Frequency-modulated pulses of ERK activity transmit quantitative proliferation signals

Differential cell-cycle control by oscillatory versus sustained Hes1 expression via p21

Oscillatory Hes1 expression activates cell proliferation, while high and sustained Hes1 expression induces quiescence, but the mechanism by which Hes1 differentially controls cell proliferation depending on its expression dynamics is unclear. Here, we show that oscillatory Hes1 expression down-regulates the expression of the cyclin-dependent kinase inhibitor p21 (Cdkn1a), which delays cell-cycle progression, and thereby activates the proliferation of mouse neural stem cells (NSCs). By contrast, sustained Hes1 overexpression up-regulates p21 expression and inhibits NSC proliferation, although it initially down-regulates p21 expression. Compared with Hes1 oscillation, sustained Hes1 overexpression represses Dusp7, a phosphatase for phosphorylated Erk (p-Erk), and increases the levels of p-Erk, which can up-regulate p21 expression. These results indicate that p21 expression is directly repressed by oscillatory Hes1 expression, but indirectly up-regulated by sustained Hes1 overexpression, suggesting that depending on its expression dynamics, Hes1 differentially controls NSC proliferation via p21.

FRA-1 as a Regulator of EMT and Metastasis in Breast Cancer

Among FOS-related components of the dimeric AP-1 transcription factor, the oncoprotein FRA-1 (encoded by FOSL1) is a key regulator of invasion and metastasis. The well-established FRA-1 pro-invasive activity in breast cancer, in which FOSL1 is overexpressed in the TNBC (Triple Negative Breast Cancer)/basal subtypes, correlates with the FRA-1-dependent transcriptional regulation of EMT (Epithelial-to-Mesenchymal Transition). After summarizing the major findings on FRA-1 in breast cancer invasiveness, we discuss the FRA-1 mechanistic links with EMT and cancer cell stemness, mediated by transcriptional and posttranscriptional interactions between FOSL1/FRA-1 and EMT-regulating transcription factors, miRNAs, RNA binding proteins and cytokines, along with other target genes involved in EMT. In addition to the FRA-1/AP-1 effects on the architecture of target promoters, we discuss the diagnostic and prognostic significance of the EMT-related FRA-1 transcriptome, along with therapeutic implications. Finally, we consider several novel perspectives regarding the less explored roles of FRA-1 in the tumor microenvironment and in control of the recently characterized hybrid EMT correlated with cancer cell plasticity, stemness, and metastatic potential. We will also examine the application of emerging technologies, such as single-cell analyses, along with animal models of TNBC and tumor-derived CTCs and PDXs (Circulating Tumor Cells and Patient-Derived Xenografts) for studying the FRA-1-mediated mechanisms in in vivo systems of EMT and metastasis.

The MAPK/ERK channel capacity exceeds 6 bit/hour

Living cells utilize signaling pathways to sense, transduce, and process information. As the extracellular stimulation often has rich temporal characteristics which may govern dynamic cellular responses, it is important to quantify the rate of information flow through the signaling pathways. In this study, we used an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter to assess the ability of the MAPK/ERK pathway to transduce signal encoded in a sequence of pulses. By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour. The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence. The high information transmission rate may enable the pathway to coordinate multiple processes including cell movement and respond to rapidly varying stimuli such as chemoattracting gradients created by other cells.

Cell-to-cell variability in Myc dynamics drives transcriptional heterogeneity in cancer cells

Cell-to-cell heterogeneity is vital for tumor evolution and survival. How cancer cells achieve and exploit this heterogeneity remains an active area of research. Here, we identify c-Myc as a highly heterogeneously expressed transcription factor and an orchestrator of transcriptional and phenotypic diversity in cancer cells. By monitoring endogenous c-Myc protein in individual living cells, we report the surprising pulsatile nature of c-Myc expression and the extensive cell-to-cell variability in its dynamics. We further show that heterogeneity in c-Myc dynamics leads to variable target gene transcription and that timing of c-Myc expression predicts cell-cycle progression rates and drug sensitivities. Together, our data advocate for a model in which cancer cells increase the heterogeneity of functionally diverse transcription factors such as c-Myc to rapidly survey transcriptional landscapes and survive stress.

Long-term p21 and p53 dynamics regulate the frequency of mitosis events and cell cycle arrest following radiation damage

Radiation exposure of healthy cells can halt cell cycle temporarily or permanently. In this work, we analyze the time evolution of p21 and p53 from two single cell datasets of retinal pigment epithelial cells exposed to several levels of radiation, and in particular, the effect of radiation on cell cycle arrest. Employing various quantification methods from signal processing, we show how p21 levels, and to a lesser extent p53 levels, dictate whether the cells are arrested in their cell cycle and how frequently these mitosis events are likely to occur. We observed that single cells exposed to the same dose of DNA damage exhibit heterogeneity in cellular outcomes and that the frequency of cell division is a more accurate monitor of cell damage rather than just radiation level. Finally, we show how heterogeneity in DNA damage signaling is manifested early in the response to radiation exposure level and has potential to predict long-term fate.

Oscillatory ERK Signaling and Morphology Determine Heterogeneity of Breast Cancer Cell Chemotaxis via MEK-ERK and p38-MAPK Signaling Pathways

Chemotaxis, regulated by oscillatory signals, drives critical processes in cancer metastasis. Crucial chemoattractant molecules in breast cancer, CXCL12 and EGF, drive the activation of ERK and Akt. Regulated by feedback and crosstalk mechanisms, oscillatory signals in ERK and Akt control resultant changes in cell morphology and chemotaxis. While commonly studied at the population scale, metastasis arises from small numbers of cells that successfully disseminate, underscoring the need to analyze processes that cancer cells use to connect oscillatory signaling to chemotaxis at single-cell resolution. Furthermore, little is known about how to successfully target fast-migrating cells to block metastasis. We investigated to what extent oscillatory networks in single cells associate with heterogeneous chemotactic responses and how targeted inhibitors block signaling processes in chemotaxis. We integrated live, single-cell imaging with time-dependent data processing to discover oscillatory signal processes defining heterogeneous chemotactic responses. We identified that short ERK and Akt waves, regulated by MEK-ERK and p38-MAPK signaling pathways, determine the heterogeneous random migration of cancer cells. By comparison, long ERK waves and the morphological changes regulated by MEK-ERK signaling, determine heterogeneous directed motion. This study indicates that treatments against chemotaxis in consider must interrupt oscillatory signaling.

