Tracing Information Flow from Erk to Target Gene Induction Reveals Mechanisms of Dynamic and Combinatorial Control

Transient frequency preference responses in cell signaling systems

Ligand-receptor systems, covalent modification cycles, and transcriptional networks are the fundamental components of cell signaling and gene expression systems. While their behavior in reaching a steady-state regime under step-like stimulation is well understood, their response under repetitive stimulation, particularly at early time stages is poorly characterized. Yet, early-stage responses to external inputs are arguably as informative as late-stage ones. In simple systems, a periodic stimulation elicits an initial transient response, followed by periodic behavior. Transient responses are relevant when the stimulation has a limited time span, or when the stimulated component's timescale is slow as compared to the timescales of the downstream processes, in which case the latter processes may be capturing only those transients. In this study, we analyze the frequency response of simple motifs at different time stages. We use dose-conserved pulsatile input signals and consider different metrics versus frequency curves. We show that in ligand-receptor systems, there is a frequency preference response in some specific metrics during the transient stages, which is not present in the periodic regime. We suggest this is a general system-level mechanism that cells may use to filter input signals that have consequences for higher order circuits. In addition, we evaluate how the described behavior in isolated motifs is reflected in similar types of responses in cascades and pathways of which they are a part. Our studies suggest that transient frequency preferences are important dynamic features of cell signaling and gene expression systems, which have been overlooked.

Molecular regulation of PPARγ/RXRα signaling by the novel cofactor ZFP407

Cofactors interacting with PPARγ can regulate adipogenesis and adipocyte metabolism by modulating the transcriptional activity and selectivity of PPARγ signaling. ZFP407 was previously demonstrated to regulate PPARγ target genes such as GLUT4, and its overexpression improved glucose homeostasis in mice. Here, using a series of molecular assays, including protein-interaction studies, mutagenesis, and ChIP-seq, ZFP407 was found to interact with the PPARγ/RXRα protein complex in the nucleus of adipocytes. Consistent with this observation, ZFP407 ChIP-seq peaks significantly overlapped with PPARγ ChIP-seq peaks, with more than half of ZFP407 peaks overlapping with PPARγ peaks. Transcription factor binding motifs enriched in these overlapping sites included CTCF, RARα/RXRγ, TP73, and ELK1, which regulate cellular development and function within adipocytes. Site-directed mutagenesis of frequent PPARγ phosphorylation or SUMOylation sites did not prevent its regulation by ZFP407, while mutagenesis of ZFP407 domains potentially necessary for RXR and PPARγ binding abrogated any impact of ZFP407 on PPARγ activity. These data suggest that ZFP407 controls the activity of PPARγ, but does so independently of post-translational modifications, likely by direct binding, establishing ZFP407 as a newly identified PPARγ cofactor. In addition, ZFP407 ChIP-seq analyses identified regions that did not overlap with PPARγ peaks. These non-overlapping peaks were significantly enriched for the transcription factor binding motifs of TBX19, PAX8, HSF4, and ZKSCAN3, which may contribute to the PPARγ-independent functions of ZFP407 in adipocytes and other cell types.

Collective intelligence: A unifying concept for integrating biology across scales and substrates

A defining feature of biology is the use of a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, biology is not only nested structurally, but also functionally: each level is able to solve problems in distinct problem spaces, such as physiological, morphological, and behavioral state space. Percolating adaptive functionality from one level of competent subunits to a higher functional level of organization requires collective dynamics: multiple components must work together to achieve specific outcomes. Here we overview a number of biological examples at different scales which highlight the ability of cellular material to make decisions that implement cooperation toward specific homeodynamic endpoints, and implement collective intelligence by solving problems at the cell, tissue, and whole-organism levels. We explore the hypothesis that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. We then briefly outline the implications of this approach, and the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.

