A Live-Cell Screen for Altered Erk Dynamics Reveals Principles of Proliferative Control

A Frequency Domain Analysis of the Growth Factor-Driven Extra-Cellular-Regulated Kinase (ERK) Pathway

The ERK pathway is an important biochemical cascade and acts as a master regulator of myriad cell processes including cell proliferation, differentiation, and survival. Early biochemical work established that the timing of ERK phosphorylation was an important determinant of PC12 cell fate, with extended phosphorylation (with nerve growth factor treatment) linked to differentiation but rapid on-off ERK phosphorylation kinetics (with epidermal growth factor treatment) linked to cell proliferation. Recent work from several laboratories has revealed that periodic forcing the phosphorylation of ERK with growth factors, light (optogenetics) or electronically can switch cell fate from proliferative to differentiated depending on type of stimulus (amplitude and frequency). Here, we take an ERK model and analyze it from the frequency domain perspective. The key is the transfer function, which provides a compact description of input (growth factor)-output (ERK activation) behavior over a range of input frequencies, allowing an understanding of system dynamics in terms of amplitude modulations, phase shifts, and signaling bandwidths. Our analysis of transfer functions indicates that, at normal receptor levels, the ERK pathway acts as a negative feedback amplifier to growth factor fluctuations, amplifying them at low receptor occupancy but suppressing them at high receptor occupancy. The frequency dependence is best described as a resonant low pass filter, which selectively filters out high frequency input oscillations. We use the transfer function to predict how different growth factor input dynamics shape ERK activation.

Reversible Optical Control of Receptor Tyrosine Kinase Activity and ERK Dynamics Using Azobenzene-Carrying DNA Aptamer Agonist

Receptor tyrosine kinases (RTKs) play a pivotal role in cell signaling through their activation via dimerization. Recent studies have demonstrated the importance of the temporal dynamics of RTK activity and downstream signals, such as ERK, in determining the cell fate. To better understand these dynamics, it is essential to develop methods capable of controlling the RTK activity with high temporal resolution. However, techniques for precisely modulating the activity of endogenous RTKs without requiring genetic modification remain insufficiently established. In this study, we developed a DNA aptamer agonist, Met-azo-aptamer, which enables reversible optical control of the activity of the c-Met receptor, a member of the RTK family. This was achieved by incorporating azobenzene, a photoisomerizable molecule, into a DNA aptamer that binds to c-Met. This design allows light-induced switching between the active and inactive structures of the aptamer. When the aptamer was applied to HeLa cells and exposed to ultraviolet or blue light, phosphorylation signals within the cells were activated in response to the light patterns. Furthermore, by variation of the light patterns, the Met-azo-aptamer successfully controlled the timing, amplitude, and duration of downstream ERK activation. The Met-azo-aptamer developed in this study offers a high-resolution method for investigating the relationship between RTK activation patterns and cell function or fate.

CDK2 activity crosstalk on the ERK kinase translocation reporter can be resolved computationally

The mitogen-activated protein kinase (MAPK) pathway integrates growth factor signaling through extracellular signal-regulated kinase (ERK) to control cell proliferation. To study ERK dynamics, many researchers use an ERK activity kinase translocation reporter (KTR). Our study reveals that this ERK KTR also partially senses cyclin-dependent kinase 2 (CDK2) activity, making it appear as if ERK activity rises as cells progress through the cell cycle. Through single-cell time-lapse imaging, we identified a residual ERK KTR signal that was eliminated by selective CDK2 inhibitors, indicating crosstalk from CDK2 onto the ERK KTR. By contrast, EKAREN5, a FRET-based ERK sensor, showed no CDK2 crosstalk. A related p38 KTR is also partly affected by CDK2 activity. To address this, we developed linear and non-linear computational correction methods that subtract CDK2 signal from the ERK and p38 KTRs. These findings will allow for more accurate quantification of MAPK activities, especially for studies of actively cycling cells.

Programmable promoter editing for precise control of transgene expression

Subtle changes in gene expression direct cells to distinct cellular states. Identifying and controlling dose-dependent transgenes require tools for precisely titrating expression. To this end, we developed a highly modular, extensible framework called DIAL for building editable promoters that allow for fine-scale, heritable changes in transgene expression. Using DIAL, we increase expression by recombinase-mediated excision of spacers between the binding sites of a synthetic zinc finger transcription factor and the core promoter. By nesting varying numbers and lengths of spacers, DIAL generates a tunable range of unimodal setpoints from a single promoter. Through small-molecule control of transcription factors and recombinases, DIAL supports temporally defined, user-guided control of transgene expression that is extensible to additional transcription factors. Lentiviral delivery of DIAL generates multiple setpoints in primary cells and iPSCs. As promoter editing generates stable states, DIAL setpoints are heritable, facilitating mapping of transgene levels to phenotypes. The DIAL framework opens new opportunities for tailoring transgene expression and improving the predictability and performance of gene circuits across diverse applications.

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events

Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.

Characterizing heterogeneous single-cell dose responses computationally and experimentally using threshold inhibition surfaces and dose-titration assays

Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs. We first explore the connection between population and single-cell dose responses using a computational model, revealing that multiple heterogeneous populations can yield nearly identical population dose responses. We demonstrate that a single-cell analysis method, which we term a threshold inhibition surface, can differentiate among these populations. To demonstrate the applicability of this method, we develop a dose-titration assay to measure dose responses in single cells. We apply this assay to breast cancer cells responding to phosphatidylinositol-3-kinase inhibition (PI3Ki), using clinically relevant PI3Kis on breast cancer cell lines expressing fluorescent biosensors for kinase activity. We demonstrate that MCF-7 breast cancer cells exhibit heterogeneous dose responses with some cells requiring over ten-fold higher concentrations than the population average to achieve inhibition. Our work reimagines dose-response relationships for cancer drugs in an emerging paradigm of single-cell tumor heterogeneity.

