Dynamics and Variability of ERK2 Response to EGF in Individual Living Cells

A bright future: optogenetics to dissect the spatiotemporal control of cell behavior

Cells sense, process, and respond to extracellular information using signaling networks: collections of proteins that act as precise biochemical sensors. These protein networks are characterized by both complex temporal organization, such as pulses of signaling activity, and by complex spatial organization, where proteins assemble structures at particular locations and times within the cell. Yet despite their ubiquity, studying these spatial and temporal properties has remained challenging because they emerge from the entire protein network rather than a single node, and cannot be easily tuned by drugs or mutations. These challenges are being met by a new generation of optogenetic tools capable of directly controlling the activity of individual signaling nodes over time and the assembly of protein complexes in space. Here, we outline how these recent innovations are being used in conjunction with engineering-influenced experimental design to address longstanding questions in signaling biology.

Cancer mutations and targeted drugs can disrupt dynamic signal encoding by the Ras-Erk pathway

The Ras-Erk (extracellular signal-regulated kinase) pathway encodes information in its dynamics; the duration and frequency of Erk activity can specify distinct cell fates. To enable dynamic encoding, temporal information must be accurately transmitted from the plasma membrane to the nucleus. We used optogenetic profiling to show that both oncogenic B-Raf mutations and B-Raf inhibitors can cause corruption of this transmission, so that short pulses of input Ras activity are distorted into abnormally long Erk outputs. These changes can reshape downstream transcription and cell fates, resulting in improper decisions to proliferate. These findings illustrate how altered dynamic signal transmission properties, and not just constitutively increased signaling, can contribute to cell proliferation and perhaps cancer, and how optogenetic profiling can dissect mechanisms of signaling dysfunction in disease.

When More Is Less: Dual Phosphorylation Protects Signaling Off State against Overexpression

Kinases in signaling pathways are commonly activated by multisite phosphorylation. For example, the mitogen-activated protein kinase Erk is activated by its kinase Mek by two consecutive phosphorylations within its activation loop. In this article, we use kinetic models to study how the activation of Erk is coupled to its abundance. Intuitively, Erk activity should rise with increasing amounts of Erk protein. However, a mathematical model shows that the signaling off state is robust to increasing amounts of Erk, and Erk activity may even decline with increasing amounts of Erk. This counterintuitive, bell-shaped response of Erk activity to increasing amounts of Erk arises from the competition of the unmodified and single phosphorylated form of Erk for access to its kinase Mek. This shows that phosphorylation cycles can contain an intrinsic robustness mechanism that protects signaling from aberrant activation e.g., by gene expression noise or kinase overexpression after gene duplication events in diseases like cancer.

Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.

Revisited analysis of a SHIVA01 trial cohort using functional mutational analyses successfully predicted treatment outcome

It still remains to be demonstrated that using molecular profiling to guide therapy improves patient outcome in oncology. Classification of somatic variants is not straightforward, rendering treatment decisions based on variants with unknown significance (VUS) hard to implement. The oncogenic activity of VUS and mutations identified in 12 patients treated with molecularly targeted agents (MTAs) in the frame of SHIVA01 trial was assessed using Functional Annotation for Cancer Treatment (FACT). MTA response prediction was measured in vitro, blinded to the actual clinical trial results, and survival predictions according to FACT were correlated with the actual PFS of SHIVA01 patients. Patients with positive prediction had a median PFS of 5.8 months versus 1.7 months in patients with negative prediction (P < 0.05). Our results highlight the role of the functional interpretation of molecular profiles to predict MTA response.

Heritable stress response dynamics revealed by single-cell genealogy

Cells often respond to environmental stimuli by activating specific transcription factors. Upon exposure to glucose limitation stress, it is known that yeast Saccharomyces cerevisiae cells dephosphorylate the general stress response factor Msn2, leading to its nuclear localization, which in turn activates the expression of many genes. However, the precise dynamics of Msn2 nucleocytoplasmic translocations and whether they are inherited over multiple generations in a stress-dependent manner are not well understood. Tracking Msn2 localization events in yeast lineages grown on a microfluidic chip, here we report how cells modulate the amplitude, duration, frequency, and dynamic pattern of the localization events in response to glucose limitation stress. Single yeast cells were found to modulate the amplitude and frequency of Msn2 nuclear localization, but not its duration. Moreover, the Msn2 localization frequency was epigenetically inherited in descendants of mother cells, leading to a decrease in cell-to-cell variation in localization frequency. An analysis of the time dynamic patterns of nuclear localizations between genealogically related cell pairs using an information theory approach found that the magnitude of pattern similarity increased with stress intensity and was strongly inherited by the descendant cells at the highest stress level. By dissecting how general stress response dynamics is contributed by different modulation schemes over long time scales, our work provides insight into which scheme evolution might have acted on to optimize fitness in stressful environments.

EGFR Trafficking in Physiology and Cancer

Signaling from the epidermal growth factor receptor (EGFR) elicits multiple biological responses, including cell proliferation, migration, and survival. Receptor endocytosis and trafficking are critical physiological processes that control the strength, duration, diversification, and spatial restriction of EGFR signaling through multiple mechanisms, which we review in this chapter. These mechanisms include: (i) regulation of receptor density and activation at the cell surface; (ii) concentration of receptors into distinct nascent endocytic structures; (iii) commitment of the receptor to different endocytic routes; (iv) endosomal sorting and postendocytic trafficking of the receptor through distinct pathways, and (v) recycling to restricted regions of the cell surface. We also highlight how communication between organelles controls EGFR activity along the endocytic route. Finally, we illustrate how abnormal trafficking of EGFR oncogenic mutants, as well as alterations of the endocytic machinery, contributes to aberrant EGFR signaling in cancer.

Live-cell measurements of kinase activity in single cells using translocation reporters

Although kinases are important regulators of many cellular processes, measuring their activity in live cells remains challenging. We have developed kinase translocation reporters (KTRs), which enable multiplexed measurements of the dynamics of kinase activity at a single-cell level. These KTRs are composed of an engineered construct in which a kinase substrate is fused to a bipartite nuclear localization signal (bNLS) and nuclear export signal (NES), as well as to a fluorescent protein for microscopy-based detection of its localization. The negative charge introduced by phosphorylation of the substrate is used to directly modulate nuclear import and export, thereby regulating the reporter's distribution between the cytoplasm and nucleus. The relative cytoplasmic versus nuclear fluorescence of the KTR construct (the C/N ratio) is used as a proxy for the kinase activity in living, single cells. Multiple KTRs can be studied in the same cell by fusing them to different fluorescent proteins. Here, we present a protocol to execute and analyze live-cell microscopy experiments using KTRs. We describe strategies for development of new KTRs and procedures for lentiviral expression of KTRs in a cell line of choice. Cells are then plated in a 96-well plate, from which multichannel fluorescent images are acquired with automated time-lapse microscopy. We provide detailed guidance for a computational analysis and parameterization pipeline. The entire procedure, from virus production to data analysis, can be completed in ∼10 d.

