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ERK signal duration decoding by mRNA dynamics
Abstract
Der RAF-MEK-ERK-Signalweg steuert grundlegende, oftmals entgegengesetzte zelluläre Prozesse wie die Proliferation und Apoptose von Zellen. Die Dauer des vermittelten Signals wurde als entscheidener Faktor für die Steuerung dieser Prozesse identifiziert. Es ist jedoch nicht eindeutig geklärt, wie die verschiedenen früh und spät reagierenden Genexpressionsmodule kurze und lange Signale unterscheiden können und durch welche kinetischen Merkmale ihre Antwortzeit bestimmt wird. In der vorliegenden Arbeit wurden sowohl Proteinphosphorylierungsdaten als auch Genexpressionsdaten aus HEK293-Zellen gewonnen, die ein induzierbares Konstrukt des Proto-Onkogens RAF tragen. Hierbei wurde ein neues Genexpressionsmodul identifiziert, dass sich aus sofort induzierten aber spät antwortenden Genen zusammensetzt. Es unterscheidet sich in der Genexpressionsdynamik und Genfunktion von anderen Modulen, und wurde mit Hilfe mathematischer Modellierung experimenteller Daten identifiziert. Es wurde festgestellt, dass diese Gene aufgrund von langen Halbwertszeiten der vermitteltenden mRNA in der Lage sind spät auf das eingehende Signal zu reagieren und die Dauer des Signals in die Amplitude der Genantwort zu übersetzen. Trotz der langsamen Akkumulation und damit späten Antwortzeit, konnte aufgrund einer GC-reichen Promoterstruktur zunächst vermutet und mit Hilfe eines Markerverfahrens bestätigt werden, dass die Transkription dieser Gene instantan mit Beginn der ERK-Aktivierung startet. Eine vergleichende Analyse zeigte, dass das Prinzip der Signaldauer-Entschlüsselung in PC12-Zellen und MCF7-Zellen, zwei paradigmatischen Zellsystemen für die ERK-Signaldauer, konserviert ist. Insgesamt deuten die Ergebnisse der Untersuchung darauf hin, dass das neu identifizierte Genexpressionsmodul der Entschlüsselung der ERK-Signaldauer dient und das mRNA Halbwertszeiten sowohl hierfür, als auch für die zeitliche Abfolge der Genantwort eine entscheidende Rolle spielen.
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Global quantification of total RNA is used to investigate steady state levels of gene expression. However, being able to differentiate pre-existing RNA (that has been synthesized prior to a defined point in time) and newly transcribed RNA can provide invaluable information e.g. to estimate RNA half-lives or identify fast and complex regulatory processes. Recently, new techniques based on metabolic labeling and RNA-seq have emerged that allow to quantify new and old RNA: Nucleoside analogs are incorporated into newly transcribed RNA and are made detectable as point mutations in mapped reads. However, relatively infrequent incorporation events and significant sequencing error rates make the differentiation between old and new RNA a highly challenging task. We developed a statistical approach termed GRAND-SLAM that, for the first time, allows to estimate the proportion of old and new RNA in such an experiment. Uncertainty in the estimates is quantified in a Bayesian framework. Simulation experiments show our approach to be unbiased and highly accurate. Furthermore, we analyze how uncertainty in the proportion translates into uncertainty in estimating RNA half-lives and give guidelines for planning experiments. Finally, we demonstrate that our estimates of RNA half-lives compare favorably to other experimental approaches and that biological processes affecting RNA half-lives can be investigated with greater power than offered by any other method. GRAND-SLAM is freely available for non-commercial use at http://software.erhard-lab.de; R scripts to generate all figures are available at zenodo (doi: 10.5281/zenodo.1162340).
RNA sequencing (RNA-seq) offers a snapshot of cellular RNA populations, but not temporal information about the sequenced RNA. Here we report TimeLapse-seq, which uses oxidative-nucleophilic-aromatic substitution to convert 4-thiouridine into cytidine analogs, yielding apparent U-to-C mutations that mark new transcripts upon sequencing. TimeLapse-seq is a single-molecule approach that is adaptable to many applications and reveals RNA dynamics and induced differential expression concealed in traditional RNA-seq.
The turnover of the RNA molecules is determined by the rates of transcription and RNA degradation. Several methods have been developed to study RNA turnover since the beginnings of molecular biology. Here we summarize the main methods to measure RNA half-life: transcription inhibition, gene control, and metabolic labelling. These methods were used to detect the cellular activity of the mRNAs degradation machinery, including the exo-ribonuclease Xrn1 and the exosome. On the other hand, the study of the differential stability of mature RNAs has been hampered by the fact that different methods have often yielded inconsistent results. Recent advances in the systematic comparison of different method variants in yeast have permitted the identification of the least invasive methodologies that reflect half-lives the most faithfully, which is expected to open the way for a consistent quantitative analysis of the determinants of mRNA stability.
This study in the history and philosophy of science is concerned with the role of metaphors in the creation of scientific concepts, theories, and explanations. It treats the history of key metaphors that have informed cell theory and the experimental, philosophical and social circumstances under which they have emerged, risen in popularity, and in some cases faded from view. It should be of special interest to historians and philosophers of science, science studies, cell biologists, and science education.