Machine learning inference of continuous single-cell state transitions during myoblast differentiation and fusion

Cells modify their internal organization during continuous state transitions, supporting functions from cell division to differentiation. However, tools to measure dynamic physiological states of individual transitioning cells are lacking. We combined live-cell imaging and machine learning to monitor ERK1/2-inhibited primary murine skeletal muscle precursor cells, that transition rapidly and robustly from proliferating myoblasts to post-mitotic myocytes and then fuse, forming multinucleated myotubes. Our models, trained using motility or actin intensity features from single-cell tracking data, effectively tracked real-time continuous differentiation, revealing that differentiation occurs 7.5-14.5 h post induction, followed by fusion ~3 h later. Co-inhibition of ERK1/2 and p38 led to differentiation without fusion. Our model inferred co-inhibition leads to terminal differentiation, indicating that p38 is specifically required for transitioning from terminal differentiation to fusion. Our model also predicted that co-inhibition leads to changes in actin dynamics. Mass spectrometry supported these in silico predictions and suggested novel fusion and maturation regulators downstream of differentiation. Collectively, this approach can be adapted to various biological processes to uncover novel links between dynamic single-cell states and their functional outcomes.

Opticool: Cutting-edge transgenic optical tools

Only a few short decades have passed since the sequencing of GFP, yet the modern repertoire of transgenically encoded optical tools implies an exponential proliferation of ever improving constructions to interrogate the subcellular environment. A myriad of tags for labeling proteins, RNA, or DNA have arisen in the last few decades, facilitating unprecedented visualization of subcellular components and processes. Development of a broad array of modern genetically encoded sensors allows real-time, in vivo detection of molecule levels, pH, forces, enzyme activity, and other subcellular and extracellular phenomena in ever expanding contexts. Optogenetic, genetically encoded optically controlled manipulation systems have gained traction in the biological research community and facilitate single-cell, real-time modulation of protein function in vivo in ever broadening, novel applications. While this field continues to explosively expand, references are needed to assist scientists seeking to use and improve these transgenic devices in new and exciting ways to interrogate development and disease. In this review, we endeavor to highlight the state and trajectory of the field of in vivo transgenic optical tools.

A guide to ERK dynamics, part 2: downstream decoding

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

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

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

Conditional fluorescent mouse translocation reporters for ERK1/2 and AKT signaling

Understanding how cells activate intracellular signaling pathways in response to external signals, such as growth factors, is a longstanding goal of cell and developmental biology. Recently, live-cell signaling reporters have greatly expanded our understanding of signaling dynamics in response to wide-ranging stimuli and chemical or genetic perturbation, both ex vivo (cell lines) and in vivo (whole embryos or animals). Among the many varieties of reporter systems, translocation reporters that change sub-cellular localization in response to pathway activation have received considerable attention for their ease of use compared to FRET systems and favorable response times compared to transcriptional reporters. We reasoned that mouse reporter lines expressed in a conditional fashion would be a useful addition to the arsenal of mouse genetic tools, as such lines remain undeveloped despite widespread use of these sensors. We therefore created and validated two novel mouse reporter lines at the ROSA26 locus. One expresses an ERK1/2 pathway reporter and a nuclear marker from a single transcript, while the second additionally expresses an AKT reporter in order to simultaneously interrogate both pathways.

Analysis of RAS and drug induced homo- and heterodimerization of RAF and KSR1 proteins in living cells using split Nanoluc luciferase

The dimerization of RAF kinases represents a key event in their activation cycle and in RAS/ERK pathway activation. Genetic, biochemical and structural approaches provided key insights into this process defining RAF signaling output and the clinical efficacy of RAF inhibitors (RAFi). However, methods reporting the dynamics of RAF dimerization in living cells and in real time are still in their infancy. Recently, split luciferase systems have been developed for the detection of protein-protein-interactions (PPIs), incl. proof-of-concept studies demonstrating the heterodimerization of the BRAF and RAF1 isoforms. Due to their small size, the Nanoluc luciferase moieties LgBiT and SmBiT, which reconstitute a light emitting holoenzyme upon fusion partner promoted interaction, appear as well-suited to study RAF dimerization. Here, we provide an extensive analysis of the suitability of the Nanoluc system to study the homo- and heterodimerization of BRAF, RAF1 and the related KSR1 pseudokinase. We show that KRAS^G12V promotes the homo- and heterodimerization of BRAF, while considerable KSR1 homo- and KSR1/BRAF heterodimerization already occurs in the absence of this active GTPase and requires a salt bridge between the CC-SAM domain of KSR1 and the BRAF-specific region. We demonstrate that loss-of-function mutations impairing key steps of the RAF activation cycle can be used as calibrators to gauge the dynamics of heterodimerization. This approach identified the RAS-binding domains and the C-terminal 14-3-3 binding motifs as particularly critical for the reconstitution of RAF mediated LgBiT/SmBiT reconstitution, while the dimer interface was less important for dimerization but essential for downstream signaling. We show for the first time that BRAF^V600E, the most common BRAF oncoprotein whose dimerization status is controversially portrayed in the literature, forms homodimers in living cells more efficiently than its wildtype counterpart. Of note, Nanoluc activity reconstituted by BRAF^V600E homodimers is highly sensitive to the paradox-breaking RAFi PLX8394, indicating a dynamic and specific PPI. We report the effects of eleven ERK pathway inhibitors on RAF dimerization, incl. third-generation compounds that are less-defined in terms of their dimer promoting abilities. We identify Naporafenib as a potent and long-lasting dimerizer and show that the split Nanoluc approach discriminates between type I, I^1/2 and II RAFi. Video Abstract.

A disordered tether to iLID improves photoswitchable protein patterning on model membranes

Reversible protein patterning on model membranes is important to reproduce spatiotemporal protein dynamics in vitro. An engineered version of iLID, disiLID, with a disordered domain as a membrane tether improves the recruitment of Nano under blue light and the reversibility in the dark, which enables protein patterning on membranes with higher spatiotemporal precision.