In vivo single cell analysis reveals Gata2 dynamics in cells transitioning to hematopoietic fate

Eich et al. reveal the dynamic expression of the Gata2 transcription factor in single aortic cells transitioning to hematopoietic fate by vital imaging of Gata2Venus mouse embryos. Pulsatile expression level changes highlight an unstable genetic state during hematopoietic cell generation.

Cell fate is established through coordinated gene expression programs in individual cells. Regulatory networks that include the Gata2 transcription factor play central roles in hematopoietic fate establishment. Although Gata2 is essential to the embryonic development and function of hematopoietic stem cells that form the adult hierarchy, little is known about the in vivo expression dynamics of Gata2 in single cells. Here, we examine Gata2 expression in single aortic cells as they establish hematopoietic fate in Gata2Venus mouse embryos. Time-lapse imaging reveals rapid pulsatile level changes in Gata2 reporter expression in cells undergoing endothelial-to-hematopoietic transition. Moreover, Gata2 reporter pulsatile expression is dramatically altered in Gata2^+/− aortic cells, which undergo fewer transitions and are reduced in hematopoietic potential. Our novel finding of dynamic pulsatile expression of Gata2 suggests a highly unstable genetic state in single cells concomitant with their transition to hematopoietic fate. This reinforces the notion that threshold levels of Gata2 influence fate establishment and has implications for transcription factor–related hematologic dysfunctions.

Foxo1 nucleo-cytoplasmic distribution and unidirectional nuclear influx are the same in nuclei in a single skeletal muscle fiber but vary between fibers

Foxo transcription factors promote protein breakdown and atrophy of skeletal muscle fibers. Foxo transcriptional effectiveness is largely determined by phosphorylation-dependent nucleo-cytoplasmic shuttling. Imaging Foxo1-green fluorescent protein (GFP) over time in 124 nuclei in 68 multinucleated adult skeletal muscle fibers under control culture conditions reveals large variability between fibers in Foxo1-GFP nucleo-cytoplasmic concentration ratio (N/C) and in the apparent rate coefficient ( kI') for Foxo1-GFP unidirectional nuclear influx (measured with efflux blocked by leptomycin B). Pairs of values of N/C or of kI' from different nuclei in the same fiber were essentially the same, but only weakly correlated in nuclei from different fibers in the same culture well. Thus, fiber to fiber variability of cellular factors, but not extracellular factors, determines Foxo1 distribution. Over all nuclei, N/C and kI' were closely proportional, indicating that kI' is the major determinant of Foxo1 distribution. IGF-I activation of Foxo kinase Akt reduces variability by decreasing kI' and N/C in all fibers. However, inhibiting Akt did not drive kI' uniformly high, indicating other pathways in Foxo1 regulation.

NF-κB Dynamics Discriminate between TNF Doses in Single Cells

Although cytokine-dependent dynamics of nuclear factor κB (NF-κB) are known to encode information that regulates cell fate decisions, it is unclear whether single-cell responses are switch-like or encode more information about cytokine dose. Here, we measure the dynamic subcellular localization of NF-κB in response to a range of tumor necrosis factor (TNF) stimulation conditions to determine the prevailing mechanism of single-cell dose discrimination. Using an information theory formalism that accounts for signaling dynamics and non-responsive cell subpopulations, we find that the information transmission capacity of single cells exceeds that predicted from a switch-like response. Instead, we observe that NF-κB dynamics within single cells contain sufficient information to encode multiple, TNF-dependent cellular states, and have an activation threshold that varies across the population. By comparing single-cell responses to an internal, experimentally observed reference, we demonstrate that cells can grade responses to TNF across several orders of magnitude in concentration. This suggests that cells contain additional control points to fine-tune their cytokine responses beyond the decision to activate.

Cross-hierarchy systems principles

One driving motivation of systems biology is the search for general principles that govern the design of biological systems. But questions often arise as to what kind of general principles biology could have. Concepts from engineering such as robustness and modularity are indeed becoming a regular way of describing biological systems. Another source of potential general principles is the emerging similarities found in processes across biological hierarchies. In this piece, I describe several emerging cross-hierarchy similarities. Identification of more cross-hierarchy principles, and understanding the implications these convergence have on the construction of biological systems, I believe, present exciting challenges for systems biology in the decades to come.

Optical control of cell signaling by single-chain photoswitchable kinases

Protein kinases transduce signals to regulate a wide array of cellular functions in eukaryotes. A generalizable method for optical control of kinases would enable fine spatiotemporal interrogation or manipulation of these various functions. We report the design and application of single-chain cofactor-free kinases with photoswitchable activity. We engineered a dimeric protein, pdDronpa, that dissociates in cyan light and reassociates in violet light. Attaching two pdDronpa domains at rationally selected locations in the kinase domain, we created the photoswitchable kinases psRaf1, psMEK1, psMEK2, and psCDK5. Using these photoswitchable kinases, we established an all-optical cell-based assay for screening inhibitors, uncovered a direct and rapid inhibitory feedback loop from ERK to MEK1, and mediated developmental changes and synaptic vesicle transport in vivo using light.

Correlated receptor transport processes buffer single-cell heterogeneity

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system.

Cell surface receptors translate extracellular ligand concentrations to intracellular responses. Receptor transport between the plasma membrane and other cellular compartments regulates the number of accessible receptors at the plasma membrane that determines the strength of downstream pathway activation at a given ligand concentration. In cell populations, pathway activation strength and cellular responses vary between cells. Understanding origins of cell-to-cell variability is highly relevant for cancer research, motivated by the problem of fractional killing by chemotherapies and development of resistance in subpopulations of tumor cells. The erythropoietin receptor (EpoR) is a characteristic example of a receptor system that strongly depends on receptor transport processes. It is involved in several cellular processes, such as differentiation or proliferation, regulates the renewal of erythrocytes, and is expressed in several tumors. To investigate the involvement of receptor transport processes in cell-to-cell variability, we quantitatively characterized trafficking of EpoR in individual cells by combining live-cell imaging with mathematical modeling. Thereby, we found that EpoR dynamics was strongly dependent on rapid receptor transport and turnover. Interestingly, although transport processes largely differed between individual cells, receptor concentrations in cellular compartments were robust to variability in trafficking processes due to the correlated kinetics of opposing transport processes.