Deep model predictive control of gene expression in thousands of single cells

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phenotypes can be difficult to determine. Researchers have historically been limited to passive observations of natural dynamics, which can preclude studies of elusive and noisy cellular events where large amounts of data are required to reveal statistically significant effects. Here, using recent advances in the fields of machine learning and control theory, we train a deep neural network to accurately predict the response of an optogenetic system in Escherichia coli cells. We then use the network in a deep model predictive control framework to impose arbitrary and cell-specific gene expression dynamics on thousands of single cells in real time, applying the framework to generate complex time-varying patterns. We also showcase the framework's ability to link expression patterns to dynamic functional outcomes by controlling expression of the tetA antibiotic resistance gene. This study highlights how deep learning-enabled feedback control can be used to tailor distributions of gene expression dynamics with high accuracy and throughput without expert knowledge of the biological system.

Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements

The Ras/ERK pathway drives cell proliferation and other oncogenic behaviors, and quantifying its activity in situ is of high interest in cancer diagnosis and therapy. Pathway activation is often assayed by measuring phosphorylated ERK. However, this form of measurement overlooks dynamic aspects of signaling that can only be observed over time. In this study, we combine a live, single-cell ERK biosensor approach with multiplexed immunofluorescence staining of downstream target proteins to ask how well immunostaining captures the dynamic history of ERK activity. Combining linear regression, machine learning, and differential equation models, we develop an interpretive framework for immunostains, in which Fra-1 and pRb levels imply long term activation of ERK signaling, while Egr-1 and c-Myc indicate recent activation. We show that this framework can distinguish different classes of ERK dynamics within a heterogeneous population, providing a tool for annotating ERK dynamics within fixed tissues.

Extracellular Signal-Regulated Kinases: One Pathway, Multiple Fates

This comprehensive review delves into the multifaceted aspects of ERK signaling and the intricate mechanisms underlying distinct cellular fates. ERK1 and ERK2 (ERK) govern proliferation, transformation, epithelial-mesenchymal transition, differentiation, senescence, or cell death, contingent upon activation strength, duration, and context. The biochemical mechanisms underlying these outcomes are inadequately understood, shaped by signaling feedback and the spatial localization of ERK activation. Generally, ERK activation aligns with the Goldilocks principle in cell fate determination. Inadequate or excessive ERK activity hinders cell proliferation, while balanced activation promotes both cell proliferation and survival. Unraveling the intricacies of how the degree of ERK activation dictates cell fate requires deciphering mechanisms encompassing protein stability, transcription factors downstream of ERK, and the chromatin landscape.

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.

Dynamics of an incoherent feedforward loop drive ERK-dependent pattern formation in the early Drosophila embryo

Positional information in development often manifests as stripes of gene expression, but how stripes form remains incompletely understood. Here, we use optogenetics and live-cell biosensors to investigate the posterior brachyenteron (byn) stripe in early Drosophila embryos. This stripe depends on interpretation of an upstream ERK activity gradient and the expression of two target genes, tailless (tll) and huckebein (hkb), that exert antagonistic control over byn. We find that high or low doses of ERK signaling produce transient or sustained byn expression, respectively. Although tll transcription is always rapidly induced, hkb converts graded ERK inputs into a variable time delay. Nuclei thus interpret ERK amplitude through the relative timing of tll and hkb transcription. Antagonistic regulatory paths acting on different timescales are hallmarks of an incoherent feedforward loop, which is sufficient to explain byn dynamics and adds temporal complexity to the steady-state model of byn stripe formation. We further show that 'blurring' of an all-or-none stimulus through intracellular diffusion non-locally produces a byn stripe. Overall, we provide a blueprint for using optogenetics to dissect developmental signal interpretation in space and time.

Future medicine: from molecular pathways to the collective intelligence of the body

The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.

