A guide to ERK dynamics, part 1: mechanisms and models.

Extracellular signal-regulated kinase (ERK) has long been studied as a key driver of both essential cellular processes and disease. A persistent question has been how this single pathway is able to direct multiple cell behaviors, including growth, proliferation, and death. Modern biosensor studies have revealed that the temporal pattern of ERK activity is highly variable and heterogeneous, and critically, that these dynamic differences modulate cell fate. This two-part review discusses the current understanding of dynamic activity in the ERK pathway, how it regulates cellular decisions, and how these cell fates lead to tissue regulation and pathology. In part 1, we cover the optogenetic and live-cell imaging technologies that first revealed the dynamic nature of ERK, as well as current challenges in biosensor data analysis. We also discuss advances in mathematical models for the mechanisms of ERK dynamics, including receptor-level regulation, negative feedback, cooperativity, and paracrine signaling. While hurdles still remain, it is clear that higher temporal and spatial resolution provide mechanistic insights into pathway circuitry. Exciting new algorithms and advanced computational tools enable quantitative measurements of single-cell ERK activation, which in turn inform better models of pathway behavior. However, the fact that current models still cannot fully recapitulate the diversity of ERK responses calls for a deeper understanding of network structure and signal transduction in general.

A guide to ERK dynamics, part 2: downstream decoding.

Signaling by the extracellular signal-regulated kinase (ERK) pathway controls many cellular processes, including cell division, death, and differentiation. In this second installment of a two-part review, we address the question of how the ERK pathway exerts distinct and context-specific effects on multiple processes. We discuss how the dynamics of ERK activity induce selective changes in gene expression programs, with insights from both experiments and computational models. With a focus on single-cell biosensor-based studies, we summarize four major functional modes for ERK signaling in tissues: adjusting the size of cell populations, gradient-based patterning, wave propagation of morphological changes, and diversification of cellular gene expression states. These modes of operation are disrupted in cancer and other related diseases and represent potential targets for therapeutic intervention. By understanding the dynamic mechanisms involved in ERK signaling, there is potential for pharmacological strategies that not only simply inhibit ERK, but also restore functional activity patterns and improve disease outcomes.

Oncogenic mutant RAS signaling activity is rescaled by the ERK/MAPK pathway.

Activating mutations in RAS are present in ~ 30% of human tumors, and the resulting aberrations in ERK/MAPK signaling play a central role in oncogenesis. However, the form of these signaling changes is uncertain, with activating RAS mutants linked to both increased and decreased ERK activation in vivo. Rationally targeting the kinase activity of this pathway requires clarification of the quantitative effects of RAS mutations. Here, we use live-cell imaging in cells expressing only one RAS isoform to quantify ERK activity with a new level of accuracy. We find that despite large differences in their biochemical activity, mutant KRAS isoforms within cells have similar ranges of ERK output. We identify roles for pathway-level effects, including variation in feedback strength and feedforward modulation of phosphatase activity, that act to rescale pathway sensitivity, ultimately resisting changes in the dynamic range of ERK activity while preserving responsiveness to growth factor stimuli. Our results reconcile seemingly inconsistent reports within the literature and imply that the signaling changes induced by RAS mutations early in oncogenesis are subtle.

Receptor Level Mechanisms Are Required for Epidermal Growth Factor (EGF)-stimulated Extracellular Signal-regulated Kinase (ERK) Activity Pulses.

In both physiological and cell culture systems, EGF-stimulated ERK activity occurs in discrete pulses within individual cells. Many feedback loops are present in the EGF receptor (EGFR)-ERK network, but the mechanisms driving pulsatile ERK kinetics are unknown. Here, we find that in cells that respond to EGF with frequency-modulated pulsatile ERK activity, stimulation through a heterologous TrkA receptor system results in non-pulsatile, amplitude-modulated activation of ERK. We further dissect the kinetics of pulse activity using a combination of FRET- and translocation-based reporters and find that EGFR activity is required to maintain ERK activity throughout the 10-20-minute lifetime of pulses. Together, these data indicate that feedbacks operating within the core Ras-Raf-MEK-ERK cascade are insufficient to drive discrete pulses of ERK activity and instead implicate mechanisms acting at the level of EGFR.

Model-based analysis for qualitative data: an application in Drosophila germline stem cell regulation.