Live Imaging with Genetically Encoded Physiologic Sensors and Optogenetic Tools

Barrier tissues such as the epidermis employ complex signal transduction systems to execute morphogenetic programs and to rapidly respond to environmental cues to promote homeostasis. Recent advances in live-imaging techniques and tools allow precise spatial and temporal monitoring and manipulation of intracellular signaling cascades. Leveraging the chemistry of naturally occurring light-sensitive proteins, genetically encoded fluorescent biosensors have emerged as robust tools for visualizing dynamic signaling events. In contrast, optogenetic protein constructs permit laser-mediated control of signal receptors and effectors within live cells, organoids, and even model organisms. In this paper, we review the basic principles underlying novel biosensors and optogenetic tools and highlight how recent studies in cutaneous biology have leveraged these imaging strategies to illuminate the spatiotemporal signals regulating epidermal development, barrier formation, and tissue homeostasis.

Integration of intermittent calcium signals in T cells revealed by temporally patterned optogenetics

T cells become activated following one or multiple contacts with antigen-presenting cells. Calcium influx is a key signaling event elicited during these cellular interactions; however, it is unclear whether T cells recall and integrate calcium signals elicited during temporally separated contacts. To study the integration of calcium signals, we designed a programmable, multiplex illumination strategy for temporally patterned optogenetics (TEMPO). We found that a single round of calcium elevation was insufficient to promote nuclear factor of activated T cells (NFAT) activity and cytokine production in a T cell line. However, robust responses were detected after a second identical stimulation even when signals were separated by several hours. Our results suggest the existence of a biochemical memory of calcium signals in T cells that favors signal integration during temporally separated contacts and promote cytokine production. As illustrated here, TEMPO is a versatile approach for dissecting temporal integration in defined signaling pathways.

Application of Optogenetics to Probe the Signaling Dynamics of Cell Fate Decision-Making

The development of optogenetic control over signaling pathways has provided a unique opportunity to decode the role of signaling dynamics in cell fate programing. Here I present a protocol for decoding cell fates through systematic interrogation with optogenetics and visualization of signaling with live biosensors. Specifically, this is written for Erk control of cell fates using the optoSOS system in mammalian cells or Drosophila embryos, though it is intended to be adapted to apply generally for several optogenetic tools, pathways, and model systems. This guide focuses on calibrating these tools, tricks of their use, and using them to interrogate features which program cell fates.

Pooled genetic screens with image-based profiling

Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.

Relating individual cell division events to single-cell ERK and Akt activity time courses

Biochemical correlates of stochastic single-cell fates have been elusive, even for the well-studied mammalian cell cycle. We monitored single-cell dynamics of the ERK and Akt pathways, critical cell cycle progression hubs and anti-cancer drug targets, and paired them to division events in the same single cells using the non-transformed MCF10A epithelial line. Following growth factor treatment, in cells that divide both ERK and Akt activities are significantly higher within the S-G2 time window (~ 8.5-40 h). Such differences were much smaller in the pre-S-phase, restriction point window which is traditionally associated with ERK and Akt activity dependence, suggesting unappreciated roles for ERK and Akt in S through G2. Simple metrics of central tendency in this time window are associated with subsequent cell division fates. ERK activity was more strongly associated with division fates than Akt activity, suggesting Akt activity dynamics may contribute less to the decision driving cell division in this context. We also find that ERK and Akt activities are less correlated with each other in cells that divide. Network reconstruction experiments demonstrated that this correlation behavior was likely not due to crosstalk, as ERK and Akt do not interact in this context, in contrast to other transformed cell types. Overall, our findings support roles for ERK and Akt activity throughout the cell cycle as opposed to just before the restriction point, and suggest ERK activity dynamics may be more important than Akt activity dynamics for driving cell division in this non-transformed context.

Spatiotemporal control of ERK pulse frequency coordinates fate decisions during mammary acinar morphogenesis

The signaling events controlling proliferation, survival, and apoptosis during mammary epithelial acinar morphogenesis remain poorly characterized. By imaging single-cell ERK activity dynamics in MCF10A acini, we find that these fates depend on the average frequency of non-periodic ERK pulses. High pulse frequency is observed during initial acinus growth, correlating with rapid cell motility and proliferation. Subsequent decrease in motility correlates with lower ERK pulse frequency and quiescence. Later, during lumen formation, coordinated multicellular ERK waves emerge, correlating with high and low ERK pulse frequencies in outer surviving and inner dying cells, respectively. Optogenetic entrainment of ERK pulses causally connects high ERK pulse frequency with inner cell survival. Acini harboring the PIK3CA H1047R mutation display increased ERK pulse frequency and inner cell survival. Thus, fate decisions during acinar morphogenesis are coordinated by different spatiotemporal modalities of ERK pulse frequency.

Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer

Multicellular synchronization is a ubiquitous phenomenon in living systems. However, how noisy and heterogeneous behaviors of individual cells are integrated across a population toward multicellular synchronization is unclear. Here, we study the process of multicellular calcium synchronization of the endothelial cell monolayer in response to mechanical stimuli. We applied information theory to quantify the asymmetric information transfer between pairs of cells and defined quantitative measures to how single cells receive or transmit information within a multicellular network. Our analysis revealed that multicellular synchronization was established by gradual enhancement of information spread from the single cell to the multicellular scale. Synchronization was associated with heterogeneity in the cells' communication properties, reinforcement of the cells' state, and information flow. Altogether, we suggest a phenomenological model where cells gradually learn their local environment, adjust, and reinforce their internal state to stabilize the multicellular network architecture to support information flow from local to global scales toward multicellular synchronization.