Abnormalities of signal transduction networks in chronic schizophrenia

Schizophrenia is a serious neuropsychiatric disorder characterized by disruptions of brain cell metabolism, microstructure, and neurotransmission. All of these processes require coordination of multiple kinase-mediated signaling events. We hypothesize that imbalances in kinase activity propagate through an interconnected network of intracellular signaling with potential to simultaneously contribute to many or all of the observed deficits in schizophrenia. We established a workflow distinguishing schizophrenia-altered kinases in anterior cingulate cortex using a previously published kinome array data set. We compared schizophrenia-altered kinases to haloperidol-altered kinases, and identified systems, functions, and regulators predicted using pathway analyses. We used kinase inhibitors with the kinome array to test hypotheses about imbalance in signaling and conducted preliminary studies of kinase proteins, phosphoproteins, and activity for kinases of interest. We investigated schizophrenia-associated single nucleotide polymorphisms in one of these kinases, AKT, for genotype-dependent changes in AKT protein or activity. Kinome analyses identified new kinases as well as some previously implicated in schizophrenia. These results were not explained by chronic antipsychotic treatment. Kinases identified in our analyses aligned with cytoskeletal arrangement and molecular trafficking. Of the kinases we investigated further, AKT and (unexpectedly) JNK, showed the most dysregulation in the anterior cingulate cortex of schizophrenia subjects. Changes in kinase activity did not correspond to protein or phosphoprotein levels. We also show that AKT single nucleotide polymorphism rs1130214, previously associated with schizophrenia, influenced enzyme activity but not protein or phosphoprotein levels. Our data indicate subtle changes in kinase activity and regulation across an interlinked kinase network, suggesting signaling imbalances underlie the core symptoms of schizophrenia.

A study by US scientists indicates that changes in the activity of key signaling proteins may underlie core symptoms of schizophrenia. Protein kinases mediate the activation of intracellular signaling events and analyses of the kinome, the complete set of protein kinases encoded in the genome, previously revealed significant changes in phosphorylation patterns in postmortem brain tissue from patients with schizophrenia. Based on these findings, Jennifer McGuire at the University of Cincinnati and colleagues investigated the upstream regulation of these proteins. They identified both established and novel proteins associated with schizophrenia in the anterior cingulate cortex, with JNK and AKT activity being the most disrupted in schizophrenia patients. Their findings highlight how subtle changes in the activity of a small number of signaling proteins can propagate and have major consequences for mental health.

Connecting the dots across time: reconstruction of single-cell signalling trajectories using time-stamped data

Single-cell responses are shaped by the geometry of signalling kinetic trajectories carved in a multidimensional space spanned by signalling protein abundances. It is, however, challenging to assay a large number (more than 3) of signalling species in live-cell imaging, which makes it difficult to probe single-cell signalling kinetic trajectories in large dimensions. Flow and mass cytometry techniques can measure a large number (4 to more than 40) of signalling species but are unable to track single cells. Thus, cytometry experiments provide detailed time-stamped snapshots of single-cell signalling kinetics. Is it possible to use the time-stamped cytometry data to reconstruct single-cell signalling trajectories? Borrowing concepts of conserved and slow variables from non-equilibrium statistical physics we develop an approach to reconstruct signalling trajectories using snapshot data by creating new variables that remain invariant or vary slowly during the signalling kinetics. We apply this approach to reconstruct trajectories using snapshot data obtained from in silico simulations, live-cell imaging measurements, and, synthetic flow cytometry datasets. The application of invariants and slow variables to reconstruct trajectories provides a radically different way to track objects using snapshot data. The approach is likely to have implications for solving matching problems in a wide range of disciplines.

Stable swarming using adaptive long-range interactions

Sensory mechanisms in biology, from cells to humans, have the property of adaptivity, whereby the response produced by the sensor is adapted to the overall amplitude of the signal, reducing the sensitivity in the presence of strong stimulus, while increasing it when it is weak. This property is inherently energy consuming and a manifestation of the nonequilibrium nature of living organisms. We explore here how adaptivity affects the effective forces that organisms feel due to others in the context of a uniform swarm, in both two and three dimensions. The interactions between the individuals are taken to be attractive and long-range and of power-law form. We find that the effects of adaptivity inside the swarm are dramatic, where the effective forces decrease (or remain constant) with increasing swarm density. Linear stability analysis demonstrates how this property prevents collapse (Jeans instability), when the forces are adaptive. Adaptivity therefore endows swarms with a natural mechanism for self-stabilization.

Fundamental trade-offs between information flow in single cells and cellular populations

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Accelerating Live Single-Cell Signalling Studies

The dynamics of signalling networks that couple environmental conditions with cellular behaviour can now be characterised in exquisite detail using live single-cell imaging experiments. Recent improvements in our abilities to introduce fluorescent sensors into cells, coupled with advances in pipelines for quantifying and extracting single-cell data, mean that high-throughput systematic analyses of signalling dynamics are becoming possible. In this review, we consider current technologies that are driving progress in the scale and range of such studies. Moreover, we discuss novel approaches that are allowing us to explore how pathways respond to changes in inputs and even predict the fate of a cell based upon its signalling history and state.

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation

Recent advancements in single-cell and single-molecule imaging technologies have resolved biological processes in time and space that are fundamental to understanding the regulation of gene expression. Observations of single-molecule events in their cellular context have revealed highly dynamic aspects of transcriptional and post-transcriptional control in eukaryotic cells. This approach can relate transcription with mRNA abundance and lifetimes. Another key aspect of single-cell analysis is the cell-to-cell variability among populations of cells. Definition of heterogeneity has revealed stochastic processes, determined characteristics of under-represented cell types or transitional states, and integrated cellular behaviors in the context of multicellular organisms. In this review, we discuss novel aspects of gene expression of eukaryotic cells and multicellular organisms revealed by the latest advances in single-cell and single-molecule imaging technology.

p53 dynamics in response to DNA damage vary across cell lines and are shaped by efficiency of DNA repair and activity of the kinase ATM

Cellular systems show a wide range of signaling dynamics. Many of these dynamics are highly stereotyped, such as oscillations at a fixed frequency. However, most studies looking at the role of signaling dynamics focus on one or a few cell lines, leaving the diversity of dynamics across tissues or cell lines a largely unexplored question. We focused on the dynamics of the tumor suppressor protein p53, which regulates cell cycle arrest and apoptosis in response to DNA damage. We established live-cell reporters for 12 cancer cell lines expressing wild-type p53 and quantified p53 dynamics in response to double-strand break-inducing DNA damage. In many of the tested cell lines, we found that p53 abundance oscillated in response to ionizing radiation or the DNA-damaging chemotherapeutic neocarzinostatin and that the periodicity of the oscillations was fixed. In other cell lines, p53 abundance dynamically changed in different ways, such as a single broad pulse or a continuous induction. By combining single-cell assays of p53 signaling dynamics, small-molecule screening in live cells, and mathematical modeling, we identified molecules that perturbed p53 dynamics and determined that cell-specific variation in the efficiency of DNA repair and the activity of the kinase ATM (ataxia-telangiectasia mutated) controlled the signaling landscape of p53 dynamics. Because the dynamics of wild-type p53 varied substantially between cell lines, our study highlights the limitation of using one line as a model system and emphasizes the importance of studying the dynamics of other signaling pathways across different cell lines and genetic backgrounds.

