other in vitro systems. However, such investigations are performed with the assumption that H2O2 concentration is constant, which may not properly reflect in vivo settings, particularly in redox-turbulent microenvironments such as mitochondria. Here we introduced and tested a novel concept of fluctuating oxidative stress. We treated C6 astroglial cells and primary astrocytes with H2O2, using three regimes of exposure - continuous, as well as fluctuating at low or high rate, and evaluated mitochondrial membrane potential and other parameters of mitochondrial activity - respiration, reducing capacity, and superoxide production, as well as intracellular ATP, intracellular calcium, and NF-κB activation. When compared to continuous exposure, fluctuating H2O2 induced a pronounced hyperpolarization in mitochondria, whereas the activity of electron transport chain appears not to be significantly affected. H2O2 provoked a decrease of ATP level and an increase of intracellular calcium concentration, independently of the regime of treatment. However, fluctuating H2O2 induced a specific pattern of large-amplitude fluctuations of calcium concentration. An impact on NF-κB activation was observed for high rate fluctuations, whereas continuous and low rate fluctuating oxidative stress did not provoke significant effects. Presented results outline the (patho)physiological relevance of redox fluctuations.

Proximity ligation assay for high-content profiling of cell signaling pathways on a microfluidic chip

Here, we present the full integration of a proximity ligation assay (PLA) on a microfluidic chip for systematic cell signaling studies. PLA is an in situ technology for the detection of protein interaction, post-translational modification, concentration, and cellular location with single-molecule resolution. Analytical performance advances on chip are achieved, including full automation of the biochemical PLA steps, target multiplexing, and reduction of antibody consumption by 2 orders of magnitude relative to standard procedures. In combination with a microfluidic cell-culturing platform, this technology allows one to gain control over 128 cell culture microenvironments. We demonstrate the use of the combined cell culture and protein analytic assay on chip by characterizing the Akt signaling pathway upon PDGF stimulation. Signal transduction is detected by monitoring the phosphorylation states of Akt, GSK-3β, p70S6K, S6, Erk1/2, and mTOR and the cellular location of FoxO3a in parallel with the PLA. Single-cell PLA results revealed for Akt and direct targets of Akt a maximum activation time of 4 to 8 min upon PDGF stimulation. Activation times for phosphorylation events downward in the Akt signaling pathway including the phosphorylation of S6, p70S6K, and mTOR are delayed by 8 to 10 min or exhibit a response time of at least 1 h. Quantitative confirmation of the Akt phosphorylation signal was determined with the help of a mouse embryonic fibroblast cell line deficient for rictor. In sum, this work with a miniaturized PLA chip establishes a biotechnological tool for general cell signaling studies and their dynamics relevant for a broad range of biological inquiry.

Recent developments in microfluidic large scale integration

In 2002, Thorsen et al. integrated thousands of micromechanical valves on a single microfluidic chip and demonstrated that the control of the fluidic networks can be simplified through multiplexors [1]. This enabled realization of highly parallel and automated fluidic processes with substantial sample economy advantage. Moreover, the fabrication of these devices by multilayer soft lithography was easy and reliable hence contributed to the power of the technology; microfluidic large scale integration (mLSI). Since then, mLSI has found use in wide variety of applications in biology and chemistry. In the meantime, efforts to improve the technology have been ongoing. These efforts mostly focus on; novel materials, components, micromechanical valve actuation methods, and chip architectures for mLSI. In this review, these technological advances are discussed and, recent examples of the mLSI applications are summarized.

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.

Fluidic and microfluidic tools for quantitative systems biology

Understanding genes and their functions is a daunting task due to the level of complexity in biological organisms. For discovering how genotype and phenotype are linked to each other, it is essential to carry out systematic studies with maximum sensitivity and high-throughput. Recent developments in fluid-handling technologies, both at the macro and micro scale, are now allowing us to apply engineering approaches to achieve this goal. With these newly developed tools, it is now possible to identify genetic factors that are responsible for particular phenotypes, perturb and monitor cells at the single-cell level, evaluate cell-to-cell variability, detect very rare phenotypes, and construct faithful in vitro disease models.