The book’s objectives are fourfold: (i) to provide a history of some of the key metaphors in cell theory and cell biology, ranging from the 17th century to the present (Chs. 1-4); (ii) to provide a philosophical account of the cognitive work these metaphors have done in several important areas of cell biology (chiefly anatomy, physiology, developmental biology, and cell communication and signaling) (Chs. 1-4); (iii) to provide a philosophical account of the value of metaphor in science that is critically self-aware of the type of meta-metaphors commonly used to talk about how metaphors work in science, e.g. metaphors provide a ‘lens’ through which to ‘see’ a subject, or metaphors are ‘cognitive tools or instruments’ (Ch. 5); and (iv) to draw out the implications of science’s reliance upon metaphor for a philosophical account of scientific theory, explanation, understanding, and the scientific realism question (Ch. 6).
The central argument of the book is that close attention to the history and current practice of cell biology reveals that metaphor is an essential component of scientific investigation. Metaphors are not simply rhetorical façons de parler used by scientists when talking to lay audiences or for pedagogical purposes. They are central and constitutive to how scientists understand biology at the cellular and molecular levels and to the explanations they create of how cells and molecules function. Over time and with regular use, however, some novel metaphors become ‘dead’ metaphors. As many of the originally surprising connotations are stripped away or forgotten, the once metaphorical term comes to represent what is now generally and literally understood by the scientific community. The term ‘cell’ is just one instructive example. In some cases it is unclear whether a term is used metaphorically or literally. The porous or dynamic nature of the ‘literal-metaphorical’ distinction necessitates a more pragmatic, practice-oriented, and less literal interpretation of the scientific realism thesis, as is articulated and defended in this book.
Gene expression profiling by high-throughput sequencing reveals qualitative and quantitative changes in RNA species at steady state but obscures the intracellular dynamics of RNA transcription, processing and decay. We developed thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM seq), an orthogonal-chemistry-based RNA sequencing technology that detects 4-thiouridine (s4U) incorporation in RNA species at single-nucleotide resolution. In combination with well-established metabolic RNA labeling protocols and coupled to standard, low-input, high-throughput RNA sequencing methods, SLAM seq enabled rapid access to RNA-polymerase-II-dependent gene expression dynamics in the context of total RNA. We validated the method in mouse embryonic stem cells by showing that the RNA-polymerase-II-dependent transcriptional output scaled with Oct4/Sox2/Nanog-defined enhancer activity, and we provide quantitative and mechanistic evidence for transcript-specific RNA turnover mediated by post-transcriptional gene regulatory pathways initiated by microRNAs and N6-methyladenosine. SLAM seq facilitates the dissection of fundamental mechanisms that control gene expression in an accessible, cost-effective and scalable manner.
Single-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled resolution in the measurement of the abundance and localization of nascent and mature RNA transcripts in fixed, single cells. We developed a computational pipeline (BayFish) to infer the kinetic parameters of gene expression from smFISH data at multiple time points after gene induction. Given an underlying model of gene expression, BayFish uses a Monte Carlo method to estimate the Bayesian posterior probability of the model parameters and quantify the parameter uncertainty given the observed smFISH data. We tested BayFish on synthetic data and smFISH measurements of the neuronal activity-inducible gene Npas4 in primary neurons.
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The online version of this article (doi:10.1186/s13059-017-1297-9) contains supplementary material, which is available to authorized users.
An outstanding question is how receptor tyrosine kinases (RTKs) determine different cell-fate decisions despite sharing the same signalling cascades. Here, we uncovered an unexpected mechanism of RTK trafficking in this process. By quantitative high-resolution FRET microscopy, we found that phosphorylated epidermal growth factor receptor (p-EGFR) is not randomly distributed but packaged at constant mean amounts in endosomes. Cells respond to higher EGF concentrations by increasing the number of endosomes but keeping the mean p-EGFR content per endosome almost constant. By mathematical modelling, we found that this mechanism confers both robustness and regulation to signalling output. Different growth factors caused specific changes in endosome number and size in various cell systems and changing the distribution of p-EGFR between endosomes was sufficient to reprogram cell-fate decision upon EGF stimulation. We propose that the packaging of p-RTKs in endosomes is a general mechanism to ensure the fidelity and specificity of the signalling response.
Personalised medicine is widely considered as the way of the future for medicine. However, progress in cancer, with a few outstanding exceptions, has fallen below expectations because of the challenges of tumour heterogeneity and clonal evolution. In both benign and malignant disease, diseases caused by single genetic alterations are more amenable to precision medicine approaches. However, most common diseases are caused by a complex interplay of multiple genetic and environmental factors making personalised medicine far more challenging. The current optimism for personalised medicine is distorting clinical consultations, resource allocation and research funding prioritisation. A research active clinician must act both as an agent of change and development, and as a communicator of realism. Thus personalised medicine that includes a sober appreciation of what genomics can achieve, together with continued focus on the individual as a person not just as a genome, will contribute to further improvements in health and healthcare.