Deep Neural Networks for Predicting Single-Cell Responses and Probability Landscapes

Engineering biology relies on the accurate prediction of cell responses. However, making these predictions is challenging for a variety of reasons, including the stochasticity of biochemical reactions, variability between cells, and incomplete information about underlying biological processes. Machine learning methods, which can model diverse input-output relationships without requiring a priori mechanistic knowledge, are an ideal tool for this task. For example, such approaches can be used to predict gene expression dynamics given time-series data of past expression history. To explore this application, we computationally simulated single-cell responses, incorporating different sources of noise and alternative genetic circuit designs. We showed that deep neural networks trained on these simulated data were able to correctly infer the underlying dynamics of a cell response even in the presence of measurement noise and stochasticity in the biochemical reactions. The training set size and the amount of past data provided as inputs both affected prediction quality, with cascaded genetic circuits that introduce delays requiring more past data. We also tested prediction performance on a bistable auto-activation circuit, finding that our initial method for predicting a single trajectory was fundamentally ill-suited for multimodal dynamics. To address this, we updated the network architecture to predict the entire distribution of future states, showing it could accurately predict bimodal expression distributions. Overall, these methods can be readily applied to the diverse prediction tasks necessary to predict and control a variety of biological circuits, a key aspect of many synthetic biology applications.

Intensity-dependent gamma electrical stimulation regulates microglial activation, reduces beta-amyloid load, and facilitates memory in a mouse model of Alzheimer's disease

BACKGROUND

Gamma sensory stimulation may reduce AD-specific pathology. Yet, the efficacy of alternating electrical current stimulation in animal models of AD is unknown, and prior research has not addressed intensity-dependent effects.

METHODS

The intensity-dependent effect of gamma electrical stimulation (GES) with a sinusoidal alternating current at 40 Hz on Aβ clearance and microglia modulation were assessed in 5xFAD mouse hippocampus and cortex, as well as the behavioral performance of the animals with the Morris Water Maze.

RESULTS

One hour of epidural GES delivered over a month significantly (1) reduced Aβ load in the AD brain, (2) increased microglia cell counts, decreased cell body size, increased length of cellular processes of the Iba1 + cells, and (3) improved behavioral performance (learning & memory). All these effects were most pronounced when a higher stimulation current was applied.

CONCLUSION

The efficacy of GES on the reduction of AD pathology and the intensity-dependent feature provide guidance for the development of this promising therapeutic approach.

Optogenetic dissection of RET signaling reveals robust activation of ERK and enhanced filopodia-like protrusions of regenerating axons

RET (REarranged during Transfection) is a receptor tyrosine kinase that transduces various external stimuli into biological functions, such as survival and differentiation, in neurons. In the current study, we developed an optogenetic tool for modulating RET signaling, termed optoRET, combining the cytosolic region of human RET with a blue-light-inducible homo-oligomerizing protein. By varying the duration of photoactivation, we were able to dynamically modulate RET signaling. Activation of optoRET recruited Grb2 (growth factor receptor-bound protein 2) and stimulated AKT and ERK (extracellular signal-regulated kinase) in cultured neurons, evoking robust and efficient ERK activation. By locally activating the distal part of the neuron, we were able to retrogradely transduce the AKT and ERK signal to the soma and trigger formation of filopodia-like F-actin structures at stimulated regions through Cdc42 (cell division control 42) activation. Importantly, we successfully modulated RET signaling in dopaminergic neurons of the substantia nigra in the mouse brain. Collectively, optoRET has the potential to be developed as a future therapeutic intervention, modulating RET downstream signaling with light.

Heterostructures with Built-in Electric Fields for Long-lasting Chemodynamic Therapy

Sustained signal activation by hydroxyl radicals (⋅OH) has great significance, especially for tumor treatment, but remains challenging. Here, a built-in electric field (BIEF)-driven strategy was proposed for sustainable generation of ⋅OH, thereby achieving long-lasting chemodynamic therapy (LCDT). As a proof of concept, a novel Janus-like Fe@Fe₃ O₄ -Cu₂ O heterogeneous catalyst was designed and synthesized, in which the BIEF induced the transfer of electrons in the Fe core to the surface, reducing ≡Cu²⁺ to ≡Cu⁺ , thus achieving continuous Fenton-like reactions and ⋅OH release for over 18 h, which is approximately 12 times longer than that of Fe₃ O₄ -Cu₂ O and 72 times longer than that of Cu₂ O nanoparticles. In vitro and in vivo antitumor results indicated that sustained ⋅OH levels led to persistent extracellular regulated protein kinases (ERK) signal activation and irreparable oxidative damage to tumor cells, which promoted irreversible tumor apoptosis. Importantly, this strategy provides ideas for developing long-acting nanoplatforms for various applications.