Stochastic responses may allow genetically diverse cell populations to optimize performance with simpler signaling networks

Two theories have emerged for the role that stochasticity plays in biological responses: first, that it degrades biological responses, so the performance of biological signaling machinery could be improved by increasing molecular copy numbers of key proteins; second, that it enhances biological performance, by enabling diversification of population-level responses. Using T cell biology as an example, we demonstrate that these roles for stochastic responses are not sufficient to understand experimental observations of stochastic response in complex biological systems that utilize environmental and genetic diversity to make cooperative responses. We propose a new role for stochastic responses in biology: they enable populations to make complex responses with simpler biochemical signaling machinery than would be required in the absence of stochasticity. Thus, the evolution of stochastic responses may be linked to the evolvability of different signaling machineries.

Probing cellular processes by long-term live imaging--historic problems and current solutions

Living organisms, tissues, cells and molecules are highly dynamic. The importance of their continuous and long-term observation has been recognized for over a century but has been limited by technological hurdles. Improvements in imaging technologies, genetics, protein engineering and data analysis have more recently allowed us to answer long-standing questions in biology using quantitative continuous long-term imaging. This requires a multidisciplinary collaboration between scientists of various backgrounds: biologists asking relevant questions, imaging specialists and engineers developing hardware, and informaticians and mathematicians developing software for data acquisition, analysis and computational modeling. Despite recent improvements, there are still obstacles to be addressed before this technology can achieve its full potential. This Commentary aims at providing an overview of currently available technologies for quantitative continuous long-term single-cell imaging, their limitations and what is required to bring this field to the next level. We provide an historical perspective on the development of this technology and discuss key issues in time-lapse imaging: keeping cells alive, using labels, reporters and biosensors, and hardware and software requirements. We highlight crucial and often non-obvious problems for researchers venturing into the field and hope to inspire experts in the field and from related disciplines to contribute to future solutions.

The details in the distributions: why and how to study phenotypic variability

Phenotypic variability is present even when genetic and environmental differences between cells are reduced to the greatest possible extent. For example, genetically identical bacteria display differing levels of resistance to antibiotics, clonal yeast populations demonstrate morphological and growth-rate heterogeneity, and mouse blastomeres from the same embryo have stochastic differences in gene expression. However, the distributions of phenotypes present among isogenic organisms are often overlooked; instead, many studies focus on population aggregates such as the mean. The details of these distributions are relevant to major questions in diverse fields, including the evolution of antimicrobial-drug and chemotherapy resistance. We review emerging experimental and statistical techniques that allow rigorous analysis of phenotypic variability and thereby may lead to advances across the biological sciences.

T lymphocytes sense antigens within seconds and make a decision within one minute

Adaptive immune responses are triggered by the rapid and sensitive detection of MHC-bound peptides by TCRs. The kinetics of early TCR/APC contacts are incompletely known. In this study, we used total internal reflection fluorescence microscopy to image human T cell membranes near model surfaces: contact was mediated by mobile protrusions of <0.4 μm diameter. The mean lifetime of contacts with a neutral surface was 8.6 s. Adhesive interactions increased mean contact time to 27.6 s. Additional presence of TCR ligands dramatically decreased contact to 13.7 s, thus evidencing TCR-mediated triggering of a pulling motion within seconds after ligand encounter. After an interaction typically involving 30-40 contacts formed during a 1-min observation period, TCR stimulation triggered a rapid and active cell spreading. Pulling events and cell spreading were mimicked by pharmacological phospholipase Cγ1 activation, and they were prevented by phospholipase Cγ1 inhibition. These results provide a quantitative basis for elucidating the earliest cell response to the detection of foreign Ags.