Genetic visualization of protein interactions harnessing liquid phase transitions

Protein-protein interactions (PPIs) are essential components of cellular function. Current fluorescence-based technologies to measure PPIs have limited dynamic range and quantitative reproducibility. Here, we describe a genetically-encoded PPI visualization system that harnesses the dynamics of condensed liquid-phase transitions to analyze protein interactions in living cells. The fluorescent protein Azami-Green and p62-PB1 domain when fused to PPI partners triggered a rapid concatenation/oligomerization process that drove the condensation of liquid-phase droplets for real-time analysis of the interaction with unlimited dynamic range in the fluorescence signal. Proof-of-principle studies revealed novel insights on the live cell dynamics of XIAP-Smac and ERK2-dimer interactions. A photoconvertible variant allowed time-resolved optical highlighting for PPI kinetic analysis. Our system, called Fluoppi, demonstrates the unique signal amplification properties of liquid-phase condensation to detect PPIs. The findings introduce a general method for discovery of novel PPIs and modulators of established PPIs.

Measuring Signaling and RNA-Seq in the Same Cell Links Gene Expression to Dynamic Patterns of NF-κB Activation

Signaling proteins display remarkable cell-to-cell heterogeneity in their dynamic responses to stimuli, but the consequences of this heterogeneity remain largely unknown. For instance, the contribution of the dynamics of the innate immune transcription factor nuclear factor κB (NF-κB) to gene expression output is disputed. Here we explore these questions by integrating live-cell imaging approaches with single-cell sequencing technologies. We used this approach to measure both the dynamics of lipopolysaccharide-induced NF-κB activation and the global transcriptional response in the same individual cell. Our results identify multiple, distinct cytokine expression patterns that are correlated with NF-κB activation dynamics, establishing a functional role for NF-κB dynamics in determining cellular phenotypes. Applications of this approach to other model systems and single-cell sequencing technologies have significant potential for discovery, as it is now possible to trace cellular behavior from the initial stimulus, through the signaling pathways, down to genome-wide changes in gene expression, all inside of a single cell.

Sensing relative signal in the Tgf-β/Smad pathway

How signaling pathways function reliably despite cellular variation remains a question in many systems. In the transforming growth factor-β (Tgf-β) pathway, exposure to ligand stimulates nuclear localization of Smad proteins, which then regulate target gene expression. Examining Smad3 dynamics in live reporter cells, we found evidence for fold-change detection. Although the level of nuclear Smad3 varied across cells, the fold change in the level of nuclear Smad3 was a more precise outcome of ligand stimulation. The precision of the fold-change response was observed throughout the signaling duration and across Tgf-β doses, and significantly increased the information transduction capacity of the pathway. Using single-molecule FISH, we further observed that expression of Smad3 target genes (ctgf, snai1, and wnt9a) correlated more strongly with the fold change, rather than the level, of nuclear Smad3. These findings suggest that some target genes sense Smad3 level relative to background, as a strategy for coping with cellular noise.

Nuclear relocation of Kss1 contributes to the specificity of the mating response

Mitogen Activated Protein Kinases (MAPK) play a central role in transducing extra-cellular signals into defined biological responses. These enzymes, conserved in all eukaryotes, exert their function via the phosphorylation of numerous substrates located throughout the cell and by inducing a complex transcriptional program. The partitioning of their activity between the cytoplasm and the nucleus is thus central to their function. Budding yeast serves as a powerful system to understand the regulation of these fundamental biological phenomena. Under vegetative growth, the MAPK Kss1 is enriched in the nucleus of the cells. Stimulation with mating pheromone results in a rapid relocation of the protein in the cytoplasm. Activity of either Fus3 or Kss1 in the mating pathway is sufficient to drive this change in location by disassembling the complex formed between Kss1, Ste12 and Dig1. Artificial enrichment of the MAPK Kss1 in the nucleus in presence of mating pheromone alters the transcriptional response of the cells and induces a cell-cycle arrest in absence of Fus3 and Far1.

A Dynamic Model of Immune Responses to Antigen Presentation Predicts Different Regions of Tumor or Pathogen Elimination

The immune system must discriminate between agents of disease and an organism's healthy cells. While the identification of an antigen as self/non-self is critically important, the dynamic features of antigen presentation may also determine the immune system's response. Here, we use a simple mathematical model of immune activation to explore the idea of antigen discrimination through dynamics. We propose that antigen presentation is coupled to two nodes, one regulatory and one effecting the immune response, through an incoherent feedforward loop and repressive feedback. This circuit would allow the immune system to effectively estimate the increase of antigens with respect to time, a key determinant of immune reactivity in vivo. Our model makes the prediction that tumors growing at specific rates evade the immune system despite the continuous presence of antigens indicating disease, a phenomenon closely related to clinically observed "two-zone tolerance." Finally, we discuss a plausible biological instantiation of our circuit using combinations of regulatory and effector T cells.

Quantification of growth factor signaling and pathway cross talk by live-cell imaging

Peptide growth factors stimulate cellular responses through activation of their transmembrane receptors. Multiple intracellular signaling cascades are engaged following growth factor-receptor binding, leading to short- and long-term biological effects. Each receptor-activated signaling pathway does not act in isolation but rather interacts at different levels with other pathways to shape signaling networks that are distinctive for each growth factor. To gain insights into the specifics of growth factor-regulated interactions among different signaling cascades, we developed a HeLa cell line stably expressing fluorescent live-cell imaging reporters that are readouts for two major growth factor-stimulated pathways, Ras-Raf-Mek-ERK and phosphatidylinositol (PI) 3-kinase-Akt. Incubation of cells with epidermal growth factor (EGF) resulted in rapid, robust, and sustained ERK signaling but shorter-term activation of Akt. In contrast, hepatocyte growth factor induced sustained Akt signaling but weak and short-lived ERK activity, and insulin-like growth factor-I stimulated strong long-term Akt responses but negligible ERK signaling. To address potential interactions between signaling pathways, we employed specific small-molecule inhibitors. In cells incubated with EGF or platelet-derived growth factor-AA, Raf activation and the subsequent stimulation of ERK reduced Akt signaling, whereas Mek inhibition, which blocked ERK activation, enhanced Akt and turned transient effects into sustained responses. Our results reveal that individual growth factors initiate signaling cascades that vary markedly in strength and duration and demonstrate in living cells the dramatic effects of cross talk from Raf and Mek to PI 3-kinase and Akt. Our data further indicate how specific growth factors can encode distinct cellular behaviors by promoting complex interactions among signaling pathways.