Dynamic regulation of RAS and RAS signaling

RAS proteins regulate most aspects of cellular physiology. They are mutated in 30% of human cancers and 4% of developmental disorders termed Rasopathies. They cycle between active GTP-bound and inactive GDP-bound states. When active, they can interact with a wide range of effectors that control fundamental biochemical and biological processes. Emerging evidence suggests that RAS proteins are not simple on/off switches but sophisticated information processing devices that compute cell fate decisions by integrating external and internal cues. A critical component of this compute function is the dynamic regulation of RAS activation and downstream signaling that allows RAS to produce a rich and nuanced spectrum of biological outputs. We discuss recent findings how the dynamics of RAS and its downstream signaling is regulated. Starting from the structural and biochemical properties of wild-type and mutant RAS proteins and their activation cycle, we examine higher molecular assemblies, effector interactions and downstream signaling outputs, all under the aspect of dynamic regulation. We also consider how computational and mathematical modeling approaches contribute to analyze and understand the pleiotropic functions of RAS in health and disease.

Crosstalk between protein kinases AKT and ERK1/2 in human lung tumor-derived cell models

There is no doubt that cell signaling manipulation is a key strategy for anticancer therapy. Furthermore, cell state determines drug response. Thus, establishing the relationship between cell state and therapeutic sensitivity is essential for the development of cancer therapies. In the era of personalized medicine, the use of patient-derived ex vivo cell models is a promising approach in the translation of key research findings into clinics. Here, we were focused on the non-oncogene dependencies of cell resistance to anticancer treatments. Signaling-related mechanisms of response to inhibitors of MEK/ERK and PI3K/AKT pathways (regulators of key cellular functions) were investigated using a panel of patients' lung tumor-derived cell lines with various stemness- and EMT-related markers, varying degrees of ERK1/2 and AKT phosphorylation, and response to anticancer treatment. The study of interactions between kinases was the goal of our research. Although MEK/ERK and PI3K/AKT interactions are thought to be cell line-specific, where oncogenic mutations have a decisive role, we demonstrated negative feedback loops between MEK/ERK and PI3K/AKT signaling pathways in all cell lines studied, regardless of genotype and phenotype differences. Our work showed that various and distinct inhibitors of ERK signaling - selumetinib, trametinib, and SCH772984 - increased AKT phosphorylation, and conversely, inhibitors of AKT - capivasertib, idelalisib, and AKT inhibitor VIII - increased ERK phosphorylation in both control and cisplatin-treated cells. Interaction between kinases, however, was dependent on cellular state. The feedback between ERK and AKT was attenuated by the focal adhesion kinase inhibitor PF573228, and in cells grown in suspension, showing the possible role of extracellular contacts in the regulation of crosstalk between kinases. Moreover, studies have shown that the interplay between MEK/ERK and PI3K/AKT signaling pathways may be dependent on the strength of the chemotherapeutic stimulus. The study highlights the importance of spatial location of the cells and the strength of the treatment during anticancer therapy.

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.

