Temporal decoding of MAP kinase and CREB phosphorylation by selective immediate early gene expression

Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements

The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives cell proliferation, metabolism, and other processes through effector proteins including c-Myc, c-Fos, Fra-1, and Egr-1. These proteins are sensitive to the dynamics of ERK activity, but it is not clear to what extent the pattern of ERK activity in an individual cell determines effector protein expression, or how much information about ERK dynamics is embedded in the pattern of effector expression. Here, we evaluate these relationships using live-cell biosensor measurements of ERK activity, multiplexed with immunofluorescence staining for downstream target proteins of the pathway. Combining these datasets with linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunofluorescence data, wherein Fra-1 and pRb levels imply long-term activation of ERK signaling, while Egr-1 and c-Myc indicate more recent activation. Analysis of multiple cancer cell lines reveals a distorted relationship between ERK activity and cell state in malignant cells. We show that this framework can infer various classes of ERK dynamics from effector protein stains within a heterogeneous population, providing a basis for annotating ERK dynamics within fixed cells.

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.

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.

Simultaneous administration of bromodomain and histone deacetylase I inhibitors alleviates cognition deficit in Alzheimer's model of rats

BACKGROUND

Histone deacetylases (HDACs) target various genes responsible for cognitive functions. However, chromatin readers, particularly bromodomain-containing protein 4 (BRD4), are capable to change the final products of genes. The objective of this study was to evaluate the simultaneous effects of inhibition of HDACs and BRD4 on spatial and aversive memories impaired by amyloid β (Aβ) in a rat model of Alzheimer's disease (AD) considering CREB and TNF-α signaling.

METHODS

Forty male Wistar rats aged 3 months were randomly divided into five groups: saline +DMSO, Aβ+saline+DMSO, Aβ+JQ1, Aβ+MS-275, Aβ+JQ1+MS-275, and received the related treatments. MS-275, is the second generation of HDACs inhibitor, and JQ1 is a potent inhibitor of the BET family of bromodomain proteins in mammals. After the treatments, cognitive function was assessed by Morris water maze (MWM) and passive avoidance learning (PAL). The hippocampal level of mRNA for CREB and TNF-α, and also phosphorylated CREB were measured using real-time PCR and western blotting respectively.

RESULTS

Administration of JQ1 and MS-275, either separately or simultaneously, improved acquisition and retrieval of spatial and aversive memories as it was evident by decreased escape latency and increased time spent in the target quadrant (TTS) in Morris water maze (MWM), together with increase in step-through latency, but reduced time spent in the dark zone time in passive avoidance learning (PAL) compared with Aβ+saline+DMSO. Furthermore, there was a significant rise in the hippocampal level of CREB mRNA and phosphorylated CREB, but a reduction in TNF-α expression in comparison with Aβ + Saline.

CONCLUSION

Simultaneous administration of JQ1 and MS-275 improves acquisition and retrieval of both spatial and aversive memories partly via CREB and TNF-α signaling with no superiority to monotherapy.

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.

System identification of signaling dependent gene expression with different time-scale data

Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input-output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.

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.

Model-based control of the temporal patterns of intracellular signaling in silico

The functions of intracellular signal transduction systems are determined by the temporal behavior of intracellular molecules and their interactions. Of the many dynamical properties of the system, the relationship between the dynamics of upstream molecules and downstream molecules is particularly important. A useful tool in understanding this relationship is a methodology to control the dynamics of intracellular molecules with an extracellular stimulus. However, this is a difficult task because the relationship between the levels of upstream molecules and those of downstream molecules is often not only stochastic, but also time-inhomogeneous, nonlinear, and not one-to-one. In this paper, we present an easy-to-implement model-based control method that makes the target downstream molecule to trace a desired time course by changing the concentration of a controllable upstream molecule. Our method uses predictions from Monte Carlo simulations of the model to decide the strength of the stimulus, while using a particle-based approach to make inferences regarding unobservable states. We applied our method to in silico control problems of insulin-dependent AKT pathway model and EGF-dependent Akt pathway model with system noise. We show that our method can robustly control the dynamics of the intracellular molecules against unknown system noise of various strengths, even in the absence of complete knowledge of the true model of the target system.

