Phosphoinositide 3-Kinase Regulates Glycolysis through Mobilization of Aldolase from the Actin Cytoskeleton.

The phosphoinositide 3-kinase (PI3K) pathway regulates multiple steps in glucose metabolism and also cytoskeletal functions, such as cell movement and attachment. Here, we show that PI3K directly coordinates glycolysis with cytoskeletal dynamics in an AKT-independent manner. Growth factors or insulin stimulate the PI3K-dependent activation of Rac, leading to disruption of the actin cytoskeleton, release of filamentous actin-bound aldolase A, and an increase in aldolase activity. Consistently, PI3K inhibitors, but not AKT, SGK, or mTOR inhibitors, cause a significant decrease in glycolysis at the step catalyzed by aldolase, while activating PIK3CA mutations have the opposite effect. These results point toward a master regulatory function of PI3K that integrates an epithelial cell's metabolism and its form, shape, and function, coordinating glycolysis with the energy-intensive dynamics of actin remodeling.

Uncovering a tumor suppressor for triple-negative breast cancers.

"Triple-negative" breast cancers are aggressive malignancies that respond poorly to treatments. Now Sun et al. (2011) find that the activity of the protein tyrosine phosphatase PTPN12 is lost in a large percentage of this breast cancer subtype, offering molecular drivers and possible therapeutic targets for this heterogeneous and intractable cancer.

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.

Frequency-modulated pulses of ERK activity transmit quantitative proliferation signals.

The EGF-stimulated ERK/MAPK pathway is a key conduit for cellular proliferation signals and a therapeutic target in many cancers. Here, we characterize two central quantitative aspects of this pathway: the mechanism by which signal strength is encoded and the response curve relating signal output to proliferation. Under steady-state conditions, we find that ERK is activated in discrete, asynchronous pulses with frequency and duration determined by extracellular concentrations of EGF spanning the physiological range. In genetically identical sister cells, cell-to-cell variability in pulse dynamics influences the decision to enter S phase. While targeted inhibition of EGFR reduces the frequency of ERK activity pulses, inhibition of MEK reduces their amplitude. Continuous response curves measured in multiple cell lines reveal that proliferation is effectively silenced only when ERK pathway output falls below a threshold of ~10%, indicating that high-dose targeting of the pathway is necessary to achieve therapeutic efficacy.

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.

Quantitative analysis of pathways controlling extrinsic apoptosis in single cells.

Apoptosis in response to TRAIL or TNF requires the activation of initiator caspases, which then activate the effector caspases that dismantle cells and cause death. However, little is known about the dynamics and regulatory logic linking initiators and effectors. Using a combination of live-cell reporters, flow cytometry, and immunoblotting, we find that initiator caspases are active during the long and variable delay that precedes mitochondrial outer membrane permeabilization (MOMP) and effector caspase activation. When combined with a mathematical model of core apoptosis pathways, experimental perturbation of regulatory links between initiator and effector caspases reveals that XIAP and proteasome-dependent degradation of effector caspases are important in restraining activity during the pre-MOMP delay. We identify conditions in which restraint is impaired, creating a physiologically indeterminate state of partial cell death with the potential to generate genomic instability. Together, these findings provide a quantitative picture of caspase regulatory networks and their failure modes.

Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis.

In microorganisms, noise in gene expression gives rise to cell-to-cell variability in protein concentrations. In mammalian cells, protein levels also vary and individual cells differ widely in their responsiveness to uniform physiological stimuli. In the case of apoptosis mediated by TRAIL (tumour necrosis factor (TNF)-related apoptosis-inducing ligand) it is common for some cells in a clonal population to die while others survive-a striking divergence in cell fate. Among cells that die, the time between TRAIL exposure and caspase activation is highly variable. Here we image sister cells expressing reporters of caspase activation and mitochondrial outer membrane permeabilization after exposure to TRAIL. We show that naturally occurring differences in the levels or states of proteins regulating receptor-mediated apoptosis are the primary causes of cell-to-cell variability in the timing and probability of death in human cell lines. Protein state is transmitted from mother to daughter, giving rise to transient heritability in fate, but protein synthesis promotes rapid divergence so that sister cells soon become no more similar to each other than pairs of cells chosen at random. Our results have implications for understanding 'fractional killing' of tumour cells after exposure to chemotherapy, and for variability in mammalian signal transduction in general.

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.

Applications of Plant-Made Fibroblast Growth Factor for Human Pluripotent Stem Cells.

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs) hold great potential in regenerative medicine. These cells can be expanded indefinitely in theory and are able to differentiate into different types of cells for cell therapies, drug screening, and basic biology studies. The reliable and effective propagation of hESCs and hiPSCs is important for their downstream applications. Basic fibroblast growth factor (bFGF) is critical to hESCs and hiPSCs for maintaining their pluripotency. Plant-produced growth factors are safe to use without potential contamination of infectious viruses and are less expensive to produce. In this study, we used rice cell-made basic fibroblast growth factor (RbFGF) to propagate hESCs and hiPSCs for at least eight passages. Both hESCs and hiPSCs cultured with RbFGF not only maintained the morphology but also the specific expression (OCT4, SSEA4, SOX2, and TRA-1-60) of PSCs, similar to those cultured with the commercial Escherichia coli-produced bFGF. Furthermore, both gene chip-based PluriTest and TaqMan hPSC Scorecard pluripotency analysis demonstrated the pluripotent expression profile of the hESCs cultured with RbFGF. In vitro trilineage assays further showed that these hESCs and hiPSCs cultured on RbFGF were capable of giving rise to cell derivatives of ectoderm, mesoderm, and endoderm, further demonstrating their pluripotency. Finally, chromosome stability was also maintained in hESCs cultured with RbFGF as demonstrated by normal karyotypes. This study suggests broad applications for plant-made growth factors in stem cell culture and regenerative medicine.