Trapping of single diffusing particles by a circular disk on a reflecting flat surface. Absorbing hemisphere approximation

Recent progress in biophysics (for example, in studies of chemical sensing and spatiotemporal cell-signaling) poses new challenges to statistical theory of trapping of single diffusing particles. Here we deal with one of them, namely, trapping kinetics of single particles diffusing in a half-space bounded by a reflecting flat surface containing an absorbing circular disk. This trapping problem is essentially two-dimensional and the question of the angular dependence of the kinetics on the particle starting point is highly nontrivial. We propose an approximate approach to the problem that replaces the absorbing disk by an absorbing hemisphere of a properly chosen radius. This replacement makes the problem angular-independent and essentially one-dimensional. After the replacement one can find an exact solution for the particle propagator (Green's function) that allows one to completely characterize the kinetics. Extensive testing of the theoretical predictions based on the absorbing hemisphere approximation against three-dimensional Brownian dynamics simulations shows excellent agreement between the analytical and simulation results when the particle starts sufficiently far away from the disk. Our approach fails and the angular dependence of the kinetics is important when the distance of the particle starting point from the disk center is comparable with the disk radius. However, even when the initial distance is only two disk radii, the maximum relative error of the theoretical predictions is about 10%. The relative error rapidly decreases as the initial distance increases.

Cell cycle control by the insulin-like growth factor signal: at the crossroad between cell growth and mitotic regulation

In proliferating cells and tissues a number of checkpoints (G1/S and G2/M) preceding cell division (M-phase) require the signal provided by growth factors present in serum. IGFs (I and II) have been demonstrated to constitute key intrinsic components of the peptidic active fraction of mammalian serum. In vivo genetic ablation studies have shown that the cellular signal triggered by the IGFs through their cellular receptors represents a non-replaceable requirement for cell growth and cell cycle progression. Retroactive and current evaluation of published literature sheds light on the intracellular circuitry activated by these factors providing us with a better picture of the pleiotropic mechanistic actions by which IGFs regulate both cell size and mitogenesis under developmental growth as well as in malignant proliferation. The present work aims to summarize the cumulative knowledge learned from the IGF ligands/receptors and their intracellular signaling transducers towards control of cell size and cell-cycle with particular focus to their actionable circuits in human cancer. Furthermore, we bring novel perspectives on key functional discriminants of the IGF growth-mitogenic pathway allowing re-evaluation on some of its signal components based upon established evidences.

Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway

Nongenetic heterogeneity is key to cellular decisions, as even genetically identical cells respond in very different ways to the same external stimulus, e.g., during cell differentiation or therapeutic treatment of disease. Strong heterogeneity is typically already observed at the level of signaling pathways that are the first sensors of external inputs and transmit information to the nucleus where decisions are made. Since heterogeneity arises from random fluctuations of cellular components, mathematical models are required to fully describe the phenomenon and to understand the dynamics of heterogeneous cell populations. Here, we review the experimental and theoretical literature on cellular signaling heterogeneity, with special focus on the TGFβ/SMAD signaling pathway.

Nuclear-cytoplasmic compartmentalization of cyclin B1-Cdk1 promotes robust timing of mitotic events

The cyclin-dependent kinase (Cdk1) oscillator is widely characterized in homogenized cytosolic extracts, leaving unclear the impact of nucleocytoplasmic compartmentalization. Here, by developing a Förster resonance energy transfer (FRET) biosensor, we track Cdk1 spatiotemporal dynamics in reconstituted cells with or without side by side and find compartmentalization significantly modulates clock properties previously found in bulk studies. Although nucleus-absent cells display highly tunable frequency, the nucleus-present cells maintain constant frequency against cyclin B1 variations. Despite high expression variability, cyclin degraded within the same duration, enabling a robust mitotic phase. Moreover, Cdk1 and cyclin B1 cycle rigorously out-of-phase, ensuring wide phase-plane orbits, essential for oscillation robustness. Although Cdk1 in homogeneous extracts is well known for delayed switch-like activation, we find active cyclin B1-Cdk1 accumulates in nuclei, without delay, until the nuclear envelope breakdown (NEB) when another abrupt activation triggers anaphase. Cdk1 biphasic activation and spatial compartmentalization may together coordinate the accurate ordering of different downstream events.

Nodal signaling establishes a competency window for stochastic cell fate switching

Specification of the germ layers by Nodal signaling has long been regarded as an archetype of how graded morphogens induce different cell fates. However, this deterministic model cannot explain why only a subset of cells at the early zebrafish embryo margin adopt the endodermal fate, whereas their immediate neighbours, experiencing a similar signaling environment, become mesoderm. Combining pharmacology, quantitative imaging and single cell transcriptomics, we demonstrate that sustained Nodal signaling establishes a bipotential progenitor state from which cells can switch to an endodermal fate or differentiate into mesoderm. Switching is a random event, the likelihood of which is modulated by Fgf signaling. This inherently imprecise mechanism nevertheless leads to robust endoderm formation because of buffering at later stages. Thus, in contrast to previous deterministic models of morphogen action, Nodal signaling establishes a temporal window when cells are competent to undergo a stochastic cell fate switch, rather than determining fate itself.

Coordination of MAPK and p53 dynamics in the cellular responses to DNA damage and oxidative stress

In response to different cellular stresses, the transcription factor p53 undergoes different dynamics. p53 dynamics, in turn, control cell fate. However, distinct stresses can generate the same p53 dynamics but different cell fate outcomes, suggesting integration of dynamic information from other pathways is important for cell fate regulation. To determine how MAPK activities affect p53-mediated responses to DNA breaks and oxidative stress, we simultaneously tracked p53 and either ERK, JNK, or p38 activities in single cells. While p53 dynamics were comparable between the stresses, cell fate outcomes were distinct. Combining MAPK dynamics with p53 dynamics was important for distinguishing between the stresses and for generating temporal ordering of cell fate pathways. Furthermore, cross-talk between MAPKs and p53 controlled the balance between proliferation and cell death. These findings provide insight into how cells integrate signaling pathways with distinct temporal patterns of activity to encode stress specificity and drive different cell fate decisions.