Multi-scale modeling predicts a balance of tumor necrosis factor-α and interleukin-10 controls the granuloma environment during Mycobacterium tuberculosis infection

Interleukin-10 (IL-10) and tumor necrosis factor-α (TNF-α) are key anti- and pro-inflammatory mediators elicited during the host immune response to Mycobacterium tuberculosis (Mtb). Understanding the opposing effects of these mediators is difficult due to the complexity of processes acting across different spatial (molecular, cellular, and tissue) and temporal (seconds to years) scales. We take an in silico approach and use multi-scale agent based modeling of the immune response to Mtb, including molecular scale details for both TNF-α and IL-10. Our model predicts that IL-10 is necessary to modulate macrophage activation levels and to prevent host-induced tissue damage in a granuloma, an aggregate of cells that forms in response to Mtb. We show that TNF-α and IL-10 parameters related to synthesis, signaling, and spatial distribution processes control concentrations of TNF-α and IL-10 in a granuloma and determine infection outcome in the long-term. We devise an overall measure of granuloma function based on three metrics - total bacterial load, macrophage activation levels, and apoptosis of resting macrophages - and use this metric to demonstrate a balance of TNF-α and IL-10 concentrations is essential to Mtb infection control, within a single granuloma, with minimal host-induced tissue damage. Our findings suggest that a balance of TNF-α and IL-10 defines a granuloma environment that may be beneficial for both host and pathogen, but perturbing the balance could be used as a novel therapeutic strategy to modulate infection outcomes.

Microfluidic platforms for single-cell protein analysis

Elucidation of the heterogeneity of cells is a challenging task due to the lack of efficient analytical tools to make measurements with single-cell resolution. Microfluidics has emerged as a powerful platform for single-cell analysis with the ability to manipulate small volume and integrate multiple sample preparation steps into one device. In this review, we discuss the differentiating advantages of microfluidic platforms that have been demonstrated for single-cell protein analysis.

RNA splicing regulates the temporal order of TNF-induced gene expression

When cells are induced to express inflammatory genes by treatment with TNF, the mRNAs for the induced genes appear in three distinct waves, defining gene groups I, II, and III, or early, intermediate, and late genes. To examine the basis for these different kinetic classes, we have developed a PCR-based procedure to distinguish pre-mRNAs from mRNAs. It shows that the three groups initiate transcription virtually simultaneously but that delays in splicing characterize groups II and III. We also examined the elongation times, concluding that pre-mRNA synthesis is coordinate but splicing differences directly regulate the timing of mRNA production.

Dissecting genealogy and cell cycle as sources of cell-to-cell variability in MAPK signaling using high-throughput lineage tracking

Cells, even those having identical genotype, exhibit variability in their response to external stimuli. This variability arises from differences in the abundance, localization, and state of cellular components. Such nongenetic differences are likely heritable between successive generations and can also be influenced by processes such as cell cycle, age, or interplay between different pathways. To address the contribution of nongenetic heritability and cell cycle in cell-to-cell variability we developed a high-throughput and fully automated microfluidic platform that allows for concurrent measurement of gene expression, cell-cycle periods, age, and lineage information under a large number of temporally changing medium conditions and using multiple strains. We apply this technology to examine the role of nongenetic inheritance in cell heterogeneity of yeast pheromone signaling. Our data demonstrate that the capacity to respond to pheromone is passed across generations and that the strength of the response correlations between related cells is affected by perturbations in the signaling pathway. We observe that a ste50Δ mutant strain exhibits highly heterogeneous response to pheromone originating from a unique asymmetry between mother and daughter response. On the other hand, fus3Δ cells were found to exhibit an unusually high correlation between mother and daughter cells that arose from a combination of extended cell-cycle periods of fus3Δ mothers, and decreased cell-cycle modulation of the pheromone pathway. Our results contribute to the understanding of the origins of cell heterogeneity and demonstrate the importance of automated platforms that generate single-cell data on several parameters.

Higher-order assemblies in a new paradigm of signal transduction

Recent studies have revealed that multiple intracellular signaling proteins may assemble into structured, yet sometimes infinite, higher-order signaling machines for transmission of receptor activation information to cellular responses. These studies advance our understanding of cell signaling and implicate new molecular mechanisms in proximity-driven enzyme activation, threshold behavior, signal amplification, reduction of biological noise, and temporal and spatial control of signal transduction.

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.

Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death

Populations of 'identical' cells are rarely truly identical. Even when in the same state of differentiation, isogenic cells may vary in expression of key signaling regulators, activate signal transduction at different thresholds, and consequently respond heterogeneously to a given stimulus. Here, we review how new experimental and analytical techniques are suited to connect these different levels of variability, quantitatively mapping the effects of cell-to-cell variability on cellular decision-making. In particular, we summarize how this helps classify signaling regulators according to the impact of their variability on biological functions. We further discuss how variability can also be leveraged to shed light on the molecular mechanisms regulating cellular signaling, from the individual cell to the population of cells as a whole.