Optimized Transcriptional Signature for Evaluation of MEK/ERK Pathway Baseline Activity and Long-Term Modulations in Ovarian Cancer

Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. The high activity of the MEK/ERK signaling pathway is tightly associated with tumor growth, high recurrence rate, and treatment resistance. Several transcriptional signatures were proposed recently for evaluation of MEK/ERK activity in tumor tissue. In the present study, we validated the performance of a robust multi-cancer MPAS 10-gene signature in various experimental models and publicly available sets of ovarian cancer samples. Expression of four MPAS genes (PHLDA1, DUSP4, EPHA2, and SPRY4) displayed reproducible responses to MEK/ERK activity modulations across several experimental models in vitro and in vivo. Levels of PHLDA1, DUSP4, and EPHA2 expression were also significantly associated with baseline levels of MEK/ERK pathway activity in multiple human ovarian cancer cell lines and ovarian cancer patient samples available from the TCGA database. Initial platinum therapy resistance and advanced age at diagnosis were independently associated with poor overall patient survival. Taken together, our results demonstrate that the performance of transcriptional signatures is significantly affected by tissue specificity and aspects of particular experimental models. We therefore propose that gene expression signatures derived from comprehensive multi-cancer studies should be always validated for each cancer type.

Signaling oscillations: Molecular mechanisms and functional roles

Mounting evidence shows that oscillatory activity is widespread in cell signaling. Here, we review some of this recent evidence, focusing on both the molecular mechanisms that potentially underlie such dynamical behavior, and the potential advantages that signaling oscillations might have in cell function. The biological processes considered include cellular differentiation and tissue maintenance, intermittent responses in pluripotent stem cells, and collective cell migration during wound healing. With the aid of mathematical modeling, we review recent examples in which delayed negative feedback has been seen to act as a unifying principle that underpins this wide variety of phenomena.

Information Theory as an Experimental Tool for Integrating Disparate Biophysical Signaling Modules

There is a growing appreciation in the fields of cell biology and developmental biology that cells collectively process information in time and space. While many powerful molecular tools exist to observe biophysical dynamics, biologists must find ways to quantitatively understand these phenomena at the systems level. Here, we present a guide for the application of well-established information theory metrics to biological datasets and explain these metrics using examples from cell, developmental and regenerative biology. We introduce a novel computational tool named after its intended purpose, calcium imaging, (CAIM) for simple, rigorous application of these metrics to time series datasets. Finally, we use CAIM to study calcium and cytoskeletal actin information flow patterns between Xenopus laevis embryonic animal cap stem cells. The tools that we present here should enable biologists to apply information theory to develop a systems-level understanding of information processing across a diverse array of experimental systems.

LITOS: a versatile LED illumination tool for optogenetic stimulation

Optogenetics has become a key tool to manipulate biological processes with high spatio-temporal resolution. Recently, a number of commercial and open-source multi-well illumination devices have been developed to provide throughput in optogenetics experiments. However, available commercial devices remain expensive and lack flexibility, while open-source solutions require programming knowledge and/or include complex assembly processes. We present a LED Illumination Tool for Optogenetic Stimulation (LITOS) based on an assembled printed circuit board controlling a commercially available 32 × 64 LED matrix as illumination source. LITOS can be quickly assembled without any soldering, and includes an easy-to-use interface, accessible via a website hosted on the device itself. Complex light stimulation patterns can easily be programmed without coding expertise. LITOS can be used with different formats of multi-well plates, petri dishes, and flasks. We validated LITOS by measuring the activity of the MAPK/ERK signaling pathway in response to different dynamic light stimulation regimes using FGFR1 and Raf optogenetic actuators. LITOS can uniformly stimulate all the cells in a well and allows for flexible temporal stimulation schemes. LITOS's affordability and ease of use aims at democratizing optogenetics in any laboratory.