Spatial and temporal signal processing and decision making by MAPK pathways

Recent studies show that MAPK pathways perform exquisite spatial and temporal signal processing. This review discusses the mechanisms that process dynamic inputs into graded output responses, the role of positive and negative feedbacks, and feedforward regulation.

Mitogen-activated protein kinase (MAPK) pathways are conserved from yeast to man and regulate a variety of cellular processes, including proliferation and differentiation. Recent developments show how MAPK pathways perform exquisite spatial and temporal signal processing and underscores the importance of studying the dynamics of signaling pathways to understand their physiological response. The importance of dynamic mechanisms that process input signals into graded downstream responses has been demonstrated in the pheromone-induced and osmotic stress–induced MAPK pathways in yeast and in the mammalian extracellular signal-regulated kinase MAPK pathway. Particularly, recent studies in the yeast pheromone response have shown how positive feedback generates switches, negative feedback enables gradient detection, and coherent feedforward regulation underlies cellular memory. More generally, a new wave of quantitative single-cell studies has begun to elucidate how signaling dynamics determine cell physiology and represents a paradigm shift from descriptive to predictive biology.

Single-Cell Imaging of ERK Signaling Using Fluorescent Biosensors

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

Optogenetic Control of Ras/Erk Signaling Using the Phy-PIF System

The Ras/Erk signaling pathway plays a central role in diverse cellular processes ranging from development to immune cell activation to neural plasticity to cancer. In recent years, this pathway has been widely studied using live-cell fluorescent biosensors, revealing complex Erk dynamics that arise in many cellular contexts. Yet despite these high-resolution tools for measurement, the field has lacked analogous tools for control over Ras/Erk signaling in live cells. Here, we provide detailed methods for one such tool based on the optical control of Ras activity, which we call "Opto-SOS." Expression of the Opto-SOS constructs can be coupled with a live-cell reporter of Erk activity to reveal highly quantitative input-to-output maps of the pathway. Detailed herein are protocols for expressing the Opto-SOS system in cultured cells, purifying the small molecule cofactor necessary for optical stimulation, imaging Erk responses using live-cell microscopy, and processing the imaging data to quantify Ras/Erk signaling dynamics.

Distinct cellular states determine calcium signaling response

The heterogeneity in mammalian cells signaling response is largely a result of pre‐existing cell‐to‐cell variability. It is unknown whether cell‐to‐cell variability rises from biochemical stochastic fluctuations or distinct cellular states. Here, we utilize calcium response to adenosine trisphosphate as a model for investigating the structure of heterogeneity within a population of cells and analyze whether distinct cellular response states coexist. We use a functional definition of cellular state that is based on a mechanistic dynamical systems model of calcium signaling. Using Bayesian parameter inference, we obtain high confidence parameter value distributions for several hundred cells, each fitted individually. Clustering the inferred parameter distributions revealed three major distinct cellular states within the population. The existence of distinct cellular states raises the possibility that the observed variability in response is a result of structured heterogeneity between cells. The inferred parameter distribution predicts, and experiments confirm that variability in IP3R response explains the majority of calcium heterogeneity. Our work shows how mechanistic models and single‐cell parameter fitting can uncover hidden population structure and demonstrate the need for parameter inference at the single‐cell level.

Modeling Cellular Noise Underlying Heterogeneous Cell Responses in the Epidermal Growth Factor Signaling Pathway

Cellular heterogeneity, which plays an essential role in biological phenomena, such as drug resistance and migration, is considered to arise from intrinsic (i.e., reaction kinetics) and extrinsic (i.e., protein variability) noise in the cell. However, the mechanistic effects of these types of noise to determine the heterogeneity of signal responses have not been elucidated. Here, we report that the output of epidermal growth factor (EGF) signaling activity is modulated by cellular noise, particularly by extrinsic noise of particular signaling components in the pathway. We developed a mathematical model of the EGF signaling pathway incorporating regulation between extracellular signal-regulated kinase (ERK) and nuclear pore complex (NPC), which is necessary for switch-like activation of the nuclear ERK response. As the threshold of switch-like behavior is more sensitive to perturbations than the graded response, the effect of biological noise is potentially critical for cell fate decision. Our simulation analysis indicated that extrinsic noise, but not intrinsic noise, contributes to cell-to-cell heterogeneity of nuclear ERK. In addition, we accurately estimated variations in abundance of the signal proteins between individual cells by direct comparison of experimental data with simulation results using Apparent Measurement Error (AME). AME was constant regardless of whether the protein levels varied in a correlated manner, while covariation among proteins influenced cell-to-cell heterogeneity of nuclear ERK, suppressing the variation. Simulations using the estimated protein abundances showed that each protein species has different effects on cell-to-cell variation in the nuclear ERK response. In particular, variability of EGF receptor, Ras, Raf, and MEK strongly influenced cellular heterogeneity, while others did not. Overall, our results indicated that cellular heterogeneity in response to EGF is strongly driven by extrinsic noise, and that such heterogeneity results from variability of particular protein species that function as sensitive nodes, which may contribute to the pathogenesis of human diseases.

Individual cell behaviors are controlled by a variety of noise, such as fluctuations in biochemical reactions, protein variability, molecular diffusion, transcriptional noise, cell-to-cell contact, temperature, and pH. Such cellular noise often interferes with signal responses from external stimuli, and such heterogeneity functions in induction of drug resistance, survival, and migration of cells. Thus, heterogeneous cellular responses have positive and negative roles. However, the regulatory mechanisms that produce cellular heterogeneity are unclear. By mathematical modeling and simulations, we investigated how heterogeneous signaling responses are evoked in the EGF signaling pathway and influence the switch-like activation of nuclear ERK. This study demonstrated that cellular heterogeneity of the EGF signaling response is evoked by cell-to-cell variation of particular signaling proteins, such as EGFR, Ras, Raf, and MEK, which act as sensitive nodes in the pathway. These results suggest that signaling responses in individual cells can be predicted from the levels of proteins of sensitive nodes. This study also suggested that proteins of sensitive nodes may serve as cell survival mechanisms.