Study of spatiotemporal regulation of kinase signaling using genetically encodable molecular tools

Precise spatiotemporal organization and regulation of signal transduction networks are essential for cellular response to internal and external cues. To understand how this biochemical activity architecture impacts cellular function, many genetically encodable tools which regulate kinase activity at a subcellular level have been developed. In this review, we highlight various types of genetically encodable molecular tools, including tools to regulate endogenous kinase activity and biorthogonal techniques to perturb kinase activity. Finally, we emphasize the use of these tools alongside biosensors for kinase activity to measure and perturb kinase activity in real time for a better understanding of the cellular biochemical activity architecture.

Network inference from perturbation time course data

Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible.

Relating individual cell division events to single-cell ERK and Akt activity time courses

Biochemical correlates of stochastic single-cell fates have been elusive, even for the well-studied mammalian cell cycle. We monitored single-cell dynamics of the ERK and Akt pathways, critical cell cycle progression hubs and anti-cancer drug targets, and paired them to division events in the same single cells using the non-transformed MCF10A epithelial line. Following growth factor treatment, in cells that divide both ERK and Akt activities are significantly higher within the S-G2 time window (~ 8.5-40 h). Such differences were much smaller in the pre-S-phase, restriction point window which is traditionally associated with ERK and Akt activity dependence, suggesting unappreciated roles for ERK and Akt in S through G2. Simple metrics of central tendency in this time window are associated with subsequent cell division fates. ERK activity was more strongly associated with division fates than Akt activity, suggesting Akt activity dynamics may contribute less to the decision driving cell division in this context. We also find that ERK and Akt activities are less correlated with each other in cells that divide. Network reconstruction experiments demonstrated that this correlation behavior was likely not due to crosstalk, as ERK and Akt do not interact in this context, in contrast to other transformed cell types. Overall, our findings support roles for ERK and Akt activity throughout the cell cycle as opposed to just before the restriction point, and suggest ERK activity dynamics may be more important than Akt activity dynamics for driving cell division in this non-transformed context.

Signaling oscillations: Molecular mechanisms and functional roles

Mounting evidence shows that oscillatory activity is widespread in cell signaling. Here, we review some of this recent evidence, focusing on both the molecular mechanisms that potentially underlie such dynamical behavior, and the potential advantages that signaling oscillations might have in cell function. The biological processes considered include cellular differentiation and tissue maintenance, intermittent responses in pluripotent stem cells, and collective cell migration during wound healing. With the aid of mathematical modeling, we review recent examples in which delayed negative feedback has been seen to act as a unifying principle that underpins this wide variety of phenomena.

Spatiotemporal control of ERK pulse frequency coordinates fate decisions during mammary acinar morphogenesis

The signaling events controlling proliferation, survival, and apoptosis during mammary epithelial acinar morphogenesis remain poorly characterized. By imaging single-cell ERK activity dynamics in MCF10A acini, we find that these fates depend on the average frequency of non-periodic ERK pulses. High pulse frequency is observed during initial acinus growth, correlating with rapid cell motility and proliferation. Subsequent decrease in motility correlates with lower ERK pulse frequency and quiescence. Later, during lumen formation, coordinated multicellular ERK waves emerge, correlating with high and low ERK pulse frequencies in outer surviving and inner dying cells, respectively. Optogenetic entrainment of ERK pulses causally connects high ERK pulse frequency with inner cell survival. Acini harboring the PIK3CA H1047R mutation display increased ERK pulse frequency and inner cell survival. Thus, fate decisions during acinar morphogenesis are coordinated by different spatiotemporal modalities of ERK pulse frequency.

Cellular context alters EGF-induced ERK dynamics and reveals potential crosstalk with GDF-15

Cellular signaling dynamics are sensitive to differences in ligand identity, levels, and temporal patterns. These signaling patterns are also impacted by the larger context that the cell experiences (i.e., stimuli such as media formulation or substrate stiffness that are constant in an experiment exploring a particular variable but may differ between independent experiments which explore that variable) although the reason for different dynamics is not always obvious. Here, we compared extracellular-regulated kinase (ERK) signaling in response to epidermal growth factor treatment of human mammary epithelial cells cultures in either well culture or a microfluidic device. Using a single-cell ERK kinase translocation reporter, we observed extended ERK activation in well culture and only transient activity in microfluidic culture. The activity in microfluidic culture resembled that of the control condition, suggesting that shear stress led to the early activity and a loss of autocrine factors dampened extended signaling. Through experimental analysis we identified growth differentiation factor-15 as a candidate factor that led to extended ERK activation through a protein kinase C-α/β dependent pathway. Our results demonstrate that context impacts ERK dynamics and that comparison of distinct contexts can be used to elucidate new aspects of the cell signaling network.

LITOS: a versatile LED illumination tool for optogenetic stimulation

Optogenetics has become a key tool to manipulate biological processes with high spatio-temporal resolution. Recently, a number of commercial and open-source multi-well illumination devices have been developed to provide throughput in optogenetics experiments. However, available commercial devices remain expensive and lack flexibility, while open-source solutions require programming knowledge and/or include complex assembly processes. We present a LED Illumination Tool for Optogenetic Stimulation (LITOS) based on an assembled printed circuit board controlling a commercially available 32 × 64 LED matrix as illumination source. LITOS can be quickly assembled without any soldering, and includes an easy-to-use interface, accessible via a website hosted on the device itself. Complex light stimulation patterns can easily be programmed without coding expertise. LITOS can be used with different formats of multi-well plates, petri dishes, and flasks. We validated LITOS by measuring the activity of the MAPK/ERK signaling pathway in response to different dynamic light stimulation regimes using FGFR1 and Raf optogenetic actuators. LITOS can uniformly stimulate all the cells in a well and allows for flexible temporal stimulation schemes. LITOS's affordability and ease of use aims at democratizing optogenetics in any laboratory.