Discovery in developmental biology is often driven by intuition that relies on the integration of multiple types of data such as fluorescent images, phenotypes, and the outcomes of biochemical assays. Mathematical modeling helps elucidate the biological mechanisms at play as the networks become increasingly large and complex. However, the available data is frequently under-utilized due to incompatibility with quantitative model tuning techniques. This is the case for stem cell regulation mechanisms explored in the Drosophila germarium through fluorescent immunohistochemistry. To enable better integration of biological data with modeling in this and similar situations, we have developed a general parameter estimation process to quantitatively optimize models with qualitative data. The process employs a modified version of the Optimal Scaling method from social and behavioral sciences, and multi-objective optimization to evaluate the trade-off between fitting different datasets (e.g. wild type vs. mutant). Using only published imaging data in the germarium, we first evaluated support for a published intracellular regulatory network by considering alternative connections of the same regulatory players. Simply screening networks against wild type data identified hundreds of feasible alternatives. Of these, five parsimonious variants were found and compared by multi-objective analysis including mutant data and dynamic constraints. With these data, the current model is supported over the alternatives, but support for a biochemically observed feedback element is weak (i.e. these data do not measure the feedback effect well). When also comparing new hypothetical models, the available data do not discriminate. To begin addressing the limitations in data, we performed a model-based experiment design and provide recommendations for experiments to refine model parameters and discriminate increasingly complex hypotheses.

Quantitative model analysis with diverse biological data: applications in developmental pattern formation.

Mathematical modeling of transcription factor and signaling networks is widely used to understand if and how a mechanism works, and to infer regulatory interactions that produce a model consistent with the observed data. Both of these approaches to modeling are informed by experimental data, however, much of the data available or even acquirable are not quantitative. Data that is not strictly quantitative cannot be used by classical, quantitative, model-based analyses that measure a difference between the measured observation and the model prediction for that observation. To bridge the model-to-data gap, a variety of techniques have been developed to measure model "fitness" and provide numerical values that can subsequently be used in model optimization or model inference studies. Here, we discuss a selection of traditional and novel techniques to transform data of varied quality and enable quantitative comparison with mathematical models. This review is intended to both inform the use of these model analysis methods, focused on parameter estimation, and to help guide the choice of method to use for a given study based on the type of data available. Applying techniques such as normalization or optimal scaling may significantly improve the utility of current biological data in model-based study and allow greater integration between disparate types of data.

Comparison of CPR outcome predictors between rhythmic abdominal compression and continuous chest compression CPR techniques.

OBJECTIVE: Bystander cardiopulmonary resuscitation (CPR) provides treatment for out-of-hospital cardiac arrest since perfusion of vital organs is critical to resuscitation. Alternatives to standard CPR are evaluated for effectiveness based upon outcome predictive metrics and survival studies. This study focuses on evaluating the performance of rhythmic-only abdominal compression CPR (OAC-CPR) relative to chest compression (CC-CPR) using a complementary suite of mechanistically based CPR outcome predictors. Combined, these predictors provide insight on the transduction of compression-induced pressures into flow perfusing vital organs. METHODS: Intrasubject comparisons between the CPR techniques were made during multiple 2-min intervals of induced fibrillation in 17 porcine subjects. Arterial pO2, cardiac output, carotid blood flow, coronary perfusion pressure (CPP), minute alveolar ventilation (MAV), end-tidal CO2, and time from defibrillation to the return of spontaneous circulation (ROSC) were recorded. Organ damage was assessed by necropsy. RESULTS: Compared with CC-CPR, OAC-CPR had higher pressure and ventilation metrics with increased relative CPP (+16 mm Hg), MAV (+75/ml/min/kg) and a lower reduction in arterial pO2(-22% baseline), but suffered from lower carotid flows (-9.3 ml/min). No significant difference was found comparing cardiac outputs. Furthermore, resuscitation was qualitatively more difficult after OAC-CPR, with a longer time to ROSC (+70 s). No abdominal damage was observed over short periods of OAC-CPR. CONCLUSIONS: Although OAC-CPR appeared superior to CC-CPR by pressure and ventilation metrics, lower carotid flow and longer delay until ROSC raise concerns about overall performance. These paradoxical observations suggest that the evaluation of efficacious alternative CPR techniques may require more direct measurements of vital organ perfusion.

Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements.

The Ras/ERK pathway drives cell proliferation and other oncogenic behaviors, and quantifying its activity in situ is of high interest in cancer diagnosis and therapy. Pathway activation is often assayed by measuring phosphorylated ERK. However, this form of measurement overlooks dynamic aspects of signaling that can only be observed over time. In this study, we combine a live, single-cell ERK biosensor approach with multiplexed immunofluorescence staining of downstream target proteins to ask how well immunostaining captures the dynamic history of ERK activity. Combining linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunostains, in which Fra-1 and pRb levels imply long term activation of ERK signaling, while Egr-1 and c-Myc indicate recent activation. We show that this framework can distinguish different classes of ERK dynamics within a heterogeneous population, providing a tool for annotating ERK dynamics within fixed tissues.

Spatiotemporal Clusters of ERK Activity Coordinate Cytokine-induced Inflammatory Responses in Human Airway Epithelial Cells.

RATIONALE: Spatially coordinated ERK signaling events ("SPREADs") transmit radially from a central point to adjacent cells via secreted ligands for EGFR and other receptors. SPREADs maintain homeostasis in non-pulmonary epithelia, but it is unknown whether they play a role in the airway epithelium or are dysregulated in inflammatory disease. OBJECTIVES: (1) To characterize spatiotemporal ERK activity in response to pro-inflammatory ligands, and (2) to assess pharmacological and metabolic regulation of cytokine-mediated SPREADs. METHODS: SPREADs were measured by live-cell ERK biosensors in human bronchial epithelial cell lines (HBE1 and 16HBE) and primary human bronchial epithelial (pHBE) cells, in both submerged and biphasic Air-Liquid Interface (ALI) culture conditions (i.e., differentiated cells). Cells were exposed to pro-inflammatory cytokines relevant to asthma and chronic obstructive pulmonary disease (COPD), and to pharmacological treatments (gefitinib, tocilizumab, hydrocortisone) and metabolic modulators (insulin, 2-deoxyglucose) to probe the airway epithelial mechanisms of SPREADs. Phospho-STAT3 immunofluorescence was used to measure localized inflammatory responses to IL-6. RESULTS: Pro-inflammatory cytokines significantly increased the frequency of SPREADs. Notably, differentiated pHBE cells display increased SPREAD frequency that coincides with airway epithelial barrier breakdown. SPREADs correlate with IL-6 peptide secretion and localized pSTAT3. Hydrocortisone, inhibitors of receptor signaling, and suppression of metabolic function decreased SPREAD occurrence. CONCLUSIONS: Pro-inflammatory cytokines modulate SPREADs in human airway epithelial cells via both secreted EGFR and IL6R ligands. SPREADs correlate with changes in epithelial barrier permeability, implying a role for spatiotemporal ERK signaling in barrier homeostasis and dysfunction during inflammation. The involvement of SPREADs in airway inflammation suggests a novel signaling mechanism that could be exploited clinically to supplement corticosteroid treatment for asthma and COPD.

Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response.

Paracrine signaling is a fundamental process regulating tissue development, repair, and pathogenesis of diseases such as cancer. Herein we describe a method for quantitatively measuring paracrine signaling dynamics, and resultant gene expression changes, in living cells using genetically encoded signaling reporters and fluorescently tagged gene loci. We discuss considerations for selecting paracrine "sender-receiver" cell pairs, appropriate reporters, the use of this system to ask diverse experimental questions and screen drugs blocking intracellular communication, data collection, and the use of computational approaches to model and interpret these experiments.

Continuous sensing of nutrients and growth factors by the mTORC1-TFEB axis.

mTORC1 senses nutrients and growth factors and phosphorylates downstream targets, including the transcription factor TFEB, to coordinate metabolic supply and demand. These functions position mTORC1 as a central controller of cellular homeostasis, but the behavior of this system in individual cells has not been well characterized. Here, we provide measurements necessary to refine quantitative models for mTORC1 as a metabolic controller. We developed a series of fluorescent protein-TFEB fusions and a multiplexed immunofluorescence approach to investigate how combinations of stimuli jointly regulate mTORC1 signaling at the single-cell level. Live imaging of individual MCF10A cells confirmed that mTORC1-TFEB signaling responds continuously to individual, sequential, or simultaneous treatment with amino acids and the growth factor insulin. Under physiologically relevant concentrations of amino acids, we observe correlated fluctuations in TFEB, AMPK, and AKT signaling that indicate continuous activity adjustments to nutrient availability. Using partial least squares regression modeling, we show that these continuous gradations are connected to protein synthesis rate via a distributed network of mTORC1 effectors, providing quantitative support for the qualitative model of mTORC1 as a homeostatic controller and clarifying its functional behavior within individual cells.