Quantifying β-catenin subcellular dynamics and cyclin D1 mRNA transcription during Wnt signaling in single living cells

Signal propagation from the cell membrane to a promoter can induce gene expression. To examine signal transmission through sub-cellular compartments and its effect on transcription levels in individual cells within a population, we used the Wnt/β-catenin signaling pathway as a model system. Wnt signaling orchestrates a response through nuclear accumulation of β-catenin in the cell population. However, quantitative live-cell measurements in individual cells showed variability in nuclear β-catenin accumulation, which could occur in two waves, followed by slow clearance. Nuclear accumulation dynamics were initially rapid, cell cycle independent and differed substantially from LiCl stimulation, presumed to mimic Wnt signaling. β-catenin levels increased simultaneously at adherens junctions and the centrosome, and a membrane-centrosome transport system was revealed. Correlating β-catenin nuclear dynamics to cyclin D1 transcriptional activation showed that the nuclear accumulation rate of change of the signaling factor, and not actual protein levels, correlated with the transcriptional output of the pathway.

DOI:http://dx.doi.org/10.7554/eLife.16748.001

Cells in an animal’s body must communicate with one another to coordinate many processes that are essential to life. One way that cells do this is by releasing molecules that bind to receptors located on the surface of others cells; this binding then triggers a signaling pathway in the receiving cell that passes information from the surface of the cell to its interior. The last stage of these pathways typically involves specific genes being activated, which changes the cell’s overall activity.

Wnt is one protein that animal cells release to control how nearby cells grow and divide. One arm of the Wnt signaling pathway involves a protein called β-catenin. In the absence of a Wnt signal, there is little β-catenin in the cell. When Wnt binds to its receptor, β-catenin accumulates and enters the cell’s nucleus to activate its target genes. One of these genes, called cyclin D1, controls cell division. However it was not understood how β-catenin builds up in response to a Wnt signal and influences the activity of genes.

Using microscopy, Kafri et al. have now examined how the activities of β-catenin and the cyclin D1 gene change in living human cells. These analyses were initially performed in a population of cells, and confirmed that β-catenin rapidly accumulates after a Wnt signal and that the cyclin D1 gene becomes activated.

Individual cells in a population can respond differently to signaling events. To assess whether human cells differ in their responses to Wnt, Kafri et al. examined the dynamics of β-catenin in single cells in real time. In most cells, β-catenin accumulated after Wnt activation. However, the time taken to accumulate β-catenin, and this protein’s levels, varied between individual cells. Most cells showed the “average” response, with one major wave of accumulation that peaked about two hours after the Wnt signal. Notably, in some cells, β-catenin accumulated in the cell’s nucleus in two waves; in other words, the levels in this compartment of the cell increased, dropped slightly and then increased again.

So how does β-catenin in the nucleus activate target genes? Kafri et al. saw that the absolute number of β-catenin molecules in the nucleus did not affect the activity of cyclin D1. Instead, cells appeared to sense how quickly the amount of β-catenin in the nucleus changes over time, and this rate influences the activation of cyclin D1.

Importantly, problems with Wnt signaling have been linked to diseases in humans; and different components of the Wnt signaling pathway are mutated in many cancers. An important next challenge will be to uncover how the dynamics of this pathway change during disease. Furthermore, a better understanding of Wnt signaling may in future help efforts to develop new drugs that can target the altered pathway in cancer cells.

DOI:http://dx.doi.org/10.7554/eLife.16748.002

Single-cell dynamics and variability of MAPK activity in a yeast differentiation pathway

In response to pheromones, yeast cells activate a MAPK pathway to direct processes important for mating, including gene induction, cell-cycle arrest, and polarized cell growth. Although a variety of assays have been able to elucidate signaling activities at multiple steps in the pathway, measurements of MAPK activity during the pheromone response have remained elusive, and our understanding of single-cell signaling behavior is incomplete. Using a yeast-optimized FRET-based mammalian Erk-activity reporter to monitor Fus3 and Kss1 activity in live yeast cells, we demonstrate that overall mating MAPK activity exhibits distinct temporal dynamics, rapid reversibility, and a graded dose dependence around the K_D of the receptor, where phenotypic transitions occur. The complex dose response was found to be largely a consequence of two feedbacks involving cyclin-mediated scaffold phosphorylation and Fus3 autoregulation. Distinct cell cycle-dependent response patterns comprised a large portion of the cell-to-cell variability at each dose, constituting the major source of extrinsic noise in coupling activity to downstream gene-expression responses. Additionally, we found diverse spatial MAPK activity patterns to emerge over time in cells undergoing default, gradient, and true mating responses. Furthermore, ramping up and rapid loss of activity were closely associated with zygote formation in mating-cell pairs, supporting a role for elevated MAPK activity in successful cell fusion and morphogenic reorganization. Altogether, these findings present a detailed view of spatiotemporal MAPK activity during the pheromone response, elucidating its role in mediating complex long-term developmental fates in a unicellular differentiation system.

Long-Lived Binding of Sox2 to DNA Predicts Cell Fate in the Four-Cell Mouse Embryo

Transcription factor (TF) binding to DNA is fundamental for gene regulation. However, it remains unknown how the dynamics of TF-DNA interactions change during cell-fate determination in vivo. Here, we use photo-activatable FCS to quantify TF-DNA binding in single cells of developing mouse embryos. In blastocysts, the TFs Oct4 and Sox2, which control pluripotency, bind DNA more stably in pluripotent than in extraembryonic cells. By contrast, in the four-cell embryo, Sox2 engages in more long-lived interactions than does Oct4. Sox2 long-lived binding varies between blastomeres and is regulated by H3R26 methylation. Live-cell tracking demonstrates that those blastomeres with more long-lived binding contribute more pluripotent progeny, and reducing H3R26 methylation decreases long-lived binding, Sox2 target expression, and pluripotent cell numbers. Therefore, Sox2-DNA binding predicts mammalian cell fate as early as the four-cell stage. More generally, we reveal the dynamic repartitioning of TFs between DNA sites driven by physiological epigenetic changes. VIDEO ABSTRACT.

Allosteric proteins as logarithmic sensors

Many sensory systems, from vision and hearing in animals to signal transduction in cells, respond to fold changes in signal relative to background. Responding to fold change requires that the system senses signal on a logarithmic scale, responding identically to a change in signal level from 1 to 3, or from 10 to 30. It is an ongoing search in the field to understand the ways in which a logarithmic sensor can be implemented at the molecular level. In this work, we present evidence that logarithmic sensing can be implemented with a single protein, by means of allosteric regulation. Specifically, we find that mathematical models show that allosteric proteins can respond to stimuli on a logarithmic scale. Next, we present evidence from measurements in the literature that some allosteric proteins do operate in a parameter regime that permits logarithmic sensing. Finally, we present examples suggesting that allosteric proteins are indeed used in this capacity: allosteric proteins play a prominent role in systems where fold-change detection has been proposed. This finding suggests a role as logarithmic sensors for the many allosteric proteins across diverse biological processes.