Keeping Cell Death Alive: An Introduction into the French Cell Death Research Network

Since the Nobel Prize award more than twenty years ago for discovering the core apoptotic pathway in C. elegans, apoptosis and various other forms of regulated cell death have been thoroughly characterized by researchers around the world. Although many aspects of regulated cell death still remain to be elucidated in specific cell subtypes and disease conditions, many predicted that research into cell death was inexorably reaching a plateau. However, this was not the case since the last decade saw a multitude of cell death modalities being described, while harnessing their therapeutic potential reached clinical use in certain cases. In line with keeping research into cell death alive, francophone researchers from several institutions in France and Belgium established the French Cell Death Research Network (FCDRN). The research conducted by FCDRN is at the leading edge of emerging topics such as non-apoptotic functions of apoptotic effectors, paracrine effects of cell death, novel canonical and non-canonical mechanisms to induce apoptosis in cell death-resistant cancer cells or regulated forms of necrosis and the associated immunogenic response. Collectively, these various lines of research all emerged from the study of apoptosis and in the next few years will increase the mechanistic knowledge into regulated cell death and how to harness it for therapy.

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.

Towards 'end-to-end' analysis and understanding of biological timecourse data

Petabytes of increasingly complex and multidimensional live cell and tissue imaging data are generated every year. These videos hold large promise for understanding biology at a deep and fundamental level, as they capture single-cell and multicellular events occurring over time and space. However, the current modalities for analysis and mining of these data are scattered and user-specific, preventing more unified analyses from being performed over different datasets and obscuring possible scientific insights. Here, we propose a unified pipeline for storage, segmentation, analysis, and statistical parametrization of live cell imaging datasets.

Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signaling

Cells sense their surrounding by employing intracellular signaling pathways that transmit hormonal signals from the cell membrane to the nucleus. TGF-β/SMAD signaling encodes various cell fates, controls tissue homeostasis and is deregulated in diseases such as cancer. The pathway shows strong heterogeneity at the single-cell level, but quantitative insights into mechanisms underlying fluctuations at various time scales are still missing, partly due to inefficiency in the calibration of stochastic models that mechanistically describe signaling processes. In this work we analyze single-cell TGF-β/SMAD signaling and show that it exhibits temporal stochastic bursts which are dose-dependent and whose number and magnitude correlate with cell migration. We propose a stochastic modeling approach to mechanistically describe these pathway fluctuations with high computational efficiency. Employing high-order numerical integration and fitting to burst statistics we enable efficient quantitative parameter estimation and discriminate models that assume noise in different reactions at the receptor level. This modeling approach suggests that stochasticity in the internalization of TGF-β receptors into endosomes plays a key role in the observed temporal bursting. Further, the model predicts the single-cell dynamics of TGF-β/SMAD signaling in untested conditions, e.g., successfully reflects memory effects of signaling noise and cellular sensitivity towards repeated stimulation. Taken together, our computational framework based on burst analysis, noise modeling and path computation scheme is a suitable tool for the data-based modeling of complex signaling pathways, capable of identifying the source of temporal noise.

Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics

Combining single-cell measurements of ERK activity dynamics with perturbations provides insights into the MAPK network topology. We built circuits consisting of an optogenetic actuator to activate MAPK signaling and an ERK biosensor to measure single-cell ERK dynamics. This allowed us to conduct RNAi screens to investigate the role of 50 MAPK proteins in ERK dynamics. We found that the MAPK network is robust against most node perturbations. We observed that the ERK-RAF and the ERK-RSK2-SOS negative feedback operate simultaneously to regulate ERK dynamics. Bypassing the RSK2-mediated feedback, either by direct optogenetic activation of RAS, or by RSK2 perturbation, sensitized ERK dynamics to further perturbations. Similarly, targeting this feedback in a human ErbB2-dependent oncogenic signaling model increased the efficiency of a MEK inhibitor. The RSK2-mediated feedback is thus important for the ability of the MAPK network to produce consistent ERK outputs, and its perturbation can enhance the efficiency of MAPK inhibitors.

Signaling oscillations in embryonic development

Tight spatiotemporal control of cellular behavior and cell fate decisions is paramount to the formation of multicellular organisms during embryonic development. Intercellular communication via signaling pathways mediates this control. Interestingly, these signaling pathways are not static, but dynamic and change in activity over time. Signaling oscillations as a specific type of dynamics are found in various signaling pathways and model systems. Functions of oscillations include the regulation of periodic events or the transmission of information by encoding signals in the dynamic properties of a signaling pathway. For instance, signaling oscillations in neural or pancreatic progenitor cells modulate their proliferation and differentiation. Oscillations between neighboring cells can also be synchronized, leading to the emergence of waves traveling through the tissue. Such population-wide signaling oscillations regulate for example the consecutive segmentation of vertebrate embryos, a process called somitogenesis. Here, we outline our current understanding of signaling oscillations in embryonic development, how signaling oscillations are generated, how they are studied and how they contribute to the regulation of embryonic development.

A kinase translocation reporter reveals real-time dynamics of ERK activity in Drosophila

Extracellular signal-regulated kinase (ERK) lies downstream of a core signalling cascade that controls all aspects of development and adult homeostasis. Recent developments have led to new tools to image and manipulate the pathway. However, visualising ERK activity in vivo with high temporal resolution remains a challenge in Drosophila. We adapted a kinase translocation reporter (KTR) for use in Drosophila, which shuttles out of the nucleus when phosphorylated by ERK. We show that ERK-KTR faithfully reports endogenous ERK signalling activity in developing and adult tissues, and that it responds to genetic perturbations upstream of ERK. Using ERK-KTR in time-lapse imaging, we made two novel observations: firstly, sustained hyperactivation of ERK by expression of dominant-active epidermal growth factor receptor raised the overall level but did not alter the kinetics of ERK activity; secondly, the direction of migration of retinal basal glia correlated with their ERK activity levels, suggesting an explanation for the heterogeneity in ERK activity observed in fixed tissue. Our results show that KTR technology can be applied in Drosophila to monitor ERK activity in real-time and suggest that this modular tool can be further adapted to study other kinases. This article has an associated First Person interview with the first author of the paper.