Transient phases of OXPHOS inhibitor resistance reveal underlying metabolic heterogeneity in single cells.

Cell-to-cell heterogeneity in metabolism plays an unknown role in physiology and pharmacology. To functionally characterize cellular variability in metabolism, we treated cells with inhibitors of oxidative phosphorylation (OXPHOS) and monitored their responses with live-cell reporters for ATP, ADP/ATP, or activity of the energy-sensing kinase AMPK. Across multiple OXPHOS inhibitors and cell types, we identified a subpopulation of cells resistant to activation of AMPK and reduction of ADP/ATP ratio. This resistant state persists transiently for at least several hours and can be inherited during cell divisions. OXPHOS inhibition suppresses the mTORC1 and ERK growth signaling pathways in sensitive cells, but not in resistant cells. Resistance is linked to a multi-factorial combination of increased glucose uptake, reduced protein biosynthesis, and G0/G1 cell-cycle status. Our results reveal dynamic fluctuations in cellular energetic balance and provide a basis for measuring and predicting the distribution of cellular responses to OXPHOS inhibition.

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.

Systems-Level Properties of EGFR-RAS-ERK Signaling Amplify Local Signals to Generate Dynamic Gene Expression Heterogeneity.

Intratumoral heterogeneity is associated with aggressive tumor behavior, therapy resistance, and poor patient outcomes. Such heterogeneity is thought to be dynamic, shifting over periods of minutes to hours in response to signaling inputs from the tumor microenvironment. However, models of this process have been inferred from indirect or post-hoc measurements of cell state, leaving the temporal details of signaling-driven heterogeneity undefined. Here, we developed a live-cell model system in which microenvironment-driven signaling dynamics can be directly observed and linked to variation in gene expression. Our analysis reveals that paracrine signaling between two cell types is sufficient to drive continual diversification of gene expression programs. This diversification emerges from systems-level properties of the EGFR-RAS-ERK signaling cascade, including intracellular amplification of amphiregulin-mediated paracrine signals and differential kinetic filtering by target genes including Fra-1, c-Myc, and Egr1. Our data enable more precise modeling of paracrine-driven transcriptional variation as a generator of gene expression heterogeneity. A record of this paper's transparent peer review process is included in the Supplemental Information.

Rhythmic abdominal compression CPR ventilates without supplemental breaths and provides effective blood circulation.

OBJECTIVES: Standard chest-compression CPR has an out-of-hospital resuscitation rate of less than 10% and can result in rib fractures or mouth-to-mouth transfer of infection. Recently, we introduced a new CPR method that utilizes only rhythmic abdominal compressions (OAC-CPR). The present study compares ventilation and hemodynamics produced by chest and abdominal compression CPR. METHODS: Twelve swine (29-34kg) were anesthetized, intubated and allowed to breathe spontaneously. Physiologic dead space, resting tidal volume, compression-induced lung air flow, and blood pressures were recorded. Ventricular fibrillation (VF) was electrically induced and subjects were treated with either standard CPR or OAC-CPR at various force and rate settings. Minute alveolar ventilation (MAV) and mean coronary perfusion pressure (CPP) were compared. RESULTS: For OAC-CPR, ventilation per compression tended to increase with increasing force and decreasing rate. Chest only compressions produced no MAV, while OAC-CPR at 80cycles/min or less, matched the MAV for spontaneous respiration. For all rates, abdominal compressions met, or exceeded, the CPP of chest compressions performed at 100lbs. CONCLUSIONS: OAC-CPR generated ventilatory volumes significantly greater than the dead space and produced equivalent, or larger, CPP than with chest compressions. Thus, OAC-CPR ventilates a subject, eliminating the need for mouth-to-mouth breathing, and effectively circulates blood during VF without breaking ribs. Furthermore, this technique is simple to perform, can be administered by a single rescuer, and should reduce bystander reluctance to administer CPR.