Evolution of optimal Hill coefficients in nonlinear public goods games

In evolutionary game theory, the effect of public goods like diffusible molecules has been modelled using linear, concave, sigmoid and step functions. The observation that biological systems are often sigmoid input-output functions, as described by the Hill equation, suggests that a sigmoid function is more realistic. The Michaelis-Menten model of enzyme kinetics, however, predicts a concave function, and while mechanistic explanations of sigmoid kinetics exist, we lack an adaptive explanation: what is the evolutionary advantage of a sigmoid benefit function? We analyse public goods games in which the shape of the benefit function can evolve, in order to determine the optimal and evolutionarily stable Hill coefficients. We find that, while the dynamics depends on whether output is controlled at the level of the individual or the population, intermediate or high Hill coefficients often evolve, leading to sigmoid input-output functions that for some parameters are so steep to resemble a step function (an on-off switch). Our results suggest that, even when the shape of the benefit function is unknown, biological public goods should be modelled using a sigmoid or step function rather than a linear or concave function.

The natural defense system and the normative self model

Infectious agents are not the only agressors, and the immune system is not the sole defender of the organism. In an enlarged perspective, the ‘normative self model’ postulates that a ‘natural defense system’ protects man and other complex organisms against the environmental and internal hazards of life, including infections and cancers. It involves multiple error detection and correction mechanisms that confer robustness to the body at all levels of its organization. According to the model, the self relies on a set of physiological norms, and NONself (meaning : Non Obedient to the Norms of the self) is anything ‘off-norms’. The natural defense system comprises a set of ‘civil defenses’ (to which all cells in organs and tissues contribute), and a ‘professional army ‘, made of a smaller set of mobile cells. Mobile and non mobile cells differ in their tuning abilities. Tuning extends the recognition capabilities of NONself by the mobile cells, which increase their defensive function. To prevent them to drift, which would compromise self/NONself discrimination, the more plastic mobile cells need to periodically refer to the more stable non mobile cells to keep within physiological standards.

Redefining Signaling Pathways with an Expanding Single-Cell Toolbox

Genetically identical cells respond heterogeneously to uniform environmental stimuli. Consequently, investigating the signaling networks that control these cell responses using 'average' bulk cell measurements can obscure underlying mechanisms and misses information emerging from cell-to-cell variability. Here we review recent technological advances including live-cell fluorescence imaging-based approaches and microfluidic devices that enable measurements of signaling networks, dynamics, and responses in single cells. We discuss how these single-cell tools have uncovered novel mechanistic insights for canonical signaling pathways that control cell proliferation (ERK), DNA-damage responses (p53), and innate immune and stress responses (NF-κB). Future improvements in throughput and multiplexing, analytical pipelines, and in vivo applicability will all significantly expand the biological information gained from single-cell measurements of signaling pathways.

Dynamics of CDKN1A in Single Cells Defined by an Endogenous Fluorescent Tagging Toolkit

Observing the endogenous abundance, localization, and dynamics of proteins in mammalian cells is crucial to understanding their function and behavior. Currently, there is no systematic approach for the fluorescent tagging of endogenous loci. Here, we used Cas9-catalyzed DNA breaks, short homology arms, and a family of donor plasmids to establish endogenous Fluorescent tagging (eFlut): a low-cost and efficient approach to generating endogenous proteins with fluorescent labels. We validated this protocol on multiple proteins in several cell lines and species and applied our tools to study the cell-cycle inhibitor CDKN1A in single cells. We uncover heterogeneity in the timing and rate of CDKN1A induction post-DNA damage and show that this variability is post-transcriptionally regulated, depends on cell-cycle position, and has long-term consequences for cellular proliferation. The tools developed in this study should support widespread study of the dynamics and localization of diverse proteins in mammalian cells.

Conversion of graded phosphorylation into switch-like nuclear translocation via autoregulatory mechanisms in ERK signalling

The phosphorylation cascade in the extracellular signal-regulated kinase (ERK) pathway is a versatile reaction network motif that can potentially act as a switch, oscillator or memory. Nevertheless, there is accumulating evidence that the phosphorylation response is mostly linear to extracellular signals in mammalian cells. Here we find that subsequent nuclear translocation gives rise to a switch-like increase in nuclear ERK concentration in response to signal input. The switch-like response disappears in the presence of ERK inhibitor, suggesting the existence of autoregulatory mechanisms for ERK nuclear translocation involved in conversion from a graded to a switch-like response. In vitro reconstruction of ERK nuclear translocation indicates that ERK-mediated phosphorylation of nucleoporins regulates ERK translocation. A mathematical model and knockdown experiments suggest a contribution of nucleoporins to regulation of the ERK nuclear translocation response. Taken together, this study provides evidence that nuclear translocation with autoregulatory mechanisms acts as a switch in ERK signalling.

While ERK signalling can produce switch-like cell behaviour, phosphorylation of ERK increases linearly with extracellular signals. Here, the authors solve this seeming contradiction by showing that nuclear translocation of ERK behaves in a switch-like manner and is controlled by ERK activity.

A PGC-1α-Mediated Transcriptional Network Maintains Mitochondrial Redox and Bioenergetic Homeostasis against Doxorubicin-Induced Toxicity in Human Cardiomyocytes: Implementation of TT21C

Chemical toxicity testing is fast moving in a direction that relies increasingly on cell-basedin vitroassays anchored on toxicity pathways according to the toxicity testing in the 21st century vision. Identifying points of departure (POD) via these assays and revealing their mechanistic underpinnings via computational modeling of the relevant pathways are critical and challenging steps. Here we used doxorubicin (DOX) as a prototype chemical to study mitochondrial toxicity in human AC16 cells. Mitochondrial toxicity has been linked to cardiovascular risk of DOX, which has limited its clinical use as an antitumor drug. Ourin vitrostudy revealed a well-defined POD concentration of DOX below which adaptive induction of proliferator-activated receptor-γ coactivator-1α (PGC-1α) -mediated mitochondrial genes, including NRF-1, MnSOD, UCP2, and COX1, concurred with negligible changes in mitochondrial superoxide and cytotoxicity. At higher DOX concentrations adversity became significant with elevated superoxide and suppressed ATP levels. A computational model was formulated to simulate the PGC-1α-mediated transcriptional network comprising multiple negative feedback loops that underlie redox and bioenergetics homeostasis in the mitochondrion. The model recapitulated the transition phase from adaptive to adverse responses, supporting the notion that saturated induction of PGC-1α-mediated gene network underpins POD. The model further predicts (follow-up experiments verified) that silencing PGC-1α compromises the adaptive function of the transcriptional network, leading to disruption of mitochondria and cytotoxicity at lower DOX concentrations. In summary, our study demonstrates that combining pathway-focusedin vitroassays and computational simulation of relevant biochemical network is synergistic for understanding dose-response behaviors in the low-dose region and identifying POD.