SALSA, a genetically encoded biosensor for spatiotemporal quantification of Notch signal transduction in vivo

Notch-mediated lateral specification is a fundamental mechanism to resolve stochastic cell fate choices by amplifying initial differences between equivalent cells. To study how stochastic events impact Notch activity, we developed a biosensor, SALSA (sensor able to detect lateral signaling activity), consisting of an amplifying "switch"-Notch tagged with TEV protease-and a "reporter"-GFP fused to a nuclearly localized red fluorescent protein, separated by a TEVp cut site. When ligand activates Notch, TEVp enters the nucleus and releases GFP from its nuclear tether, allowing Notch activation to be quantified based on the changes in GFP subcellular localization. We show that SALSA accurately reports Notch activity in different signaling paradigms in Caenorhabditis elegans and use time-lapse imaging to test hypotheses about how stochastic elements ensure a reproducible and robust outcome in a canonical lin-12/Notch-mediated lateral signaling paradigm. SALSA should be generalizable to other experimental systems and be adaptable to increase options for bespoke "SynNotch" applications.

Quantitative live-cell imaging of GPCR downstream signaling dynamics

G-protein-coupled receptors (GPCRs) play an important role in sensing various extracellular stimuli, such as neurotransmitters, hormones, and tastants, and transducing the input information into the cell. While the human genome encodes more than 800 GPCR genes, only four Gα-proteins (Gαs, Gαi/o, Gαq/11, and Gα12/13) are known to couple with GPCRs. It remains unclear how such divergent GPCR information is translated into the downstream G-protein signaling dynamics. To answer this question, we report a live-cell fluorescence imaging system for monitoring GPCR downstream signaling dynamics. Genetically encoded biosensors for cAMP, Ca2+, RhoA, and ERK were selected as markers for GPCR downstream signaling, and were stably expressed in HeLa cells. GPCR was further transiently overexpressed in the cells. As a proof-of-concept, we visualized GPCR signaling dynamics of 5 dopamine receptors and 12 serotonin receptors, and found heterogeneity between GPCRs and between cells. Even when the same Gα proteins were known to be coupled, the patterns of dynamics in GPCR downstream signaling, including the signal strength and duration, were substantially distinct among GPCRs. These results suggest the importance of dynamical encoding in GPCR signaling.

Signalling dynamics, cell decisions, and homeostatic control in health and disease

Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.

The Fra-1/AP-1 Oncoprotein: From the "Undruggable" Transcription Factor to Therapeutic Targeting

The genetic and epigenetic changes affecting transcription factors, coactivators, and chromatin modifiers are key determinants of the hallmarks of cancer. The acquired dependence on oncogenic transcriptional regulators, representing a major determinant of cancer cell vulnerability, points to transcription factors as ideal therapeutic targets. However, given the unavailability of catalytic activities or binding pockets for small-molecule inhibitors, transcription factors are generally regarded as undruggable proteins. Among components of the AP-1 complex, the FOS-family transcription factor Fra-1, encoded by FOSL1, has emerged as a prominent therapeutic target. Fra-1 is overexpressed in most solid tumors, in response to the BRAF-MAPK, Wnt-beta-catenin, Hippo-YAP, IL-6-Stat3, and other major oncogenic pathways. In vitro functional analyses, validated in onco-mouse models and corroborated by prognostic correlations, show that Fra-1-containing dimers control tumor growth and disease progression. Fra-1 participates in key mechanisms of cancer cell invasion, Epithelial-to-Mesenchymal Transition, and metastatic spreading, by driving the expression of EMT-inducing transcription factors, cytokines, and microRNAs. Here we survey various strategies aimed at inhibiting tumor growth, metastatic dissemination, and drug resistance by interfering with Fra-1 expression, stability, and transcriptional activity. We summarize several tools aimed at the design and tumor-specific delivery of Fra-1/AP-1-specific drugs. Along with RNA-based therapeutics targeting the FOSL1 gene, its mRNA, or cognate regulatory circRNAs, we will examine the exploitation of blocking peptides, small molecule inhibitors, and innovative Fra-1 protein degraders. We also consider the possible caveats concerning Fra-1 inhibition in specific therapeutic contexts. Finally, we discuss a recent suicide gene therapy-based approach, aimed at selectively killing the Fra-1-overexpressing neoplastic cells.

LIM Tracker: a software package for cell tracking and analysis with advanced interactivity

Cell tracking is one of the most critical tools for time-lapse image analysis to observe cell behavior and cell lineages over a long period of time. However, the accompanying graphical user interfaces are often difficult to use and do not incorporate seamless manual correction, data analysis tools, or simple training set design tools if it is machine learning based. In this paper, we introduce our cell tracking software "LIM Tracker". This software has a conventional tracking function consisting of recognition processing and link processing, a sequential search-type tracking function based on pattern matching, and a manual tracking function. LIM Tracker enables the seamless use of these functions. In addition, the system incorporates a highly interactive and interlocking data visualization method, which displays analysis result in real time, making it possible to flexibly correct the data and reduce the burden of tracking work. Moreover, recognition functions with deep learning (DL) are also available, which can be used for a wide range of targets including stain-free images. LIM Tracker allows researchers to track living objects with good usability and high versatility for various targets. We present a tracking case study based on fluorescence microscopy images (NRK-52E/EKAREV-NLS cells or MCF-10A/H2B-iRFP-P2A-mScarlet-I-hGem-P2A-PIP-NLS-mNeonGreen cells) and phase contrast microscopy images (Glioblastoma-astrocytoma U373 cells). LIM Tracker is implemented as a plugin for ImageJ/Fiji. The software can be downloaded from https://github.com/LIMT34/LIM-Tracker .

A synthetic gene circuit for imaging-free detection of signaling pulses

Cells employ intracellular signaling pathways to sense and respond to changes in their external environment. In recent years, live-cell biosensors have revealed complex pulsatile dynamics in many pathways, but studies of these signaling dynamics are limited by the necessity of live-cell imaging at high spatiotemporal resolution. Here, we describe an approach to infer pulsatile signaling dynamics from a single measurement in fixed cells using a pulse-detecting gene circuit. We computationally screened for circuits with the capability to selectively detect signaling pulses, revealing an incoherent feedforward topology that robustly performs this computation. We implemented the motif experimentally for the Erk signaling pathway using a single engineered transcription factor and fluorescent protein reporter. Our "recorder of Erk activity dynamics" (READer) responds sensitively to spontaneous and stimulus-driven Erk pulses. READer circuits open the door to permanently labeling transient, dynamic cell populations to elucidate the mechanistic underpinnings and biological consequences of signaling dynamics.