Towards 'end-to-end' analysis and understanding of biological timecourse data

Petabytes of increasingly complex and multidimensional live cell and tissue imaging data are generated every year. These videos hold large promise for understanding biology at a deep and fundamental level, as they capture single-cell and multicellular events occurring over time and space. However, the current modalities for analysis and mining of these data are scattered and user-specific, preventing more unified analyses from being performed over different datasets and obscuring possible scientific insights. Here, we propose a unified pipeline for storage, segmentation, analysis, and statistical parametrization of live cell imaging datasets.

Putting in the Erk: Growth factor signaling and mesoderm morphogenesis

It has long been known that FGF signaling contributes to mesoderm formation, a germ layer found in triploblasts that is composed of highly migratory cells that give rise to muscles and to the skeletal structures of vertebrates. FGF signaling activates several pathways in the developing mesoderm, including transient activation of the Erk pathway, which triggers mesodermal fate specification through the induction of the gene brachyury and activates morphogenetic programs that allow mesodermal cells to position themselves in the embryo. In this review, we discuss what is known about the generation and interpretation of transient Erk signaling in mesodermal tissues across species. We focus specifically on mechanisms that translate the level and duration of Erk signaling into cell fate and cell movement instructions and discuss strategies for further interrogating the role that Erk signaling dynamics play in mesodermal gastrulation and morphogenesis.

Signalling dynamics, cell decisions, and homeostatic control in health and disease

Cell signalling engenders cells with the capability to receive and process information from the intracellular and extracellular environments, trigger and execute biological responses, and communicate with each other. Ultimately, cell signalling is responsible for maintaining homeostasis at the cellular, tissue and systemic level. For this reason, cell signalling is a topic of intense research efforts aimed to elucidate how cells coordinate transitions between states in developing and adult organisms in physiological and pathological conditions. Here, we review current knowledge of how cell signalling operates at multiple spatial and temporal scales, focusing on how single-cell analytical techniques reveal mechanisms underpinning cell-to-cell variability, signalling plasticity, and collective cellular responses.

ERK signaling dissolves ERF repression condensates in living embryos

Phase separation underlies the organization of the nucleus, including the biogenesis of nucleoli and the packaging of heterochromatin. Here we explore the regulation of transcription factor condensates involved in gene repression by ERK signaling in gastrulating embryos of a simple proto-vertebrate (Ciona). ERK signaling induces nuclear export of the transcriptional repressor Ets-2 repressive factor (ERF), which has been linked to various human developmental disorders. Using high-resolution imaging, we show that ERF is localized within discrete nuclear condensates that dissolve upon ERK activation. Interestingly, we observe dynamic pulses of assembly and dissociation during interphase, providing visualization of a nuclear phase separation process regulated by cell signaling. We discuss the implications of these observations for producing sharp on/off switches in gene activity and suppressing noise in cell-cell signaling events.

A synthetic gene circuit for imaging-free detection of signaling pulses

Cells employ intracellular signaling pathways to sense and respond to changes in their external environment. In recent years, live-cell biosensors have revealed complex pulsatile dynamics in many pathways, but studies of these signaling dynamics are limited by the necessity of live-cell imaging at high spatiotemporal resolution. Here, we describe an approach to infer pulsatile signaling dynamics from a single measurement in fixed cells using a pulse-detecting gene circuit. We computationally screened for circuits with the capability to selectively detect signaling pulses, revealing an incoherent feedforward topology that robustly performs this computation. We implemented the motif experimentally for the Erk signaling pathway using a single engineered transcription factor and fluorescent protein reporter. Our "recorder of Erk activity dynamics" (READer) responds sensitively to spontaneous and stimulus-driven Erk pulses. READer circuits open the door to permanently labeling transient, dynamic cell populations to elucidate the mechanistic underpinnings and biological consequences of signaling dynamics.

Intermittent ERK oscillations downstream of FGF in mouse embryonic stem cells

Signal transduction networks generate characteristic dynamic activities to process extracellular signals and guide cell fate decisions such as to divide or differentiate. The differentiation of pluripotent cells is controlled by FGF/ERK signaling. However, only a few studies have addressed the dynamic activity of the FGF/ERK signaling network in pluripotent cells at high time resolution. Here, we use live cell sensors in wild-type and Fgf4-mutant mouse embryonic stem cells to measure dynamic ERK activity in single cells, for defined ligand concentrations and differentiation states. These sensors reveal pulses of ERK activity. Pulsing patterns are heterogeneous between individual cells. Consecutive pulse sequences occur more frequently than expected from simple stochastic models. Sequences become more prevalent with higher ligand concentration, but are rarer in more differentiated cells. Our results suggest that FGF/ERK signaling operates in the vicinity of a transition point between oscillatory and non-oscillatory dynamics in embryonic stem cells. The resulting heterogeneous dynamic signaling activities add a new dimension to cellular heterogeneity that may be linked to divergent fate decisions in stem cell cultures.

Confocal Imaging of Single-Cell Signaling in Orthotopic Models of Ovarian Cancer

Ovarian cancer (OVCA) is frequently detected at late stages of disease, often with dissemination throughout the peritoneal cavity surface, abdomen, and ascites fluid. Tumor signaling via mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) pathways can promote OVCA progression and depend on local microenvironmental cues. To better study OVCA in situ within native tissue contexts, here we describe confocal microscopy techniques to image mouse models of intraperitoneal disease at a single-cell resolution. As a proof of principle demonstration, examples are highlighted for simultaneously imaging tumor vascularization, infiltrating and often immunosuppressive immune cells (tumor-associated macrophages), and OVCA kinase activity.