The RAF‐MEK‐ERK signalling pathway controls fundamental, often opposing cellular processes such as proliferation and apoptosis. Signal duration has been identified to play a decisive role in these cell fate decisions. However, it remains unclear how the different early and late responding gene expression modules can discriminate short and long signals. We obtained both protein phosphorylation and gene expression time course data from HEK293 cells carrying an inducible construct of the proto‐oncogene RAF. By mathematical modelling, we identified a new gene expression module of immediate–late genes (ILGs) distinct in gene expression dynamics and function. We find that mRNA longevity enables these ILGs to respond late and thus translate ERK signal duration into response amplitude. Despite their late response, their GC‐rich promoter structure suggested and metabolic labelling with 4SU confirmed that transcription of ILGs is induced immediately. A comparative analysis shows that the principle of duration decoding is conserved in PC12 cells and MCF7 cells, two paradigm cell systems for ERK signal duration. Altogether, our findings suggest that ILGs function as a gene expression module to decode ERK signal duration.
The extracellular signal-regulated kinase 1/2 (ERK1/2) mitogen-activated protein kinase (MAPK) signalling pathway regulates many cellular functions, including proliferation, differentiation, and transformation. To reliably convert external stimuli into specific cellular responses and to adapt to environmental circumstances, the pathway must be integrated into the overall signalling activity of the cell. Multiple mechanisms have evolved to perform this role. In this review, we will focus on negative feedback mechanisms and examine how they shape ERK1/2 MAPK signalling. We will first discuss the extensive number of negative feedback loops targeting the different components of the ERK1/2 MAPK cascade, specifically the direct posttranslational modification of pathway components by downstream protein kinases and the induction of de novo gene synthesis of specific pathway inhibitors. We will then evaluate how negative feedback modulates the spatiotemporal signalling dynamics of the ERK1/2 pathway regarding signalling amplitude and duration as well as subcellular localisation. Aberrant ERK1/2 activation results in deregulated proliferation and malignant transformation in model systems and is commonly observed in human tumours. Inhibition of the ERK1/2 pathway thus represents an attractive target for the treatment of malignant tumours with increased ERK1/2 activity. We will, therefore, discuss the effect of ERK1/2 MAPK feedback regulation on cancer treatment and how it contributes to reduced clinical efficacy of therapeutic agents and the development of drug resistance.
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.
The transcription factor p53 responds to DNA double-strand breaks by increasing in concentration in a series of pulses of fixed amplitude, duration, and period. How p53 pulses influence the dynamics of p53 target gene expression is not understood. Here, we show that, in bulk cell populations, patterns of p53 target gene expression cluster into groups with stereotyped temporal behaviors, including pulsing and rising dynamics. These behaviors correlate statistically with the mRNA decay rates of target genes: short mRNA half-lives produce pulses of gene expression. This relationship can be recapitulated by mathematical models of p53-dependent gene expression in single cells and cell populations. Single-cell transcriptional profiling demonstrates that expression of a subset of p53 target genes is coordinated across time within single cells; p53 pulsing attenuates this coordination. These results help delineate how p53 orchestrates the complex DNA damage response and give insight into the function of pulsatile signaling pathways.
The regulation of miRNAs is critical to the definition of cell identity and behavior in normal physiology and disease. To date, the dynamics of miRNA degradation and the mechanisms involved in remain largely obscure, in particular, in higher organisms. Here, we developed a pulse-chase approach based on metabolic RNA labeling to calculate miRNA decay rates at genome-wide scale in mammalian cells. Our analysis revealed heterogeneous miRNA half-lives, with many species behaving as stable molecules (T1/2>24h), while others, including passenger miRNAs and a number (25/129) of guide miRNAs, are quickly turned over (T1/2=4-14h). Decay rates were coupled with other features, including genomic organization, transcription rates, structural heterogeneity (IsomiRs) and target abundance, measured through quantitative experimental approaches. This comprehensive analysis highlighted functional mechanisms that mediate miRNA degradation, as well as the importance of decay dynamics in the regulation of the miRNA pool under both steady state conditions and during cell transitions.
Targeted therapies within the RAS/RAF/MEK/ERK signalling axis become increasingly popular, yet cross-talk and feedbacks in the signalling network lead to unexpected effects. Here we look systematically into how inhibiting RAF and MEK with clinically relevant inhibitors result in changes in PI3K/AKT activation. We measure the signalling response using a bead-based ELISA, and use a panel of three cell lines, and isogenic cell lines that express mutant forms of the oncogenes KRAS and BRAF to interrogate the effects of the MEK and RAF inhibitors on signalling. We find that treatment with the RAF inhibitors have opposing effects on AKT phosphorylation depending on the mutational status of two important oncogenes, KRAS and BRAF. If these two genes are in wildtype configuration, RAF inhibitors reduce AKT phosphorylation. In contrast, if BRAF or KRAS are mutant, RAF inhibitors will leave AKT phosphorylation unaffected or lead to an increase of AKT phosphorylation. Down-regulation of phospho-AKT by RAF inhibitors also extends to downstream transcription factors, and correlates with apoptosis induction. Our results show that oncogenes rewire signalling such that targeted therapies can have opposing effects on parallel pathways, which depend on the mutational status of the cell.