Altered signaling in systemic juvenile idiopathic arthritis monocytes

Systemic juvenile idiopathic arthritis (sJIA) is characterized by systemic inflammation and arthritis. Monocytes are implicated in sJIA pathogenesis, but their role in disease is unclear. The response of sJIA monocytes to IFN may be dysregulated. We examined intracellular signaling in response to IFN type I (IFNα) and type II (IFNγ) in monocytes during sJIA activity and quiescence, in 2 patient groups. Independent of disease activity, monocytes from Group 1 (collected between 2002 and 2009) showed defective STAT1 phosphorylation downstream of IFNs, and expressed higher transcript levels of SOCS1, an inhibitor of IFN signaling. In the Group 2 (collected between 2011 and 2014), monocytes of patients with recent disease onset were IFNγ hyporesponsive, but in treated, quiescent subjects, monocytes were hyperresponsive to IFNγ. Recent changes in medication in sJIA may alter the IFN hyporesponsiveness. Impaired IFN/pSTAT1 signaling is consistent with skewing of sJIA monocytes away from an M1 phenotype and may contribute to disease pathology.

Frequency modulation of ERK activation dynamics rewires cell fate

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.

Dynamics and heterogeneity of a fate determinant during transition towards cell differentiation

Yan is an ETS-domain transcription factor responsible for maintaining Drosophila eye cells in a multipotent state. Yan is at the core of a regulatory network that determines the time and place in which cells transit from multipotency to one of several differentiated lineages. Using a fluorescent reporter for Yan expression, we observed a biphasic distribution of Yan in multipotent cells, with a rapid inductive phase and slow decay phase. Transitions to various differentiated states occurred over the course of this dynamic process, suggesting that Yan expression level does not strongly determine cell potential. Consistent with this conclusion, perturbing Yan expression by varying gene dosage had no effect on cell fate transitions. However, we observed that as cells transited to differentiation, Yan expression became highly heterogeneous and this heterogeneity was transient. Signals received via the EGF Receptor were necessary for the transience in Yan noise since genetic loss caused sustained noise. Since these signals are essential for eye cells to differentiate, we suggest that dynamic heterogeneity of Yan is a necessary element of the transition process, and cell states are stabilized through noise reduction.

Novel Reporter for Faithful Monitoring of ERK2 Dynamics in Living Cells and Model Organisms

Uncoupling of ERK1/2 phosphorylation from subcellular localization is essential towards the understanding of molecular mechanisms that control ERK1/2-mediated cell-fate decision. ERK1/2 non-catalytic functions and discoveries of new specific anchors responsible of the subcellular compartmentalization of ERK1/2 signaling pathway have been proposed as regulation mechanisms for which dynamic monitoring of ERK1/2 localization is necessary. However, studying the spatiotemporal features of ERK2, for instance, in different cellular processes in living cells and tissues requires a tool that can faithfully report on its subcellular distribution. We developed a novel molecular tool, ERK2-LOC, based on the T2A-mediated coexpression of strictly equimolar levels of eGFP-ERK2 and MEK1, to faithfully visualize ERK2 localization patterns. MEK1 and eGFP-ERK2 were expressed reliably and functionally both in vitro and in single living cells. We then assessed the subcellular distribution and mobility of ERK2-LOC using fluorescence microscopy in non-stimulated conditions and after activation/inhibition of the MAPK/ERK1/2 signaling pathway. Finally, we used our coexpression system in Xenopus laevis embryos during the early stages of development. This is the first report on MEK1/ERK2 T2A-mediated coexpression in living embryos, and we show that there is a strong correlation between the spatiotemporal subcellular distribution of ERK2-LOC and the phosphorylation patterns of ERK1/2. Our approach can be used to study the spatiotemporal localization of ERK2 and its dynamics in a variety of processes in living cells and embryonic tissues.

Fundamental limitation of the instantaneous approximation in fold-change detection models

The phenomenon of fold-change detection, or scale-invariance, is exhibited by a variety of sensory systems, in both bacterial and eukaryotic signalling pathways. It has been often remarked in the systems biology literature that certain systems whose output variables respond at a faster time scale than internal components give rise to an approximate scale-invariant behaviour, allowing approximate fold-change detection in stimuli. This study establishes a fundamental limitation of such a mechanism, showing that there is a minimal fold-change detection error that cannot be overcome, no matter how large the separation of time scales is. To illustrate this theoretically predicted limitation, the authors discuss two common biomolecular network motifs, an incoherent feedforward loop and a feedback system, as well as a published model of the chemotaxis signalling pathway of Dictyostelium discoideum.

Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features

Cell signaling dynamics and transcriptional regulatory activities are variable within specific cell types responding to an identical stimulus. In addition to studying the network interactions, there is much interest in utilizing single cell scale data to elucidate the non-random aspects of the variability involved in cellular decision making. Previous studies have considered the information transfer between the signaling and transcriptional domains based on an instantaneous relationship between the molecular activities. These studies predict a limited binary on/off encoding mechanism which underestimates the complexity of biological information processing, and hence the utility of single cell resolution data. Here we pursue a novel strategy that reformulates the information transfer problem as involving dynamic features of signaling rather than molecular abundances. We pursue a computational approach to test if and how the transcriptional regulatory activity patterns can be informative of the temporal history of signaling. Our analysis reveals (1) the dynamic features of signaling that significantly alter transcriptional regulatory patterns (encoding), and (2) the temporal history of signaling that can be inferred from single cell scale snapshots of transcriptional activity (decoding). Immediate early gene expression patterns were informative of signaling peak retention kinetics, whereas transcription factor activity patterns were informative of activation and deactivation kinetics of signaling. Moreover, the information processing aspects varied across the network, with each component encoding a selective subset of the dynamic signaling features. We developed novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components. Unsupervised clustering of the maps revealed two groups that aligned with network motifs distinguished by transcriptional feedforward vs feedback interactions. Our new computational methodology impacts the single cell scale experiments by identifying downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses.

Single cell studies have shown that differential patterns in the dynamics of signaling proteins, transcription factor activity, gene expression, etc. produce distinct downstream outcomes. The opposite also holds true where particular cellular outcomes have been found to be associated with the dynamical pattern of one or more signaling molecules. Signaling pathways, therefore, serve as signal processing units to inform specific downstream regulation. However, the functional capabilities of the dynamic aspects of signaling are not well understood. To address this issue, we developed a new approach that evaluates information processing between dynamic features in signaling patterns and transcriptional regulatory activity. Our work demonstrates that the information transfer occur through decoding of temporal history of signals rather than only through instantaneous correlations. Moreover, our results identify regulatory network motifs as the critical components in the information processing and filtering of variability in signaling dynamics to produce distinct patterns of downstream transcriptional responses. Our methodology can be broadly applied to single cell scale data on experimentally accessible downstream measures to infer dynamic aspects of upstream signaling.