Substratum stiffness regulates Erk signaling dynamics through receptor-level control

The EGFR/Erk pathway is triggered by extracellular ligand stimulation, leading to stimulus-dependent dynamics of pathway activity. Although mechanical properties of the microenvironment also affect Erk activity, their effects on Erk signaling dynamics are poorly understood. Here, we characterize how the stiffness of the underlying substratum affects Erk signaling dynamics in mammary epithelial cells. We find that soft microenvironments attenuate Erk signaling, both at steady state and in response to epidermal growth factor (EGF) stimulation. Optogenetic manipulation at multiple signaling nodes reveals that intracellular signal transmission is largely unaffected by substratum stiffness. Instead, we find that soft microenvironments decrease EGF receptor (EGFR) expression and alter the amount and spatial distribution of EGF binding at cell membranes. Our data demonstrate that the mechanical microenvironment tunes Erk signaling dynamics via receptor-ligand interactions, underscoring how multiple microenvironmental signals are jointly processed through a highly conserved pathway that regulates tissue development, homeostasis, and disease progression.

Signalling dynamics in embryonic development

In multicellular organisms, cellular behaviour is tightly regulated to allow proper embryonic development and maintenance of adult tissue. A critical component in this control is the communication between cells via signalling pathways, as errors in intercellular communication can induce developmental defects or diseases such as cancer. It has become clear over the last years that signalling is not static but varies in activity over time. Feedback mechanisms present in every signalling pathway lead to diverse dynamic phenotypes, such as transient activation, signal ramping or oscillations, occurring in a cell type- and stage-dependent manner. In cells, such dynamics can exert various functions that allow organisms to develop in a robust and reproducible way. Here, we focus on Erk, Wnt and Notch signalling pathways, which are dynamic in several tissue types and organisms, including the periodic segmentation of vertebrate embryos, and are often dysregulated in cancer. We will discuss how biochemical processes influence their dynamics and how these impact on cellular behaviour within multicellular systems.

Design and implementation of a microfluidic device capable of temporal growth factor delivery reveal filtering capabilities of the EGFR/ERK pathway

Utilizing microfluidics to mimic the dynamic temporal changes of growth factor and cytokine concentrations in vivo has greatly increased our understanding of how signal transduction pathways are structured to encode extracellular stimuli. To date, these devices have focused on delivering pulses of varying frequency, and there are limited cell culture models for delivering slowly increasing concentrations of stimuli that cells may experience in vivo. To examine this setting, we developed and validated a microfluidic device that can deliver increasing concentrations of growth factor over periods ranging from 6 to 24 h. Using this device and a fluorescent biosensor of extracellular-regulated kinase (ERK) activity, we delivered a slowly increasing concentration of epidermal growth factor (EGF) to human mammary epithelial cells and surprisingly observed minimal ERK activation, even at concentrations that stimulate robust activity in bolus delivery. The cells remained unresponsive to subsequent challenges with EGF, and immunocytochemistry suggested that the loss of an epidermal growth factor receptor was responsible. Cells were then challenged with faster rates of change of EGF, revealing an increased ERK activity as a function of rate of change. Specifically, both the fraction of cells that responded and the length of ERK activation time increased with the rate of change. This microfluidic device fills a gap in the current repertoire of in vitro microfluidic devices and demonstrates that slower, more physiological changes in growth factor presentation can reveal new regulatory mechanisms for how signal transduction pathways encode changes in the extracellular growth factor milieu.

DNA origami patterning of synthetic T cell receptors reveals spatial control of the sensitivity and kinetics of signal activation

Receptor clustering plays a key role in triggering cellular activation, but the relationship between the spatial configuration of clusters and the elicitation of downstream intracellular signals remains poorly understood. We developed a DNA-origami-based system that is easily adaptable to other cellular systems and enables rich interrogation of responses to a variety of spatially defined inputs. Using a chimeric antigen receptor (CAR) T cell model system with relevance to cancer therapy, we studied signaling dynamics at single-cell resolution. We found that the spatial arrangement of receptors determines the ligand density threshold for triggering and encodes the temporal kinetics of signaling activities. We also showed that signaling sensitivity of a small cluster of high-affinity ligands is enhanced when surrounded by nonstimulating low-affinity ligands. Our results suggest that cells measure spatial arrangements of ligands, translate that information into distinct signaling dynamics, and provide insights into engineering immunotherapies.

Gene expression at a single-molecule level: implications for myelodysplastic syndromes and acute myeloid leukemia

Nongenetic heterogeneity, or gene expression stochasticity, is an important source of variability in biological systems. With the advent and improvement of single molecule resolution technologies, it has been shown that transcription dynamics and resultant transcript number fluctuations generate significant cell-to-cell variability that has important biological effects and may contribute substantially to both tissue homeostasis and disease. In this respect, the pathophysiology of stem cell-derived malignancies such as acute myeloid leukemia and myelodysplastic syndromes, which has historically been studied at the ensemble level, may require reevaluation. To that end, it is our aim in this review to highlight the results of recent single-molecule, biophysical, and systems studies of gene expression dynamics, with the explicit purpose of demonstrating how the insights from these basic science studies may help inform and progress the field of leukemia biology and, ultimately, research into novel therapies.

A self-exciting point process to study multicellular spatial signaling patterns

Multicellular organisms rely on spatial signaling among cells to drive their organization, development, and response to stimuli. Several models have been proposed to capture the behavior of spatial signaling in multicellular systems, but existing approaches fail to capture both the autonomous behavior of single cells and the interactions of a cell with its neighbors simultaneously. We propose a spatiotemporal model of dynamic cell signaling based on Hawkes processes-self-exciting point processes-that model the signaling processes within a cell and spatial couplings between cells. With this cellular point process (CPP), we capture both the single-cell pathway activation rate and the magnitude and duration of signaling between cells relative to their spatial location. Furthermore, our model captures tissues composed of heterogeneous cell types with different bursting rates and signaling behaviors across multiple signaling proteins. We apply our model to epithelial cell systems that exhibit a range of autonomous and spatial signaling behaviors basally and under pharmacological exposure. Our model identifies known drug-induced signaling deficits, characterizes signaling changes across a wound front, and generalizes to multichannel observations.