Live-Cell Imaging and Analysis with Multiple Genetically Encoded Reporters.

Genetically encoded live-cell reporters measure signaling pathway activity at the cellular level with high temporal resolution, often revealing a high degree of cell-to-cell heterogeneity. By using multiple spectrally distinct reporters within the same cell, signal transmission from one node to another within a signaling pathway can be analyzed to quantify factors such as signaling efficiency and delay. With other reporter configurations, correlation between different signaling pathways can be quantified. Such analyses can be used to establish the mechanisms and consequences of cell-to-cell heterogeneity and can inform new models of the functional properties of signaling pathways. In this unit, we describe an approach for designing and executing live-cell multiplexed reporter experiments. We also describe approaches for analyzing the resulting time-course data to quantify correlations and trends between the measured parameters at the single-cell level. © 2018 by John Wiley & Sons, Inc.

Experimental and engineering approaches to intracellular communication.

Communication between and within cells is essential for multicellular life. While intracellular signal transduction pathways are often specified in molecular terms, the information content they transmit remains poorly defined. Here, we review research efforts to merge biological experimentation with concepts of communication that emerge from the engineering disciplines of signal processing and control theory. We discuss the challenges of performing experiments that quantitate information transfer at the molecular level, and we highlight recent studies that have advanced toward a clearer definition of the information content carried by signaling molecules. Across these studies, we emphasize a theme of increasingly well-matched experimental and theoretical approaches to decode the data streams directing cellular behavior.

Linear Integration of ERK Activity Predominates over Persistence Detection in Fra-1 Regulation.

ERK signaling regulates the expression of target genes, but it is unclear how ERK activity dynamics are interpreted. Here, we investigate this question using simultaneous, live, single-cell imaging of two ERK activity reporters and expression of Fra-1, a target gene controlling epithelial cell identity. We find that Fra-1 is expressed in proportion to the amplitude and duration of ERK activity. In contrast to previous "persistence detector" and "selective filter" models in which Fra-1 expression only occurs when ERK activity persists beyond a threshold duration, our observations demonstrate that the network regulating Fra-1 expression integrates total ERK activity and responds to it linearly. However, exploration of a generalized mathematical model of the Fra-1 coherent feedforward loop demonstrates that it can perform either linear integration or persistence detection, depending on the basal mRNA production rate and protein production delays. Our data indicate that significant basal expression and short delays cause Fra-1 to respond linearly to integrated ERK activity.

Single-Cell Imaging of ERK Signaling Using Fluorescent Biosensors.

Single-cell analysis of the mitogen-activated protein kinase (MAPK) extracellular signal-regulated kinase (ERK) provides a means to perform highly detailed kinetic studies, assess heterogeneity between cells, and distinguish the subcellular localization of ERK activity. We describe here the methods needed to perform such measurements in a cell type of the investigator's choosing. We discuss the selection of appropriate reporters and provide detailed methods for stably introducing reporters, collecting live-cell data, and automatically extracting quantitative information from individual cells.

Relaxation oscillations and hierarchy of feedbacks in MAPK signaling.

We formulated a computational model for a MAPK signaling cascade downstream of the EGF receptor to investigate how interlinked positive and negative feedback loops process EGF signals into ERK pulses of constant amplitude but dose-dependent duration and frequency. A positive feedback loop involving RAS and SOS, which leads to bistability and allows for switch-like responses to inputs, is nested within a negative feedback loop that encompasses RAS and RAF, MEK, and ERK that inhibits SOS via phosphorylation. This negative feedback, operating on a longer time scale, changes switch-like behavior into oscillations having a period of 1 hour or longer. Two auxiliary negative feedback loops, from ERK to MEK and RAF, placed downstream of the positive feedback, shape the temporal ERK activity profile but are dispensable for oscillations. Thus, the positive feedback introduces a hierarchy among negative feedback loops, such that the effect of a negative feedback depends on its position with respect to the positive feedback loop. Furthermore, a combination of the fast positive feedback involving slow-diffusing membrane components with slower negative feedbacks involving faster diffusing cytoplasmic components leads to local excitation/global inhibition dynamics, which allows the MAPK cascade to transmit paracrine EGF signals into spatially non-uniform ERK activity pulses.