Intermittent ERK oscillations downstream of FGF in mouse embryonic stem cells

Signal transduction networks generate characteristic dynamic activities to process extracellular signals and guide cell fate decisions such as to divide or differentiate. The differentiation of pluripotent cells is controlled by FGF/ERK signaling. However, only a few studies have addressed the dynamic activity of the FGF/ERK signaling network in pluripotent cells at high time resolution. Here, we use live cell sensors in wild-type and Fgf4-mutant mouse embryonic stem cells to measure dynamic ERK activity in single cells, for defined ligand concentrations and differentiation states. These sensors reveal pulses of ERK activity. Pulsing patterns are heterogeneous between individual cells. Consecutive pulse sequences occur more frequently than expected from simple stochastic models. Sequences become more prevalent with higher ligand concentration, but are rarer in more differentiated cells. Our results suggest that FGF/ERK signaling operates in the vicinity of a transition point between oscillatory and non-oscillatory dynamics in embryonic stem cells. The resulting heterogeneous dynamic signaling activities add a new dimension to cellular heterogeneity that may be linked to divergent fate decisions in stem cell cultures.

Bioimaging approaches for quantification of individual cell behavior during cell fate decisions

Tracking individual cells has allowed a new understanding of cellular behavior in human health and disease by adding a dynamic component to the already complex heterogeneity of single cells. Technically, despite countless advances, numerous experimental variables can affect data collection and interpretation and need to be considered. In this review, we discuss the main technical aspects and biological findings in the analysis of the behavior of individual cells. We discuss the most relevant contributions provided by these approaches in clinically relevant human conditions like embryo development, stem cells biology, inflammation, cancer and microbiology, along with the cellular mechanisms and molecular pathways underlying these conditions. We also discuss the key technical aspects to be considered when planning and performing experiments involving the analysis of individual cells over long periods. Despite the challenges in automatic detection, features extraction and long-term tracking that need to be tackled, the potential impact of single-cell bioimaging is enormous in understanding the pathogenesis and development of new therapies in human pathophysiology.

Engineered Cell Line Imaging Assay Differentiates Pathogenic from Non-Pathogenic Bacteria

Cell culture systems have greatly expanded our understanding of how bacterial pathogens target signaling pathways to manipulate the host and cause infection. Advances in genetic engineering have allowed for the creation of fluorescent protein readouts within signaling pathways, but these techniques have been underutilized in pathogen biology. Here, we genetically engineered a lung cell line with fluorescent reporters for extracellular signal-related kinase (ERK) and the downstream transcription factor FOS-related antigen 1 (Fra1) and evaluated signaling after inoculation with pathogenic and non-pathogenic bacteria. Cells were inoculated with 100 colony-forming units of Acinetobacter baylyi, Klebsiella pneumoniae, Pseudomonas aeruginosa, Streptococcus agalactiae, or Staphylococcus epidermidis and imaged in a multi-mode reader. The alamarBlue cell viability assay was used as a reference test and showed that pathogenic P. aeruginosa induced significant (p < 0.05) cell death after 8 h in both wild-type and engineered cell lines compared to non-pathogenic S. epidermidis. In engineered cells, we found that Fra1 signaling was disrupted in as little as 4 h after inoculation with bacterial pathogens compared to delayed disruption in signaling by non-pathogenic S. epidermidis. Overall, we demonstrate that low levels of pathogenic versus non-pathogenic bacteria can be rapidly and sensitively screened based on ERK-Fra1 signaling.

Subcellular regulation of glucose metabolism through multienzyme glucosome assemblies by EGF-ERK1/2 signaling pathways

A multienzyme metabolic assembly for human glucose metabolism, namely the glucosome, has been previously demonstrated to partition glucose flux between glycolysis and building block biosynthesis in an assembly size-dependent manner. Among three different sizes of glucosome assemblies, we have shown that large-sized glucosomes are functionally associated with the promotion of serine biosynthesis in the presence of epidermal growth factor (EGF). However, due to multifunctional roles of EGF in signaling pathways, it is unclear which EGF-mediated signaling pathways promote these large glucosome assemblies in cancer cells. In this study, we used Luminex multiplexing assays and high-content single-cell imaging to demonstrate that EGF triggers temporal activation of extracellular signal-regulated kinases 1/2 (ERK1/2) in Hs578T cells. Subsequently, we found that treatments with a pharmacological inhibitor of ERK1/2, SCH772984, or short-hairpin RNAs targeting ERK1/2 promote the dissociation of large-sized assemblies to medium-sized assemblies in Hs578T cells. In addition, our Western blot analyses revealed that EGF treatment does not increase the expression levels of enzymes that are involved in both glucose metabolism and serine biosynthesis. The observed spatial transition of glucosome assemblies between large and medium sizes appears to be mediated by the degree of dynamic partitioning of glucosome enzymes without changing their expression levels. Collectively, our study demonstrates that EGF–ERK1/2 signaling pathways play an important role in the upregulation of large-sized glucosomes in cancer cells, thus functionally governing the promotion of glycolysis-derived serine biosynthesis.

Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors

Kinases play key roles in signaling networks that are activated by G-protein-coupled receptors (GPCRs). Kinase activities are generally inferred from cell lysates, hiding cell-to-cell variability. To study the dynamics and heterogeneity of ERK and Akt proteins, we employed high-content biosensor imaging with kinase translocation reporters. The kinases were activated with GPCR ligands. We observed ligand concentration-dependent response kinetics to histamine, α2-adrenergic and S1P receptor stimulation. By using G-protein inhibitors, we observed that Gq mediated the ERK and Akt responses to histamine. In contrast, Gi was necessary for ERK and Akt activation in response to α2-adrenergic receptor activation. ERK and Akt were also strongly activated by S1P, showing high heterogeneity at the single-cell level, especially for ERK. Cluster analysis of time series derived from 68,000 cells obtained under the different conditions revealed several distinct populations of cells that display similar response dynamics. ERK response dynamics to S1P showed high heterogeneity, which was reduced by the inhibition of Gi. To conclude, we have set up an imaging and analysis strategy that reveals substantial cell-to-cell heterogeneity in kinase activity driven by GPCRs.