Dual-specificity MAP kinase (MAPK) phosphatases (MKPs or DUSPs) are well-established negative regulators of MAPK signalling in mammalian cells and tissues. By virtue of their differential subcellular localisation and ability to specifically recognise, dephosphorylate and inactivate different MAPK isoforms, they are key spatiotemporal regulators of pathway activity. Furthermore, as they are transcriptionally regulated as downstream targets of MAPK signalling they can either act as classical negative feedback regulators or mediate cross talk between distinct MAPK pathways. Because MAPKs and particularly Ras/ERK signalling are implicated in cancer initiation and development, the observation that MKPs are abnormally regulated in human tumours has been interpreted as evidence that these enzymes can either suppress or promote carcinogenesis. However, definitive evidence of such roles has been lacking. Here we review recent studies based on the use of mouse models, biochemical studies and clinical data that demonstrate key roles for MKPs in modulating the oncogenic potential of Ras/ERK signalling and also indicate that these enzymes may play a role in the response of tumours to certain anticancer drugs. Overall, this work reinforces the importance of negative regulatory mechanisms in modulating the activity of oncogenic MAPK signalling and indicates that MKPs may provide novel targets for therapeutic intervention in cancer.
Transient versus sustained ERK MAP kinase (MAPK) activation dynamics induce proliferation versus differentiation in response to epidermal (EGF) or nerve (NGF) growth factors in PC-12 cells. Duration of ERK activation has therefore been proposed to specify cell fate decisions. Using a biosensor to measure ERK activation dynamics in single living cells reveals that sustained EGF/NGF application leads to a heterogeneous mix of transient and sustained ERK activation dynamics in distinct cells of the population, different than the population average. EGF biases toward transient, while NGF biases toward sustained ERK activation responses. In contrast, pulsed growth factor application can repeatedly and homogeneously trigger ERK activity transients across the cell population. These datasets enable mathematical modeling to reveal salient features inherent to the MAPK network. Ultimately, this predicts pulsed growth factor stimulation regimes that can bypass the typical feedback activation to rewire the system toward cell differentiation irrespective of growth factor identity.
Cancer is often considered a genetic disease. However, much of the enormous plasticity of cancer cells to evolve different phenotypes, to adapt to challenging microenvironments and to withstand therapeutic assaults is encoded by the structure and spatiotemporal dynamics of signal transduction networks. In this Review, we discuss recent concepts concerning how the rich signalling dynamics afforded by these networks are regulated and how they impinge on cancer cell proliferation, survival, invasiveness and drug resistance. Understanding this dynamic circuitry by mathematical modelling could pave the way to new therapeutic approaches and personalized treatments.
The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset.
Cells employ a plethora of signaling pathways to make their life-and-death decisions. Extensive genetic, biochemical, and physiological studies have led to the accumulation of knowledge about signaling components and their interactions within signaling networks. These conventional approaches, although useful, lack the ability to control the spatial and temporal aspects of signaling processes. The recently emerged optogenetic tools open exciting opportunities by enabling signaling regulation with superior temporal and spatial resolution, easy delivery, rapid reversibility, fewer off-target side effects, and the ability to dissect complex signaling networks. Here we review recent achievements in using light to control intracellular signaling pathways and discuss future prospects for the field, including integration of new genetic approaches into optogenetics.
Copyright © 2014 Elsevier Ltd. All rights reserved.
Cells control dynamic transitions in transcript levels by regulating transcription, processing, and/or degradation through an integrated regulatory strategy. Here, we combine RNA metabolic labeling, rRNA-depleted RNA-seq, and DRiLL, a novel computational framework, to quantify the level; editing sites; and transcription, processing, and degradation rates of each transcript at a splice junction resolution during the LPS response of mouse dendritic cells. Four key regulatory strategies, dominated by RNA transcription changes, generate most temporal gene expression patterns. Noncanonical strategies that also employ dynamic posttranscriptional regulation control only a minority of genes, but provide unique signal processing features. We validate Tristetraprolin (TTP) as a major regulator of RNA degradation in one noncanonical strategy. Applying DRiLL to the regulation of noncoding RNAs and to zebrafish embryogenesis demonstrates its broad utility. Our study provides a new quantitative approach to discover transcriptional and posttranscriptional events that control dynamic changes in transcript levels using RNA sequencing data.
Copyright © 2014 Elsevier Inc. All rights reserved.
ERK (extracellular signal-regulated kinase) plays a central role in signal transduction networks and cell fate decisions. Sustained ERK activation induces cell differentiation while transient ERK results in proliferation of several types of cells. Sustained ERK activity stabilizes proteins of early response gene products. However, the effect of ERK activity duration on mRNA stability is unknown. We analyzed the quantitative relationship between duration of four ERK activity kinetics and mRNA expression profile in growth factors treated cells. Time-course transcriptome analysis revealed that the cells with prolonged ERK activity generally show sustained mRNA expression of late response genes, but not early- or mid-genes. Selected late response genes decayed more rapidly in the presence of a specific ERK inhibitor than a general transcription inhibitor and the decay rate was not related to the number of AU-rich elements. Our results suggest that sustained ERK activity plays an important role in lifespan of the mRNA encoded by late response genes, in addition to previously demonstrated role in protein stabilization of early response genes including transcription factors regulating transcription of mid- and late-genes. This double positive regulation of ligand-induced genes, also called feedforward regulation, is critical in cell fate decisions. This article is protected by copyright. All rights reserved.