Qualitative differences in disease-associated MEK mutants reveal molecular signatures and aberrant signaling-crosstalk in cancer

Point-mutations of MEK1, a central component of ERK signaling, are present in cancer and RASopathies, but their precise biological effects remain obscure. Here, we report a mutant MEK1 structure that uncovers the mechanisms underlying abnormal activities of cancer- and RASopathy-associated MEK1 mutants. These two classes of MEK1 mutations differentially impact on spatiotemporal dynamics of ERK signaling, cellular transcriptional programs, gene expression profiles, and consequent biological outcomes. By making use of such distinct characteristics of the MEK1 mutants, we identified cancer- and RASopathy-signature genes that may serve as diagnostic markers or therapeutic targets for these diseases. In particular, two AKT-inhibitor molecules, PHLDA1 and 2, are simultaneously upregulated by oncogenic ERK signaling, and mediate cancer-specific ERK-AKT crosstalk. The combined expression of PHLDA1/2 is critical to confer resistance to ERK pathway-targeted therapeutics on cancer cells. Finally, we propose a therapeutic strategy to overcome this drug resistance. Our data provide vital insights into the etiology, diagnosis, and therapeutic strategy of cancers and RASopathies.

Quantifying information of intracellular signaling: progress with machine learning

Cells convey information about their extracellular environment to their core functional machineries. Studying the capacity of intracellular signaling pathways to transmit information addresses fundamental questions about living systems. Here, we review how information-theoretic approaches have been used to quantify information transmission by signaling pathways that are functionally pleiotropic and subject to molecular stochasticity. We describe how recent advances in machine learning have been leveraged to address the challenges of complex temporal trajectory datasets and how these have contributed to our understanding of how cells employ temporal coding to appropriately adapt to environmental perturbations.

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.

Comparative whole-genome transcriptome analysis in renal cell populations reveals high tissue specificity of MAPK/ERK targets in embryonic kidney

Background

MAPK/ERK signaling is a well-known mediator of extracellular stimuli controlling intracellular responses to growth factors and mechanical cues. The critical requirement of MAPK/ERK signaling for embryonic stem cell maintenance is demonstrated, but specific functions in progenitor regulation during embryonic development, and in particular kidney development remain largely unexplored. We previously demonstrated MAPK/ERK signaling as a key regulator of kidney growth through branching morphogenesis and normal nephrogenesis where it also regulates progenitor expansion. Here, we performed RNA sequencing-based whole-genome expression analysis to identify transcriptional MAPK/ERK targets in two distinct renal populations: the ureteric bud epithelium and the nephron progenitors.

Results

Our analysis revealed a large number (5053) of differentially expressed genes (DEGs) in nephron progenitors and significantly less (1004) in ureteric bud epithelium, reflecting likely heterogenicity of cell types. The data analysis identified high tissue-specificity, as only a fraction (362) of MAPK/ERK targets are shared between the two tissues. Tissue-specific MAPK/ERK targets participate in the regulation of mitochondrial energy metabolism in nephron progenitors, which fail to maintain normal mitochondria numbers in the MAPK/ERK-deficient tissue. In the ureteric bud epithelium, a dramatic decline in progenitor-specific gene expression was detected with a simultaneous increase in differentiation-associated genes, which was not observed in nephron progenitors. Our experiments in the genetic model of MAPK/ERK deficiency provide evidence that MAPK/ERK signaling in the ureteric bud maintains epithelial cells in an undifferentiated state. Interestingly, the transcriptional targets shared between the two tissues studied are over-represented by histone genes, suggesting that MAPK/ERK signaling regulates cell cycle progression and stem cell maintenance through chromosome condensation and nucleosome assembly.

Conclusions

Using tissue-specific MAPK/ERK inactivation and RNA sequencing in combination with experimentation in embryonic kidneys, we demonstrate here that MAPK/ERK signaling maintains ureteric bud tip cells, suggesting a regulatory role in collecting duct progenitors. We additionally deliver new mechanistic information on how MAPK/ERK signaling regulates progenitor maintenance through its effects on chromatin accessibility and energy metabolism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01309-z.