Summary: High-content biosensor imaging with kinase translocation reporters reveals substantial cell-to-cell heterogeneity in kinase activity driven by G-protein-coupled receptors.

Pooled genetic perturbation screens with image-based phenotypes

Discovery of the genetic components underpinning fundamental and disease-related processes is being rapidly accelerated by combining efficient, programmable genetic engineering with phenotypic readouts of high spatial, temporal and/or molecular resolution. Microscopy is a fundamental tool for studying cell biology, but its lack of high-throughput sequence readouts hinders integration in large-scale genetic screens. Optical pooled screens using in situ sequencing provide massively scalable integration of barcoded lentiviral libraries (e.g., CRISPR perturbation libraries) with high-content imaging assays, including dynamic processes in live cells. The protocol uses standard lentiviral vectors and molecular biology, providing single-cell resolution of phenotype and engineered genotype, scalability to millions of cells and accurate sequence reads sufficient to distinguish >106 perturbations. In situ amplification takes ~2 d, while sequencing can be performed in ~1.5 h per cycle. The image analysis pipeline provided enables fully parallel automated sequencing analysis using a cloud or cluster computing environment.

Live imaging approach of dynamic multicellular responses in ERK signaling during vertebrate tissue development

The chemical and mechanical responses of cells via the exchange of information during growth and development result in the formation of biological tissues. Information processing within the cells through the signaling pathways and networks inherent to the constituent cells has been well-studied. However, the cell signaling mechanisms responsible for generating dynamic multicellular responses in developing tissues remain unclear. Here, I review the dynamic multicellular response systems during the development and growth of vertebrate tissues based on the extracellular signal-regulated kinase (ERK) pathway. First, an overview of the function of the ERK signaling network in cells is provided, followed by descriptions of biosensors essential for live imaging of the quantification of ERK activity in tissues. Then adducing four examples, I highlight the contribution of live imaging techniques for studying the involvement of spatio-temporal patterns of ERK activity change in tissue development and growth. In addition, theoretical implications of ERK signaling are also discussed from the viewpoint of dynamic systems. This review might help in understanding ERK-mediated dynamic multicellular responses and tissue morphogenesis.

microRNA-Mediated Encoding and Decoding of Time-Dependent Signals in Tumorigenesis

microRNAs, pivotal post-transcriptional regulators of gene expression, in the past decades have caught the attention of researchers for their involvement in different biological processes, ranging from cell development to cancer. Although lots of effort has been devoted to elucidate the topological features and the equilibrium properties of microRNA-mediated motifs, little is known about how the information encoded in frequency, amplitude, duration, and other features of their regulatory signals can affect the resulting gene expression patterns. Here, we review the current knowledge about microRNA-mediated gene regulatory networks characterized by time-dependent input signals, such as pulses, transient inputs, and oscillations. First, we identify the general characteristic of the main motifs underlying temporal patterns. Then, we analyze their impact on two commonly studied oncogenic networks, showing how their dysfunction can lead to tumorigenesis.

Capturing Biomarkers and Molecular Targets in Cellular Landscapes From Dynamic Reaction Network Models and Machine Learning

Computational dynamic ODE models of cell function describing biochemical reactions have been created for decades, but on a small scale. Still, they have been highly effective in describing and predicting behaviors. For example, oscillatory phospho-ERK levels were predicted and confirmed in MAPK signaling encompassing both positive and negative feedback loops. These models typically were limited and not adapted to large datasets so commonly found today. But importantly, ODE models describe reaction networks in well-mixed systems representing the cell and can be simulated with ordinary differential equations that are solved deterministically. Stochastic solutions, which can account for noisy reaction networks, in some cases, also improve predictions. Today, dynamic ODE models rarely encompass an entire cell even though it might be expected that an upload of the large genomic, transcriptomic, and proteomic datasets may allow whole cell models. It is proposed here to combine output from simulated dynamic ODE models, completed with omics data, to discover both biomarkers in cancer a priori and molecular targets in the Machine Learning setting.

ERK signaling for cell migration and invasion

The RAS - Extracellular signal-regulated kinase (RAS-ERK) pathway plays a conserved role in promoting cell migration and invasion. Growth factors, adhesion, and oncogenes activate ERK. While historically studied with respect to its control of cell proliferation and differentiation, the signaling pattern and effectors specific for cell migration are now coming to light. New advances in pathway probes have revealed how steady-state ERK activity fluctuates within individual cells and propagates to neighboring cells. We review new findings on the different modes of ERK pathway stimulation and how an increased baseline level of activity promotes single cell and collective migration and invasion. We discuss how ERK drives actin polymerization and adhesion turnover for edge protrusion and how cell contraction stimulates cell movement and ERK activity waves in epithelial sheets. With the steady development of new biosensors for monitoring spatial and temporal ERK activity, determining how cells individually interpret the multiple in vivo signals to ERK is within reach.

Substratum stiffness regulates Erk signaling dynamics through receptor-level control

The EGFR/Erk pathway is triggered by extracellular ligand stimulation, leading to stimulus-dependent dynamics of pathway activity. Although mechanical properties of the microenvironment also affect Erk activity, their effects on Erk signaling dynamics are poorly understood. Here, we characterize how the stiffness of the underlying substratum affects Erk signaling dynamics in mammary epithelial cells. We find that soft microenvironments attenuate Erk signaling, both at steady state and in response to epidermal growth factor (EGF) stimulation. Optogenetic manipulation at multiple signaling nodes reveals that intracellular signal transmission is largely unaffected by substratum stiffness. Instead, we find that soft microenvironments decrease EGF receptor (EGFR) expression and alter the amount and spatial distribution of EGF binding at cell membranes. Our data demonstrate that the mechanical microenvironment tunes Erk signaling dynamics via receptor-ligand interactions, underscoring how multiple microenvironmental signals are jointly processed through a highly conserved pathway that regulates tissue development, homeostasis, and disease progression.