This article is protected by copyright. All rights reserved.
The RAS-RAF-MEK-ERK signalling pathway is hyperactivated in a high percentage of tumours, most frequently owing to activating mutations of the KRAS, NRAS and BRAF genes. Recently, the use of compounds targeting components of ERK signalling, such as RAF or MEK inhibitors, has led to substantial improvement in clinical outcome in metastatic melanoma and has shown promising clinical activity in additional tumour types. However, response rates are highly variable and the efficacy of these drugs is primarily limited by the development of resistance. Both intrinsic and acquired resistance to RAF and MEK inhibitors are frequently associated with the persistence of ERK signalling in the presence of the drug, implying the need for more innovative approaches to target the pathway.
The Erk mitogen-activated protein kinase plays diverse roles in animal development. Its widespread reuse raises a conundrum: when a single kinase like Erk is activated, how does a developing cell know which fate to adopt? We combine optogenetic control with genetic perturbations to dissect Erk-dependent fates in the early Drosophila embryo. We find that Erk activity is sufficient to “posteriorize” 88% of the embryo, inducing gut endoderm-like gene expression and morphogenetic movements in all cells within this region. Gut endoderm fate adoption requires at least 1 h of signaling, whereas a 30-min Erk pulse specifies a distinct ectodermal cell type, intermediate neuroblasts. We find that the endoderm-ectoderm cell fate switch is controlled by the cumulative load of Erk activity, not the duration of a single pulse. The fly embryo thus harbors a classic example of dynamic control, where the temporal profile of Erk signaling selects between distinct physiological outcomes.
Dynamics of cell signaling and decoding
Defects in cellular signaling pathways, like those in some cancer cells, are often thought to result in increased or decreased steady-state signals that promote or inhibit cell proliferation. But Bugaj et al. show that dynamic changes in the duration or frequency of a signal can also alter cellular responses (see the Perspective by Kolch and Kiel). They took precise control of signaling in cultured human or mouse cells with a light-controlled mechanism for activating and inactivating the guanosine triphosphate Ras. Known cancer mutations in components of the Ras-activated signaling pathway or inhibitors of particular pathway components altered signal timing and readouts. The modified dynamics changed transcriptional outcomes and could inappropriately support cell proliferation. The ability to probe responses of signaling networks in this way may enhance understanding of biological regulation and reveal new therapeutic targets.
Science , this issue p. eaao3048 ; see also p. 844
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.
Cell signaling networks coordinate specific patterns of protein expression in response to external cues, yet the logic by which signaling pathway activity determines the eventual abundance of target proteins is complex and poorly understood. Here, we describe an approach for simultaneously controlling the Ras/Erk pathway and monitoring a target gene's transcription and protein accumulation in single live cells. We apply our approach to dissect how Erk activity is decoded by immediate early genes (IEGs). We find that IEG transcription decodes Erk dynamics through a shared band-pass filtering circuit; repeated Erk pulses transcribe IEGs more efficiently than sustained Erk inputs. However, despite highly similar transcriptional responses, each IEG exhibits dramatically different protein-level accumulation, demonstrating a high degree of post-transcriptional regulation by combinations of multiple pathways. Our results demonstrate that the Ras/Erk pathway is decoded by both dynamic filters and logic gates to shape target gene responses in a context-specific manner.
The RAF-MEK-ERK cascade is one of the most studied signaling pathways as it controls many vital cellular programs. There has been an immense amount of effort to determine ERK target proteins that are involved in regulating these programs. Classical biochemical and genetic approaches have identified hundreds of direct ERK substrates, and with the advent of phospho-proteomic technologies, numerous studies have expanded the number of ERK target proteins. Here, we compile a comprehensive ERK target phospho-site archive in which we gathered information from various research studies in a database to form a searchable compendium of ERK targets. This article is protected by copyright. All rights reserved.
Combinatorial control of gene expression is presumed to be mediated by molecular interactions between coincident transcription factors (TFs). While information on the genome-wide locations of TFs is available, the genes they regulate and whether they function combinatorially often remain open questions. Here, we developed a mechanistic, rather than statistical, modeling approach to elucidate TF control logic from gene expression data. Applying this approach to hundreds of genes in 85 datasets measuring the transcriptional responses of murine fibroblasts and macrophages to cytokines and pathogens, we found that stimulus-responsive TFs generally function sequentially in logical OR gates or singly. Logical AND gates were found between NF-κB-responsive mRNA synthesis and MAPKp38-responsive control of mRNA half-life, but not between temporally coincident TFs. Our analyses identified the functional target genes of each of the pathogen-responsive TFs and prompt a revision of the conceptual underpinnings of combinatorial control of gene expression to include sequentially acting molecular mechanisms that govern mRNA synthesis and decay.