Microfluidic interrogation and mathematical modeling of multi-regime calcium signaling dynamics

Through microfluidic interrogation we analyzed real-time calcium responses of HEK293 cells stimulated with short pulses of the M3 muscarinic receptor ligand carbachol in two different concentration regimes. Lower ligand concentrations elicit oscillatory calcium signals while higher concentrations trigger a rapid rise that eventually settles down at a steady-state slightly above pre-stimulus levels, referred to as an acute signal. Cells were periodically pulsed with carbachol at these two concentration regimes using a custom-made microfluidic platform, and the resulting calcium signals were measured with a single fluorescent readout. Pulsed stimulations at these two concentration regimes resulted in multiple types of response patterns that each delivered complementary information about the M3 muscarinic receptor signaling pathway. These multiple types of calcium response patterns enabled development of a comprehensive mathematical model of multi-regime calcium signaling. The resulting model suggests that dephosphorylation of deactivated receptors is rate limiting for recovery of calcium signals in the acute regime (high ligand concentration), while calcium replenishment and IP3 production determine signal recovery in the oscillatory regime (low ligand concentration). This study not only provides mechanistic insight into multi-regime signaling of the M3 muscarinic receptor pathway, but also provides a general strategy for analyzing multi-regime pathways using only one fluorescent readout.

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output, with important functional consequences. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs or proteins simultaneously, because genomic profiling methods could not be applied to single cells until very recently. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.

Protein nitration promotes inducible nitric oxide synthase transcription mediated by NF-κB in high glucose-stimulated human lens epithelial cells

Although an important event in hyperglycaemia-induced oxidative stress is the nuclear factor-kappa b (NF-κB)-activated inducible nitric oxide synthase (iNOS) expression, the underlying mechanism is not fully characterized. Peroxynitrite, formed from NO and superoxide, can induce multiple proteins nitration, even including NF-κB and iNOS, to alter their functions. In this study, we found high glucose caused conspicuous nitration of nuclear NF-κB p65 and its co-activator p300 in human lens epithelial cells. The nitration of NF-κB and p300 promoted their co-localization and binding to ensure the activation of the iNOS gene transcription. Moreover, nearly all predicted NF-κB binding sites in the human iNOS gene promoter were responsive to high glucose stimulation, might for a synergistic role. While, only the NF-κB binding site -5212 showed significant alterations by high glucose and peroxynitrite stimulations, indicating it a more important role in the protein nitration promoted iNOS gene transcription. Our results demonstrated that protein nitration can promote the NF-κB-activated iNOS gene transcription in human lens epithelial cells by high glucose stimulation.

Live cell imaging reveals marked variability in myoblast proliferation and fate

Background

During the process of muscle regeneration, activated stem cells termed satellite cells proliferate, and then differentiate to form new myofibers that restore the injured area. Yet not all satellite cells contribute to muscle repair. Some continue to proliferate, others die, and others become quiescent and are available for regeneration following subsequent injury. The mechanisms that regulate the adoption of different cell fates in a muscle cell precursor population remain unclear.

Methods

We have used live cell imaging and lineage tracing to study cell fate in the C2 myoblast line.

Results

Analyzing the behavior of individual myoblasts revealed marked variability in both cell cycle duration and viability, but similarities between cells derived from the same parental lineage. As a consequence, lineage sizes and outcomes differed dramatically, and individual lineages made uneven contributions toward the terminally differentiated population. Thus, the cohort of myoblasts undergoing differentiation at the end of an experiment differed dramatically from the lineages present at the beginning. Treatment with IGF-I increased myoblast number by maintaining viability and by stimulating a fraction of cells to complete one additional cell cycle in differentiation medium, and as a consequence reduced the variability of the terminal population compared with controls.

Conclusion

Our results reveal that heterogeneity of responses to external cues is an intrinsic property of cultured myoblasts that may be explained in part by parental lineage, and demonstrate the power of live cell imaging for understanding how muscle differentiation is regulated.

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.