Splicing repression allows the gradual emergence of new Alu-exons in primate evolution

Alu elements are retrotransposons that frequently form new exons during primate evolution. Here, we assess the interplay of splicing repression by hnRNPC and nonsense-mediated mRNA decay (NMD) in the quality control and evolution of new Alu-exons. We identify 3100 new Alu-exons and show that NMD more efficiently recognises transcripts with Alu-exons compared to other exons with premature termination codons. However, some Alu-exons escape NMD, especially when an adjacent intron is retained, highlighting the importance of concerted repression by splicing and NMD. We show that evolutionary progression of 3' splice sites is coupled with longer repressive uridine tracts. Once the 3' splice site at ancient Alu-exons reaches a stable phase, splicing repression by hnRNPC decreases, but the exons generally remain sensitive to NMD. We conclude that repressive motifs are strongest next to cryptic exons and that gradual weakening of these motifs contributes to the evolutionary emergence of new alternative exons.

Essential Roles for ARID1B in Dendritic Arborization and Spine Morphology of Developing Pyramidal Neurons

De novo truncating mutations in ARID1B, a chromatin-remodeling gene, cause Coffin-Siris syndrome, a developmental disorder characterized by intellectual disability and speech impairment; however, how the genetic elimination leads to cognitive dysfunction remains unknown. Thus, we investigated the neural functions of ARID1B during brain development. Here, we show that ARID1B regulates dendritic differentiation in the developing mouse brain. We knocked down ARID1B expression in mouse pyramidal neurons using in utero gene delivery methodologies. ARID1B knockdown suppressed dendritic arborization of cortical and hippocampal pyramidal neurons in mice. The abnormal development of dendrites accompanied a decrease in dendritic outgrowth into layer I. Furthermore, knockdown of ARID1B resulted in aberrant dendritic spines and synaptic transmission. Finally, ARID1B deficiency led to altered expression of c-Fos and Arc, and overexpression of these factors rescued abnormal differentiation induced by ARID1B knockdown. Our results demonstrate a novel role for ARID1B in neuronal differentiation and provide new insights into the origin of cognitive dysfunction associated with developmental intellectual disability.

SIGNIFICANCE STATEMENT

Haploinsufficiency of ARID1B, a component of chromatin remodeling complex, causes intellectual disability. However, the role of ARID1B in brain development is unknown. Here, we demonstrate that ARID1B is required for neuronal differentiation in the developing brain, such as in dendritic arborization and synapse formation. Our findings suggest that ARID1B plays a critical role in the establishment of cognitive circuitry by regulating dendritic complexity. Thus, ARID1B deficiency may cause intellectual disability via abnormal brain wiring induced by the defective differentiation of cortical neurons.

Laguerre Filter Analysis with Partial Least Square Regression Reveals a Priming Effect of ERK and CREB on c-FOS Induction

Signaling networks are made up of limited numbers of molecules and yet can code information that controls different cellular states through temporal patterns and a combination of signaling molecules. In this study, we used a data-driven modeling approach, the Laguerre filter with partial least square regression, to describe how temporal and combinatorial patterns of signaling molecules are decoded by their downstream targets. The Laguerre filter is a time series model used to represent a nonlinear system based on Volterra series expansion. Furthermore, with this approach, each component of the Volterra series expansion is expanded by Laguerre basis functions. We combined two approaches, application of a Laguerre filter and partial least squares (PLS) regression, and applied the combined approach to analysis of a signal transduction network. We applied the Laguerre filter with PLS regression to identify input and output (IO) relationships between MAP kinases and the products of immediate early genes (IEGs). We found that Laguerre filter with PLS regression performs better than Laguerre filter with ordinary regression for the reproduction of a time series of IEGs. Analysis of the nonlinear characteristics extracted using the Laguerre filter revealed a priming effect of ERK and CREB on c-FOS induction. Specifically, we found that the effects of a first pulse of ERK enhance the subsequent effects on c-FOS induction of treatment with a second pulse of ERK, a finding consistent with prior molecular biological knowledge. The variable importance of projections and output loadings in PLS regression predicted the upstream dependency of each IEG. Thus, a Laguerre filter with partial least square regression approach appears to be a powerful method to find the processing mechanism of temporal patterns and combination of signaling molecules by their downstream gene expression.

Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling

Cellular signaling processes can exhibit pronounced cell-to-cell variability in genetically identical cells. This affects how individual cells respond differentially to the same environmental stimulus. However, the origins of cell-to-cell variability in cellular signaling systems remain poorly understood. Here, we measure the dynamics of phosphorylated MEK and ERK across cell populations and quantify the levels of population heterogeneity over time using high-throughput image cytometry. We use a statistical modeling framework to show that extrinsic noise, particularly that from upstream MEK, is the dominant factor causing cell-to-cell variability in ERK phosphorylation, rather than stochasticity in the phosphorylation/dephosphorylation of ERK. We furthermore show that without extrinsic noise in the core module, variable (including noisy) signals would be faithfully reproduced downstream, but the within-module extrinsic variability distorts these signals and leads to a drastic reduction in the mutual information between incoming signal and ERK activity.

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Active MEK and ERK levels differ profoundly among genetically identical cells

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A statistical framework is developed to identify the causes of this variability

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Analysis shows that extrinsic noise upstream MEK-ERK module causes cell variability

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Within-module extrinsic variability distorts signals

Boolean Modeling Reveals the Necessity of Transcriptional Regulation for Bistability in PC12 Cell Differentiation

The nerve growth factor NGF has been shown to cause cell fate decisions toward either differentiation or proliferation depending on the relative activity of downstream pERK, pAKT, or pJNK signaling. However, how these protein signals are translated into and fed back from transcriptional activity to complete cellular differentiation over a time span of hours to days is still an open question. Comparing the time-resolved transcriptome response of NGF- or EGF-stimulated PC12 cells over 24 h in combination with protein and phenotype data we inferred a dynamic Boolean model capturing the temporal sequence of protein signaling, transcriptional response and subsequent autocrine feedback. Network topology was optimized by fitting the model to time-resolved transcriptome data under MEK, PI3K, or JNK inhibition. The integrated model confirmed the parallel use of MAPK/ERK, PI3K/AKT, and JNK/JUN for PC12 cell differentiation. Redundancy of cell signaling is demonstrated from the inhibition of the different MAPK pathways. As suggested in silico and confirmed in vitro, differentiation was substantially suppressed under JNK inhibition, yet delayed only under MEK/ERK inhibition. Most importantly, we found that positive transcriptional feedback induces bistability in the cell fate switch. De novo gene expression was necessary to activate autocrine feedback that caused Urokinase-Type Plasminogen Activator (uPA) Receptor signaling to perpetuate the MAPK activity, finally resulting in the expression of late, differentiation related genes. Thus, the cellular decision toward differentiation depends on the establishment of a transcriptome-induced positive feedback between protein signaling and gene expression thereby constituting a robust control between proliferation and differentiation.