Synthetic gene circuits as tools for drug discovery

Within mammalian systems, there exists enormous opportunity to use synthetic gene circuits to enhance phenotype-based drug discovery, to map the molecular origins of disease, and to validate therapeutics in complex cellular systems. While drug discovery has relied on marker staining and high-content imaging in cell-based assays, synthetic gene circuits expand the potential for precision and speed. Here we present a vision of how circuits can improve the speed and accuracy of drug discovery by enhancing the efficiency of hit triage, capturing disease-relevant dynamics in cell-based assays, and simplifying validation and readouts from organoids and microphysiological systems (MPS). By tracking events and cellular states across multiple length and time scales, circuits will transform how we decipher the causal link between molecular events and phenotypes to improve the selectivity and sensitivity of cell-based assays.

Shedding light on developmental ERK signaling with genetically encoded biosensors

The extracellular signal-regulated kinase (ERK) pathway governs cell proliferation, differentiation and migration, and therefore plays key roles in various developmental and regenerative processes. Recent advances in genetically encoded fluorescent biosensors have unveiled hitherto unrecognized ERK activation dynamics in space and time and their functional importance mainly in cultured cells. However, ERK dynamics during embryonic development have still only been visualized in limited numbers of model organisms, and we are far from a sufficient understanding of the roles played by developmental ERK dynamics. In this Review, we first provide an overview of the biosensors used for visualization of ERK activity in live cells. Second, we highlight the applications of the biosensors to developmental studies of model organisms and discuss the current understanding of how ERK dynamics are encoded and decoded for cell fate decision-making.

Signaling, Deconstructed: Using Optogenetics to Dissect and Direct Information Flow in Biological Systems

Cells receive enormous amounts of information from their environment. How they act on this information-by migrating, expressing genes, or relaying signals to other cells-comprises much of the regulatory and self-organizational complexity found across biology. The "parts list" involved in cell signaling is generally well established, but how do these parts work together to decode signals and produce appropriate responses? This fundamental question is increasingly being addressed with optogenetic tools: light-sensitive proteins that enable biologists to manipulate the interaction, localization, and activity state of proteins with high spatial and temporal precision. In this review, we summarize how optogenetics is being used in the pursuit of an answer to this question, outlining the current suite of optogenetic tools available to the researcher and calling attention to studies that increase our understanding of and improve our ability to engineer biology.

Emerging machine learning approaches to phenotyping cellular motility and morphodynamics

Cells respond heterogeneously to molecular and environmental perturbations. Phenotypic heterogeneity, wherein multiple phenotypes coexist in the same conditions, presents challenges when interpreting the observed heterogeneity. Advances in live cell microscopy allow researchers to acquire an unprecedented amount of live cell image data at high spatiotemporal resolutions. Phenotyping cellular dynamics, however, is a nontrivial task and requires machine learning (ML) approaches to discern phenotypic heterogeneity from live cell images. In recent years, ML has proven instrumental in biomedical research, allowing scientists to implement sophisticated computation in which computers learn and effectively perform specific analyses with minimal human instruction or intervention. In this review, we discuss how ML has been recently employed in the study of cell motility and morphodynamics to identify phenotypes from computer vision analysis. We focus on new approaches to extract and learn meaningful spatiotemporal features from complex live cell images for cellular and subcellular phenotyping.

Positive feedback between the T cell kinase Zap70 and its substrate LAT acts as a clustering-dependent signaling switch

Protein clustering is pervasive in cell signaling, yet how signaling from higher-order assemblies differs from simpler forms of molecular organization is still poorly understood. We present an optogenetic approach to switch between oligomers and heterodimers with a single point mutation. We apply this system to study signaling from the kinase Zap70 and its substrate linker for activation of T cells (LAT), proteins that normally form membrane-localized condensates during T cell activation. We find that fibroblasts expressing synthetic Zap70:LAT clusters activate downstream signaling, whereas one-to-one heterodimers do not. We provide evidence that clusters harbor a positive feedback loop among Zap70, LAT, and Src-family kinases that binds phosphorylated LAT and further activates Zap70. Finally, we extend our optogenetic approach to the native T cell signaling context, where light-induced LAT clustering is sufficient to drive a calcium response. Our study reveals a specific signaling function for protein clusters and identifies a biochemical circuit that robustly senses protein oligomerization state.

Dine et al. study how different modes of molecular organization contribute to cell signaling using the kinase Zap70 and its substrate LAT as a model system. Optogenetic manipulation reveals that LAT:Zap70 clusters—but not dimers—trigger potent signaling via localized positive feedback among LAT, Zap70, and Src-family kinases.

Computational methods for characterizing and learning from heterogeneous cell signaling data

Heterogeneity in cell signaling pathways is increasingly appreciated as a fundamental feature of cell biology and a driver of clinically relevant disease phenotypes. Understanding the causes of heterogeneity, the cellular mechanisms used to control heterogeneity, and the downstream effects of heterogeneity in single cells are all key obstacles for manipulating cellular populations and treating disease. Recent advances in genetic engineering, including multiplexed fluorescent reporters, have provided unprecedented measurements of signaling heterogeneity, but these vast data sets are often difficult to interpret, necessitating the use of computational techniques to extract meaning from the data. Here, we review recent advances in computational methods for extracting meaning from these novel data streams. In particular, we evaluate how machine learning methods related to dimensionality reduction and classification can identify structure in complex, dynamic datasets, simplifying interpretation. We also discuss how mechanistic models can be merged with heterogeneous data to understand the underlying differences between cells in a population. These methods are still being developed, but the work reviewed here offers useful applications of specific analysis techniques that could enable the translation of single-cell signaling data to actionable biological understanding.