Emerging Role of EGFR Mutations in Creating an Immune Suppressive Tumour Microenvironment

Several types of tumours overexpress the Epidermal Growth Factor Receptor (EGFR) in either wild type or mutated form. These tumours are often highly aggressive and difficult to treat. The underlying mechanisms for this phenomenon have remained largely unresolved, but recent publications suggest two independent mechanisms that may contribute. According to one line of research, tumours that overexpress the EGFR grow autonomously and become “addicted” to growth factor signalling. Inhibition of this signal using EGFR inhibitors can, therefore, induce cell death in tumour cells and lead to tumour shrinkage. The other line of research, as highlighted by recent findings, suggests that the overexpression, specifically of mutant forms of the EGFR, may create an immune-suppressive and lymphocyte depleted microenvironment within tumours. Such a lymphocyte depleted microenvironment may explain the resistance of EGFR overexpressing cancers to tumour therapies, particularly to check-point inhibitor treatments. In this article, we discuss the recent data which support an immune modulatory effect of EGFR signalling and compare these published studies with the most recent data from The Cancer Genome Atlas (TCGA), in this way, dissecting possible underlying mechanisms. We thereby focus our study on how EGFR overexpression may lead to the local activation of TGFβ, and hence to an immune suppressive environment. Consequently, we define a novel concept of how the mitogenic and immune modulatory effects of EGFR overexpression may contribute to tumour resistance to immunotherapy, and how EGFR specific inhibitors could be used best to enhance the efficacy of tumour therapy.

Chemical-Biology-derived in vivo Sensors: Past, Present, and Future

To understand the complex biochemistry and biophysics of biological systems, one needs to be able to monitor local concentrations of molecules, physical properties of macromolecular assemblies and activation status of signaling pathways, in real time, within single cells, and at high spatio-temporal resolution. Here we look at the tools that have been / are being / need to be provided by chemical biology to address these challenges. In particular, we highlight the utility of molecular probes that help to better measure mechanical forces and flux through key signalling pathways. Chemical biology can be used to both build biosensors to visualize, but also actuators to perturb biological processes. An emergent theme is the possibility to multiplex measurements of multiple cellular processes. Advances in microscopy automation now allow us to acquire datasets for 1000's of cells. This produces high dimensional datasets that require computer vision approaches that automate image analysis. The high dimensionality of these datasets are often not immediately accessible to human intuition, and, similarly to 'omics technologies, require statistical approaches for their exploitation. The field of biosensor imaging is therefore experiencing a multidisciplinary transition that will enable it to realize its full potential as a tool to provide a deeper appreciation of cell physiology.

Signalling dynamics in embryonic development

In multicellular organisms, cellular behaviour is tightly regulated to allow proper embryonic development and maintenance of adult tissue. A critical component in this control is the communication between cells via signalling pathways, as errors in intercellular communication can induce developmental defects or diseases such as cancer. It has become clear over the last years that signalling is not static but varies in activity over time. Feedback mechanisms present in every signalling pathway lead to diverse dynamic phenotypes, such as transient activation, signal ramping or oscillations, occurring in a cell type- and stage-dependent manner. In cells, such dynamics can exert various functions that allow organisms to develop in a robust and reproducible way. Here, we focus on Erk, Wnt and Notch signalling pathways, which are dynamic in several tissue types and organisms, including the periodic segmentation of vertebrate embryos, and are often dysregulated in cancer. We will discuss how biochemical processes influence their dynamics and how these impact on cellular behaviour within multicellular systems.

Electrically synchronizing and modulating the dynamics of ERK activation to regulate cell fate

Intracellular signaling dynamics play fundamental roles in cell biology. Precise modulation of the amplitude, duration, and frequency of signaling activation will be a powerful approach to investigate molecular mechanisms as well as to engineer signaling to control cell behaviors. Here, we showed a practical approach to achieve precise amplitude modulation (AM), frequency modulation (FM), and duration modulation (DM) of MAP kinase activation. Alternating current (AC) electrical stimulation induced synchronized ERK activation. Amplitude and duration of ERK activation were controlled by varying stimulation strength and duration. ERK activation frequencies were arbitrarily modulated with trains of short AC applications with accurately defined intervals. Significantly, ERK dynamics coded by well-designed AC can rewire PC12 cell fate independent of growth factors. This technique can be used to synchronize and modulate ERK activation dynamics, thus would offer a practical way to control cell behaviors in vivo without the use of biochemical agents or genetic manipulation.

•

Alternating-current (AC) electric field activates ERK independently of growth factors

•

AC stimulation length modulates the amplitude and duration of ERK activation

•

On-off time interval of AC modulates the frequency of ERK activation peaks

•

Electrical modulation of ERK dynamics promotes neuronal differentiation of PC12 cells

Design and implementation of a microfluidic device capable of temporal growth factor delivery reveal filtering capabilities of the EGFR/ERK pathway

Utilizing microfluidics to mimic the dynamic temporal changes of growth factor and cytokine concentrations in vivo has greatly increased our understanding of how signal transduction pathways are structured to encode extracellular stimuli. To date, these devices have focused on delivering pulses of varying frequency, and there are limited cell culture models for delivering slowly increasing concentrations of stimuli that cells may experience in vivo. To examine this setting, we developed and validated a microfluidic device that can deliver increasing concentrations of growth factor over periods ranging from 6 to 24 h. Using this device and a fluorescent biosensor of extracellular-regulated kinase (ERK) activity, we delivered a slowly increasing concentration of epidermal growth factor (EGF) to human mammary epithelial cells and surprisingly observed minimal ERK activation, even at concentrations that stimulate robust activity in bolus delivery. The cells remained unresponsive to subsequent challenges with EGF, and immunocytochemistry suggested that the loss of an epidermal growth factor receptor was responsible. Cells were then challenged with faster rates of change of EGF, revealing an increased ERK activity as a function of rate of change. Specifically, both the fraction of cells that responded and the length of ERK activation time increased with the rate of change. This microfluidic device fills a gap in the current repertoire of in vitro microfluidic devices and demonstrates that slower, more physiological changes in growth factor presentation can reveal new regulatory mechanisms for how signal transduction pathways encode changes in the extracellular growth factor milieu.