Design of small molecules that disrupt protein-protein interactions, including the interaction of RAS proteins and their effectors, may provide chemical probes and therapeutic agents. We describe here the synthesis and testing of potential small-molecule pan-RAS ligands, which were designed to interact with adjacent sites on the surface of oncogenic KRAS. One compound, termed 3144, was found to bind to RAS proteins using microscale thermophoresis, nuclear magnetic resonance spectroscopy, and isothermal titration calorimetry and to exhibit lethality in cells partially dependent on expression of RAS proteins. This compound was metabolically stable in liver microsomes and displayed anti-tumor activity in xenograft mouse cancer models. These findings suggest that pan-RAS inhibition may be an effective therapeutic strategy for some cancers and that structure-based design of small molecules targeting multiple adjacent sites to create multivalent inhibitors may be effective for some proteins.
An important step toward understanding gene regulation is the elucidation of the time necessary for the completion of individual steps. Measurement of reaction rates can reveal potential nodes for regulation. For example, measurements of in vivo transcription elongation rates reveal regulation by DNA sequence, gene architecture, and chromatin. Pre‐ mRNA splicing is regulated by transcription elongation rates and vice versa, yet the rates of RNA processing reactions remain largely elusive. Since the 1980s, numerous model systems and approaches have been used to determine the precise timing of splicing in vivo . Because splicing can be co‐transcriptional, the position of Pol II when splicing is detected has been used as a proxy for time by some investigators. In addition to these ‘distance‐based’ measurements, ‘time‐based’ measurements have been possible through live cell imaging, metabolic labeling of RNA , and gene induction. Yet splicing rates can be convolved by the time it takes for transcription, spliceosome assembly and spliceosome disassembly. The variety of assays and systems used has, perhaps not surprisingly, led to reports of widely differing splicing rates in vivo . Recently, single molecule RNA ‐seq has indicated that splicing occurs more quickly than previously deduced. Here we comprehensively review these findings and discuss evidence that splicing and transcription rates are closely coordinated, facilitating the efficiency of gene expression. On the other hand, introduction of splicing delays through as yet unknown mechanisms provide opportunity for regulation. More work is needed to understand how cells optimize the rates of gene expression for a range of biological conditions. WIREs RNA 2017, 8:e1401. doi: 10.1002/wrna.1401
This article is categorized under: RNA-Based Catalysis > RNA Catalysis in Splicing and Translation
RNA Interactions with Proteins and Other Molecules > RNA–Protein Complexes
RNA Processing > Splicing Mechanisms
TT-Seq maps a transient transcriptome
RNA expression is related to protein abundance and cellular function. However, the amounts of RNA generated at any one time-point have been difficult to determine. Schwalb et al. developed a method, transient transcriptome sequencing (TT-Seq), to collect and sequence all RNA segments synthesized over 5 minutes. Because 5 minutes is not long enough to fully degrade even the most transient RNA, this method can detect the synthesis of most RNA without bias. Applying this method to human K562 cells, TT-Seq detected thousands of noncoding transcripts, providing a snapshot of RNA synthesis rates and RNA half-lives, and full-length maps of short-lived RNAs such as enhancers and short intergenic noncoding RNAs.
Science , this issue p. 1225
Melanomas on sun-exposed skin are heterogeneous tumours, which can be subtyped on the basis of their cumulative levels of exposure to ultraviolet (UV) radiation. A melanocytic neoplasm can also be staged by how far it has progressed, ranging from a benign neoplasm, such as a naevus, to a malignant neoplasm, such as a metastatic melanoma. Each subtype of melanoma can evolve through distinct evolutionary trajectories, passing through (or sometimes skipping over) various stages of transformation. This Review delineates several of the more common progression trajectories that occur in the patient setting and proposes models for tumour evolution that integrate genetic, histopathological, clinical and biological insights from the melanoma literature.
In the early 1900s, numerous seminal publications reported that high rates of cancer occurred in certain occupations. During this period, work with infectious agents produced only meager results which seemed irrelevant to humans. Then in the 1980s ground breaking evidence began to emerge that a variety of viruses also cause cancer in humans. There is now sufficient evidence of carcinogenicity in humans for human T-cell lymphotrophic virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, human papillomavirus, Epstein-Barr virus, and human herpes virus 8 according to the International Agency for Research on Cancer (IARC). Many other causes of cancer have also been identified by the IARC, which include: Sunlight, tobacco, pharmaceuticals, hormones, alcohol, parasites, fungi, bacteria, salted fish, wood dust, and herbs. The World Cancer Research Fund and the American Institute for Cancer Research have determined additional causes of cancer, which include beta carotene, red meat, processed meats, low fibre diets, not breast feeding, obesity, increased adult height and sedentary lifestyles. In brief, a historical review of the discoveries of the causes of human cancer is presented with extended discussions of the difficulties encountered in identifying viral causes of cancer.