Live-imaging of endothelial Erk activity reveals dynamic and sequential signalling events during regenerative angiogenesis

The formation of new blood vessel networks occurs via angiogenesis during development, tissue repair, and disease. Angiogenesis is regulated by intracellular endothelial signalling pathways, induced downstream of vascular endothelial growth factors (VEGFs) and their receptors (VEGFRs). A major challenge in understanding angiogenesis is interpreting how signalling events occur dynamically within endothelial cell populations during sprouting, proliferation, and migration. Extracellular signal-regulated kinase (Erk) is a central downstream effector of Vegf-signalling and reports the signalling that drives angiogenesis. We generated a vascular Erk biosensor transgenic line in zebrafish using a kinase translocation reporter that allows live-imaging of Erk-signalling dynamics. We demonstrate the utility of this line to live-image Erk activity during physiologically relevant angiogenic events. Further, we reveal dynamic and sequential endothelial cell Erk-signalling events following blood vessel wounding. Initial signalling is dependent upon Ca²⁺ in the earliest responding endothelial cells, but is independent of Vegfr-signalling and local inflammation. The sustained regenerative response, however, involves a Vegfr-dependent mechanism that initiates concomitantly with the wound inflammatory response. This work reveals a highly dynamic sequence of signalling events in regenerative angiogenesis and validates a new resource for the study of vascular Erk-signalling in real-time.

Cytokine combinations for human blood stem cell expansion induce cell type- and cytokine-specific signaling dynamics

How hematopoietic stem cells (HSCs) integrate signals from their environment to make fate decisions remains incompletely understood. Current knowledge is based on either averages of heterogeneous populations or snapshot analyses, both missing important information about the dynamics of intracellular signaling activity. By combining fluorescent biosensors with time-lapse imaging and microfluidics, we measured the activity of the extracellular signal-regulated kinase (ERK) pathway over time (i.e. dynamics) in live single human umbilical cord blood HSCs and multipotent progenitor cells (MPPs). In single cells, ERK signaling dynamics were highly heterogeneous and depended on the cytokines, their combinations, and cell types. ERK signaling was activated by SCF and FLT3L in HSCs, but by SCF, IL3 and GCSF in MPPs. Different cytokines and their combinations led to distinct ERK signaling dynamics frequencies, and ERK dynamics in HSCs were more transient than those in MPPs. A combination of 5 cytokines recently shown to maintain HSCs in long-term culture, had a more-than-additive effect in eliciting sustained ERK dynamics in HSCs. ERK signaling dynamics also predicted future cell fates. E.g. CD45RA expression increased more in HSC daughters with intermediate than with transient or sustained ERK signaling. We demonstrate heterogeneous, cytokine- and cell type- specific ERK signaling dynamics, illustrating their relevance in regulating HSPC fates.

Steering Molecular Activity with Optogenetics: Recent Advances and Perspectives

Optogenetics utilizes photosensitive proteins to manipulate the localization and interaction of molecules in living cells. Because light can be rapidly switched and conveniently confined to the sub-micrometer scale, optogenetics allows for controlling cellular events with an unprecedented resolution in time and space. The past decade has witnessed an enormous progress in the field of optogenetics within the biological sciences. The ever-increasing amount of optogenetic tools, however, can overwhelm the selection of appropriate optogenetic strategies. Considering that each optogenetic tool may have a distinct mode of action, a comparative analysis of the current optogenetic toolbox can promote the further use of optogenetics, especially by researchers new to this field. This review provides such a compilation that highlights the spatiotemporal accuracy of current optogenetic systems. Recent advances of optogenetics in live cells and animal models are summarized, the emerging work that interlinks optogenetics with other research fields is presented, and exciting clinical and industrial efforts to employ optogenetic strategy toward disease intervention are reported.

Functional Specificity of the Members of the Sos Family of Ras-GEF Activators: Novel Role of Sos2 in Control of Epidermal Stem Cell Homeostasis

Simple Summary

The Sos Ras-GEFs are known to participate in a wide range of skin-related diseases including cutaneous cancers, cardio-facio-cutaneous syndromes, or hirsutism. However, the specific functional roles played by the Sos1 and/or Sos2 family members in specific skin compartments remain largely unknown. This report aimed at precisely characterizing the specific functions played by Sos1 and/or Sos2 in keratinocytes, an essential cellular component of the skin. Our data show that Sos1 and Sos2 make overlapping contributions to both keratinocyte proliferation and survival. However, Sos1 seems to have a preferential involvement in regulating the ERK axis, whereas Sos2 seems to control the signaling output from the PI3K axis. We also uncovered an essential role of Sos2 in the control of the population of epidermal stem cells.

Abstract

Prior reports showed the critical requirement of Sos1 for epithelial carcinogenesis, but the specific functionalities of the homologous Sos1 and Sos2 GEFs in skin homeostasis and tumorigenesis remain unclear. Here, we characterize specific mechanistic roles played by Sos1 or Sos2 in primary mouse keratinocytes (a prevalent skin cell lineage) under different experimental conditions. Functional analyses of actively growing primary keratinocytes of relevant genotypes—WT, Sos1-KO, Sos2-KO, and Sos1/2-DKO—revealed a prevalent role of Sos1 regarding transcriptional regulation and control of RAS activation and mechanistic overlapping of Sos1 and Sos2 regarding cell proliferation and survival, with dominant contribution of Sos1 to the RAS-ERK axis and Sos2 to the RAS-PI3K/AKT axis. Sos1/2-DKO keratinocytes could not grow under 3D culture conditions, but single Sos1-KO and Sos2-KO keratinocytes were able to form pseudoepidermis structures that showed disorganized layer structure, reduced proliferation, and increased apoptosis in comparison with WT 3D cultures. Remarkably, analysis of the skin of both newborn and adult Sos2-KO mice uncovered a significant reduction of the population of stem cells located in hair follicles. These data confirm that Sos1 and Sos2 play specific, cell-autonomous functions in primary keratinocytes and reveal a novel, essential role of Sos2 in control of epidermal stem cell homeostasis.