Modeling elucidates context dependence in adipose regulation.

Single-cell data and computational simulations reveal the dynamics of the transcription factors HIF1α and PPARγ during adipocyte differentiation and maturation. Modeling feedback within this network predicts a HIF1α-mediated choice between lipid accumulation and incomplete differentiation. In vitro experiments support this model, with implications for adipose dynamics in metabolic disorders involving hypoxia.

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.

ERK signaling dynamics: Lights, camera, transduction.

Three-dimensional mammary epithelial acini are a model for understanding how microenvironment-driven signaling coordinates cell behavior and tissue morphogenesis. In this issue of Developmental Cell, Ender et al. use live-cell imaging to capture dynamic spatiotemporal patterns of ERK activity that instruct cell migration and survival fates in developing acini.

Modeling a snap-action, variable-delay switch controlling extrinsic cell death.

When exposed to tumor necrosis factor (TNF) or TNF-related apoptosis-inducing ligand (TRAIL), a closely related death ligand and investigational therapeutic, cells enter a protracted period of variable duration in which only upstream initiator caspases are active. A subsequent and sudden transition marks activation of the downstream effector caspases that rapidly dismantle the cell. Thus, extrinsic apoptosis is controlled by an unusual variable-delay, snap-action switch that enforces an unambiguous choice between life and death. To understand how the extrinsic apoptosis switch functions in quantitative terms, we constructed a mathematical model based on a mass-action representation of known reaction pathways. The model was trained against experimental data obtained by live-cell imaging, flow cytometry, and immunoblotting of cells perturbed by protein depletion and overexpression. The trained model accurately reproduces the behavior of normal and perturbed cells exposed to TRAIL, making it possible to study switching mechanisms in detail. Model analysis shows, and experiments confirm, that the duration of the delay prior to effector caspase activation is determined by initiator caspase-8 activity and the rates of other reactions lying immediately downstream of the TRAIL receptor. Sudden activation of effector caspases is achieved downstream by reactions involved in permeabilization of the mitochondrial membrane and relocalization of proteins such as Smac. We find that the pattern of interactions among Bcl-2 family members, the partitioning of Smac from its binding partner XIAP, and the mechanics of pore assembly are all critical for snap-action control.

Entosis is induced by ultraviolet radiation.

Entosis is a cell death mechanism that is executed through neighbor cell ingestion and killing that occurs in cancer tissues and during development. Here, we identify JNK and p38 stress-activated kinase signaling as an inducer of entosis in cells exposed to ultraviolet (UV) radiation. Cells with high levels of stress signaling are ingested and killed by those with low levels, a result of heterogeneity arising within cell populations over time. In stressed cells, entosis occurs as part of mixed-cell death response with parallel induction of apoptosis and necrosis, and we find that inhibition of one form of cell death leads to increased rates of another. Together, these findings identify stress-activated kinase signaling as a new inducer of entosis and demonstrate cross talk between different forms of cell death that can occur in parallel in response to UV radiation.

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.

Systematic calibration of a cell signaling network model.

BACKGROUND: Mathematical modeling is being applied to increasingly complex biological systems and datasets; however, the process of analyzing and calibrating against experimental data is often challenging and a rate limiting step in model development. To address this problem, we developed a systematic methodology for calibrating quantitative models of dynamic biological processes and illustrate its utility by validating a model of TRAIL (Tumor necrosis factor Related Apoptosis-Inducing Ligand)-induced cell death. RESULTS: We propose a serial framework integrating analysis and calibration modules and we compare various methods for global sensitivity analysis and global parameter estimation. First, adequacy of the network structure is checked by global sensitivity analysis to changes in concentrations of molecular species, validating that the model can reproduce qualitative features of the system behavior derived from experiments or literature surveys. Second, rate parameters are ranked by importance using gradient-based and variance-based sensitivity indices, and we systematically determine the optimal number of parameters to include in model calibration. Third, deterministic, stochastic and hybrid algorithms for global optimization are applied to estimate the values of the most important parameters by fitting to time series data. We compare the performance of these three optimization algorithms. CONCLUSIONS: Our proposed framework covers the entire process from validating a proto-model to establishing a realistic model for in silico experiments and thereby provides a generalized workflow for the construction of predictive models of complex network systems.

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.

Combining Microbial Culturing With Mathematical Modeling in an Introductory Course-Based Undergraduate Research Experience.

Quantitative techniques are a critical part of contemporary biology research, but students interested in biology enter college with widely varying quantitative skills and attitudes toward mathematics. Course-based undergraduate research experiences (CUREs) may be an early way to build student competency and positive attitudes. Here we describe the design, implementation, and assessment of an introductory quantitative CURE focused on halophilic microbes. In this CURE, students culture and isolate halophilic microbes from environmental and food samples, perform growth assays, then use mathematical modeling to quantify the growth rate of strains in different salinities. To assess how the course may impact students' future academic plans and attitudes toward the use of math in biology, we used pre- and post-quarter surveys. Students who completed the course showed more positive attitudes toward science learning and an increased interest in pursuing additional quantitative biology experiences. We argue that the classroom application of microbiology methods, combined with mathematical modeling using student-generated data, provides a degree of student ownership, collaboration, iteration, and discovery that makes quantitative learning both relevant and exciting to students.