Cancer therapy by entrapment
Mutations in the KRAS oncogene occur at high frequency in several of the most lethal human cancers, including lung and pancreatic cancer. Substantial effort has thus been directed toward developing KRAS inhibitors. KRAS encodes an enzyme that binds the nucleotide GTP and hydrolyzes it to GDP. It had been thought that oncogenic mutations disable this hydrolytic activity, locking KRAS in the GTP-bound, active state. Surprisingly, Lito et al. found that a certain KRAS mutant (G12C) retains hydrolytic activity and continues to cycle between its active and inactive states. They describe a compound that inhibits KRAS(G12C) signaling and tumor cell growth by binding to the GDPbound form of KRAS, trapping it in its inactive state.
Science , this issue p. 604
A central question in biology is whether variability between genetically identical cells exposed to the same culture conditions is largely stochastic or deterministic. Using image-based transcriptomics in millions of single human cells, we find that while variability of cytoplasmic transcript abundance is large, it is for most genes minimally stochastic and can be predicted with multivariate models of the phenotypic state and population context of single cells. Computational multiplexing of these predictive signatures across hundreds of genes revealed a complex regulatory system that controls the observed variability of transcript abundance between individual cells. Mathematical modeling and experimental validation show that nuclear retention and transport of transcripts between the nucleus and the cytoplasm is central to buffering stochastic transcriptional fluctuations in mammalian gene expression. Our work indicates that cellular compartmentalization confines transcriptional noise to the nucleus, thereby preventing it from interfering with the control of single-cell transcript abundance in the cytoplasm.
A recent report that 93 per cent of invasive cervical cancers worldwide contain human papillomavirus (HPV) may be an underestimate, due to sample inadequacy or integration events affecting the HPV L1 gene, which is the target of the polymerase chain reaction (PCR)-based test which was used. The formerly HPV-negative cases from this study have therefore been reanalysed for HPV serum antibodies and HPV DNA. Serology for HPV 16 VLPs, E6, and E7 antibodies was performed on 49 of the 66 cases which were HPV-negative and a sample of 48 of the 866 cases which were HPV-positive in the original study. Moreover, 55 of the 66 formerly HPV-negative biopsies were also reanalysed by a sandwich procedure in which the outer sections in a series of sections are used for histological review, while the inner sections are assayed by three different HPV PCR assays targeting different open reading frames (ORFs). No significant difference was found in serology for HPV 16 proteins between the cases that were originally HPV PCR-negative and -positive. Type-specific E7 PCR for 14 high-risk HPV types detected HPV DNA in 38 (69 per cent) of the 55 originally HPV-negative and amplifiable specimens. The HPV types detected were 16, 18, 31, 33, 39, 45, 52, and 58. Two (4 per cent) additional cases were only HPV DNA-positive by E1 and/or L1 consensus PCR. Histological analysis of the 55 specimens revealed that 21 were qualitatively inadequate. Only two of the 34 adequate samples were HPV-negative on all PCR tests, as against 13 of the 21 that were inadequate ( p< 0·001). Combining the data from this and the previous study and excluding inadequate specimens, the worldwide HPV prevalence in cervical carcinomas is 99·7 per cent. The presence of HPV in virtually all cervical cancers implies the highest worldwide attributable fraction so far reported for a specific cause of any major human cancer. The extreme rarity of HPV-negative cancers reinforces the rationale for HPV testing in addition to, or even instead of, cervical cytology in routine cervical screening. Copyright
Transcription factors (TFs) are commonly deregulated in the pathogenesis of human cancer and are a major class of cancer cell dependencies. Consequently, targeting of TFs can be highly effective in treating particular malignancies, as highlighted by the clinical efficacy of agents that target nuclear hormone receptors. In this review we discuss recent advances in our understanding of TFs as drug targets in oncology, with an emphasis on the emerging chemical approaches to modulate TF function. The remarkable diversity and potency of TFs as drivers of cell transformation justifies a continued pursuit of TFs as therapeutic targets for drug discovery.
The epidermal growth factor receptor (EGFR) signaling pathway is one of the most important pathways that regulate growth, survival, proliferation, and differentiation in mammalian cells. Reflecting this importance, it is one of the best-investigated signaling systems, both experimentally and computationally, and several computational models have been developed for dynamic analysis. A map of molecular interactions of the EGFR signaling system is a valuable resource for research in this area. In this paper, we present a comprehensive pathway map of EGFR signaling and other related pathways. The map reveals that the overall architecture of the pathway is a bow-tie (or hourglass) structure with several feedback loops. The map is created using CellDesigner software that enables us to graphically represent interactions using a well-defined and consistent graphical notation, and to store it in Systems Biology Markup Language (SBML).
Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data.Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).Contact: mrobinson@wehi.edu.au
The events associated with recombination between loxP, a site in P1 EcoRI fragment 7, and loxB, a site in the bacterial chromosome, are described. When fragment 7 is in a α vector, the product of loxP × loxB recombination is the integration of the λ-P1: 7(loxP) DNA as prophage in the bacterial chromosome and the production of two new hybrid sites, loxR and loxL, flanking the prophage. Lambda phages containing loxL, loxR and loxB sites have been isolated and used to measure recombination frequencies between all four lox sites in paired phage crosses. Two principles emerge from these crosses: (1) loxP and loxL sites are much better substrates for recombination than are loxR and loxB sites. (2) Both partners in a recombination reaction must contain either loxP or loxL sites for recombination to be efficient. These results can explain all of our findings relating to the recombination between α-P1: 7 DNA and the bacterial chromosome. In particular, integration of that DNA into loxB is low because loxP × loxB recombination is inefficient, and excision of the resulting prophage DNA is low because loxL × loxR recombination is inefficient. In contrast, integration of λ-P1: 7 DNA into a chromosome already containing a λ-P1: 7 prophage at loxB is relatively high and is always accompanied by the excision and subsequent loss of the original prophage DNA. We call this process integration by prophage displacement, and we can account for it by postulating that two lox recombination events are involved (loxP × loxR and loxP × loxL), both of which are more efficient than is loxP × loxB recombination. Analysis of the physical structure of the various λlox phages indicates that loxP-containing DNA can integrate into loxB in both possible orientations, and that the loxP × loxB crossover point is located within a 100 base-pair region of P1 BamHI fragment 9, a subfragment of EcoRI fragment 7. The loxB site has been mapped to a region of the Escherichia coli chromosome between tolC (66 min) and dnaG (67 min).
c-Raf-1 is a major effector of Ras proteins, responsible for activation of the ERK MAP kinase pathway and a critical regulator of both normal growth and oncogenic transformation. Using an inducible form of Raf in MDCK cells, we have shown that sustained activation of Raf alone is able to induce the transition from an epithelial to a mesenchymal phenotype. Raf promoted invasive growth in collagen gels, a characteristic of malignant cells; this was dependent on the operation of an autocrine loop involving TGFβ, whose secretion was induced by Raf. TGFβ induced growth inhibition and apoptosis in normal MDCK cells: Activation of Raf led to inhibition of the ability of TGFβ to induce apoptosis but not growth retardation. ERK has been reported previously to inhibit TGFβ signaling via phosphorylation of the linker region of Smads, which prevents their translocation to the nucleus. However, we found no evidence in this system that ERK can significantly influence the function of Smad2, Smad3, and Smad4 at the level of nuclear translocation, DNA binding, or transcriptional activation. Instead, strong activation of Raf caused a broad protection of these cells from various apoptotic stimuli, allowing them to respond to TGFβ with increased invasiveness while avoiding cell death. The Raf–MAP kinase pathway thus synergizes with TGFβ in promoting malignancy but does not directly impair TGFβ-induced Smad signaling.
Keywords
• Ras
• Raf
• TGFβ
• SMAD
• apoptosis
RAF family kinases were among the first oncoproteins to be described more than 30 years ago. They primarily act as signalling relays downstream of RAS, and their close ties to cancer have fuelled a large number of studies. However, we still lack a systems-level understanding of their regulation and mode of action. The recent discovery that the catalytic activity of RAF depends on an allosteric mechanism driven by kinase domain dimerization is providing a vital new piece of information towards a comprehensive model of RAF function. The fact that current RAF inhibitors unexpectedly induce ERK signalling by stimulating RAF dimerization also calls for a deeper structural characterization of this family of kinases.
Background:
The BRAF inhibitors vemurafenib and dabrafenib have shown efficacy as monotherapies in patients with previously untreated metastatic melanoma with BRAF V600E or V600K mutations. Combining dabrafenib and the MEK inhibitor trametinib, as compared with dabrafenib alone, enhanced antitumor activity in this population of patients.
Methods:
In this open-label, phase 3 trial, we randomly assigned 704 patients with metastatic melanoma with a BRAF V600 mutation to receive either a combination of dabrafenib (150 mg twice daily) and trametinib (2 mg once daily) or vemurafenib (960 mg twice daily) orally as first-line therapy. The primary end point was overall survival.
Results:
At the preplanned interim overall survival analysis, which was performed after 77% of the total number of expected events occurred, the overall survival rate at 12 months was 72% (95% confidence interval [CI], 67 to 77) in the combination-therapy group and 65% (95% CI, 59 to 70) in the vemurafenib group (hazard ratio for death in the combination-therapy group, 0.69; 95% CI, 0.53 to 0.89; P=0.005). The prespecified interim stopping boundary was crossed, and the study was stopped for efficacy in July 2014. Median progression-free survival was 11.4 months in the combination-therapy group and 7.3 months in the vemurafenib group (hazard ratio, 0.56; 95% CI, 0.46 to 0.69; P<0.001). The objective response rate was 64% in the combination-therapy group and 51% in the vemurafenib group (P<0.001). Rates of severe adverse events and study-drug discontinuations were similar in the two groups. Cutaneous squamous-cell carcinoma and keratoacanthoma occurred in 1% of patients in the combination-therapy group and 18% of those in the vemurafenib group.
Conclusions:
Dabrafenib plus trametinib, as compared with vemurafenib monotherapy, significantly improved overall survival in previously untreated patients with metastatic melanoma with BRAF V600E or V600K mutations, without increased overall toxicity. (Funded by GlaxoSmithKline; ClinicalTrials.gov number, NCT01597908.).