Data science in cell imaging

Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Computation, traditionally used to quantitatively test specific hypotheses, must now also enable iterative hypothesis generation and testing by deciphering hidden biologically meaningful patterns in complex, dynamic or high-dimensional cell image data. Data science is uniquely positioned to aid in this process. In this Perspective, we survey the rapidly expanding new field of data science in cell imaging. Specifically, we highlight how data science tools are used within current image analysis pipelines, propose a computation-first approach to derive new hypotheses from cell image data, identify challenges and describe the next frontiers where we believe data science will make an impact. We also outline steps to ensure broad access to these powerful tools - democratizing infrastructure availability, developing sensitive, robust and usable tools, and promoting interdisciplinary training to both familiarize biologists with data science and expose data scientists to cell imaging.

The ERK mitogen-activated protein kinase signaling network: the final frontier in RAS signal transduction

The RAF-MEK-ERK mitogen-activated protein kinase (MAPK) cascade is aberrantly activated in a diverse set of human cancers and the RASopathy group of genetic developmental disorders. This protein kinase cascade is one of the most intensely studied cellular signaling networks and has been frequently targeted by the pharmaceutical industry, with more than 30 inhibitors either approved or under clinical evaluation. The ERK-MAPK cascade was originally depicted as a serial and linear, unidirectional pathway that relays extracellular signals, such as mitogenic stimuli, through the cytoplasm to the nucleus. However, we now appreciate that this three-tiered protein kinase cascade is a central core of a complex network with dynamic signaling inputs and outputs and autoregulatory loops. Despite our considerable advances in understanding the ERK-MAPK network, the ability of cancer cells to adapt to the inhibition of key nodes reveals a level of complexity that remains to be fully understood. In this review, we summarize important developments in our understanding of the ERK-MAPK network and identify unresolved issues for ongoing and future study.

Resonance energy transfer sensitises and monitors in situ switching of LOV2-based optogenetic actuators

Engineered light-dependent switches provide uniquely powerful opportunities to investigate and control cell regulatory mechanisms. Existing tools offer high spatiotemporal resolution, reversibility and repeatability. Cellular optogenetics applications remain limited with diffusible targets as the response of the actuator is difficult to independently validate. Blue light levels commonly needed for actuation can be cytotoxic, precluding long-term experiments. We describe a simple approach overcoming these obstacles. Resonance energy transfer can be used to constitutively or dynamically modulate actuation sensitivity. This simultaneously offers on-line monitoring of light-dependent switching and precise quantification of activation-relaxation properties in intact living cells. Applying this approach to different LOV2-based switches reveals that flanking sequences can lead to relaxation times up to 11-fold faster than anticipated. In situ–measured parameter values guide the design of target-inhibiting actuation trains with minimal blue-light exposure, and context-based optimisation can increase sensitivity and experimental throughput a further 10-fold without loss of temporal precision.

Cellular optogenetics applications are limited by difficulties in quantification and blue light toxicity. Here the authors design LOV2-based switches that use resonance energy transfer to overcome these concerns.

Optogenetic control of protein binding using light-switchable nanobodies

A growing number of optogenetic tools have been developed to reversibly control binding between two engineered protein domains. In contrast, relatively few tools confer light-switchable binding to a generic target protein of interest. Such a capability would offer substantial advantages, enabling photoswitchable binding to endogenous target proteins in cells or light-based protein purification in vitro. Here, we report the development of opto-nanobodies (OptoNBs), a versatile class of chimeric photoswitchable proteins whose binding to proteins of interest can be enhanced or inhibited upon blue light illumination. We find that OptoNBs are suitable for a range of applications including reversibly binding to endogenous intracellular targets, modulating signaling pathway activity, and controlling binding to purified protein targets in vitro. This work represents a step towards programmable photoswitchable regulation of a wide variety of target proteins.

Engineering combinatorial and dynamic decoders using synthetic immediate-early genes

Many cell- and tissue-level functions are coordinated by intracellular signaling pathways that trigger the expression of context-specific target genes. Yet the input–output relationships that link pathways to the genes they activate are incompletely understood. Mapping the pathway-decoding logic of natural target genes could also provide a basis for engineering novel signal-decoding circuits. Here we report the construction of synthetic immediate-early genes (SynIEGs), target genes of Erk signaling that implement complex, user-defined regulation and can be monitored by using live-cell biosensors to track their transcription and translation. We demonstrate the power of this approach by confirming Erk duration-sensing by FOS, elucidating how the BTG2 gene is differentially regulated by external stimuli, and designing a synthetic immediate-early gene that selectively responds to the combination of growth factor and DNA damage stimuli. SynIEGs pave the way toward engineering molecular circuits that decode signaling dynamics and combinations across a broad range of cellular contexts.

Ravindran et al. report the construction of synthetic immediate-early genes (SynIEGs), target genes of the Erk signaling pathway. SynIEGs implement user-defined regulation while tracking transcription and translation. This study underscores post-transcriptional regulation in signal decoding that may be masked by analyses of RNA abundance alone.

Development of light-responsive protein binding in the monobody non-immunoglobulin scaffold

Monobodies are synthetic non-immunoglobulin customizable protein binders invaluable to basic and applied research, and of considerable potential as future therapeutics and diagnostic tools. The ability to reversibly control their binding activity to their targets on demand would significantly expand their applications in biotechnology, medicine, and research. Here we present, as proof-of-principle, the development of a light-controlled monobody (OptoMB) that works in vitro and in cells and whose affinity for its SH2-domain target exhibits a 330-fold shift in binding affinity upon illumination. We demonstrate that our αSH2-OptoMB can be used to purify SH2-tagged proteins directly from crude E. coli extract, achieving 99.8% purity and over 40% yield in a single purification step. By virtue of their ability to be designed to bind any protein of interest, OptoMBs have the potential to find new powerful applications as light-switchable binders of untagged proteins with the temporal and spatial precision afforded by light.