Importance of being Nernst: Synaptic activity and functional relevance in stem cell-derived neurons

Functional synaptogenesis and network emergence are signature endpoints of neurogenesis. These behaviors provide higher-order confirmation that biochemical and cellular processes necessary for neurotransmitter release, post-synaptic detection and network propagation of neuronal activity have been properly expressed and coordinated among cells. The development of synaptic neurotransmission can therefore be considered a defining property of neurons. Although dissociated primary neuron cultures readily form functioning synapses and network behaviors in vitro, continuously cultured neurogenic cell lines have historically failed to meet these criteria. Therefore, in vitro-derived neuron models that develop synaptic transmission are critically needed for a wide array of studies, including molecular neuroscience, developmental neurogenesis, disease research and neurotoxicology. Over the last decade, neurons derived from various stem cell lines have shown varying ability to develop into functionally mature neurons. In this review, we will discuss the neurogenic potential of various stem cells populations, addressing strengths and weaknesses of each, with particular attention to the emergence of functional behaviors. We will propose methods to functionally characterize new stem cell-derived neuron (SCN) platforms to improve their reliability as physiological relevant models. Finally, we will review how synaptically active SCNs can be applied to accelerate research in a variety of areas. Ultimately, emphasizing the critical importance of synaptic activity and network responses as a marker of neuronal maturation is anticipated to result in in vitro findings that better translate to efficacious clinical treatments.

Light-mediated kinetic control reveals the temporal effect of the Raf/MEK/ERK pathway in PC12 cell neurite outgrowth

It has been proposed that differential activation kinetics allows cells to use a common set of signaling pathways to specify distinct cellular outcomes. For example, nerve growth factor (NGF) and epidermal growth factor (EGF) induce different activation kinetics of the Raf/MEK/ERK signaling pathway and result in differentiation and proliferation, respectively. However, a direct and quantitative linkage between the temporal profile of Raf/MEK/ERK activation and the cellular outputs has not been established due to a lack of means to precisely perturb its signaling kinetics. Here, we construct a light-gated protein-protein interaction system to regulate the activation pattern of the Raf/MEK/ERK signaling pathway. Light-induced activation of the Raf/MEK/ERK cascade leads to significant neurite outgrowth in rat PC12 pheochromocytoma cell lines in the absence of growth factors. Compared with NGF stimulation, light stimulation induces longer but fewer neurites. Intermittent on/off illumination reveals that cells achieve maximum neurite outgrowth if the off-time duration per cycle is shorter than 45 min. Overall, light-mediated kinetic control enables precise dissection of the temporal dimension within the intracellular signal transduction network.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Discrete signal transduction pathway utilization by a neuropeptide (PACAP) and a cytokine (TNF-alpha) first messenger in chromaffin cells, inferred from coupled transcriptome-promoter analysis of regulated gene cohorts

Cultured bovine adrenal chromaffin cells (BCCs) are employed to study first messenger-specific signaling by cytokines and neurotransmitters occurring in the adrenal medulla following immune-related stress responses. Here, we show that the cytokine TNF-alpha, and the neuropeptide transmitter PACAP, acting through the TNFR2 and PAC1 receptors, activate distinct signaling pathways, with correspondingly distinct transcriptomic signatures in chromaffin cells. We have carried out a comprehensive integrated transcriptome analysis of TNF-alpha and PACAP gene regulation in BCCs using two microarray platforms to maximize transcript identification. Microarray data were validated using qRT-PCR. More than 90% of the transcripts up-regulated either by TNF-alpha or PACAP were specific to a single first messenger. The final list of transcripts induced by each first messenger was subjected to multiple algorithms to identify promoter/enhancer response elements for trans-acting factors whose activation could account for gene expression by either TNF-alpha or PACAP. Distinct groups of transcription factors potentially controlling the expression of TNF-alpha or PACAP-responsive genes were found: most of the genes up-regulated by TNF-alpha contained transcription factor binding sites for members of the Rel transcription factor family, suggesting TNF-alpha-TNFR2 signaling occurs mainly through the NF-KB signaling pathway. Surprisingly, EGR1 was predicted to be the primary transcription factor controlling PACAP-modulated genes, suggesting PACAP signaling to the nucleus occurs predominantly through ERK, rather than CREB activation. Comparison of TNFR2-dependent versus TNFR1-dependent gene induction, and EGR1-mediated transcriptional activation, may provide a pharmacological avenue to the unique pathways activated by the first messengers TNF-alpha and PACAP in neuronal and endocrine cells.