Modulating gene regulation function by chemically controlled transcription factor clustering

Recent studies have suggested that transcriptional protein condensates (or clusters) may play key roles in gene regulation and cell fate determination. However, it remains largely unclear how the gene regulation function is quantitatively tuned by transcription factor (TF) clustering and whether TF clustering may confer emergent behaviors as in cell fate control systems. Here, to address this, we construct synthetic TFs whose clustering behavior can be chemically controlled. Through single-parameter tuning of the system (i.e., TF clustering propensity), we provide lines of evidence supporting the direct transcriptional activation and amplification of target genes by TF clustering. Single-gene imaging suggests that such amplification results from the modulation of transcriptional dynamics. Importantly, TF clustering propensity modulates the gene regulation function by significantly tuning the effective TF binding affinity and to a lesser extent the ultrasensitivity, contributing to bimodality and sustained response behavior that are reminiscent of canonical cell fate control systems. Collectively, these results demonstrate that TF clustering can modulate the gene regulation function to enable emergent behaviors, and highlight the potential applications of chemically controlled protein clustering.

Transcription factor (TF) condensates appear to be pervasive, yet their roles remain debated. Here, the authors use a synthetic biology approach to show that TF clusters causally amplify transcription and can confer bimodality and “memory”.

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.

Optogenetic control of the Bicoid morphogen reveals fast and slow modes of gap gene regulation

Developmental patterning networks are regulated by multiple inputs and feedback connections that rapidly reshape gene expression, limiting the information that can be gained solely from slow genetic perturbations. Here we show that fast optogenetic stimuli, real-time transcriptional reporters, and a simplified genetic background can be combined to reveal the kinetics of gene expression downstream of a developmental transcription factor in vivo. We engineer light-controlled versions of the Bicoid transcription factor and study their effects on downstream gap genes in embryos. Our results recapitulate known relationships, including rapid Bicoid-dependent transcription of giant and hunchback and delayed repression of Krüppel. In addition, we find that the posterior pattern of knirps exhibits a quick but inverted response to Bicoid perturbation, suggesting a noncanonical role for Bicoid in directly suppressing knirps transcription. Acute modulation of transcription factor concentration while recording output gene activity represents a powerful approach for studying developmental gene networks in vivo.

Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression

Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.

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.

The Red Edge: Bilin-Binding Photoreceptors as Optogenetic Tools and Fluorescence Reporters

This review adds the bilin-binding phytochromes to the Chemical Reviews thematic issue "Optogenetics and Photopharmacology". The work is structured into two parts. We first outline the photochemistry of the covalently bound tetrapyrrole chromophore and summarize relevant spectroscopic, kinetic, biochemical, and physiological properties of the different families of phytochromes. Based on this knowledge, we then describe the engineering of phytochromes to further improve these chromoproteins as photoswitches and review their employment in an ever-growing number of different optogenetic applications. Most applications rely on the light-controlled complex formation between the plant photoreceptor PhyB and phytochrome-interacting factors (PIFs) or C-terminal light-regulated domains with enzymatic functions present in many bacterial and algal phytochromes. Phytochrome-based optogenetic tools are currently implemented in bacteria, yeast, plants, and animals to achieve light control of a wide range of biological activities. These cover the regulation of gene expression, protein transport into cell organelles, and the recruitment of phytochrome- or PIF-tagged proteins to membranes and other cellular compartments. This compilation illustrates the intrinsic advantages of phytochromes compared to other photoreceptor classes, e.g., their bidirectional dual-wavelength control enabling instant ON and OFF regulation. In particular, the long wavelength range of absorption and fluorescence within the "transparent window" makes phytochromes attractive for complex applications requiring deep tissue penetration or dual-wavelength control in combination with blue and UV light-sensing photoreceptors. In addition to the wide variability of applications employing natural and engineered phytochromes, we also discuss recent progress in the development of bilin-based fluorescent proteins.

Chemical-Biology-derived in vivo Sensors: Past, Present, and Future

To understand the complex biochemistry and biophysics of biological systems, one needs to be able to monitor local concentrations of molecules, physical properties of macromolecular assemblies and activation status of signaling pathways, in real time, within single cells, and at high spatio-temporal resolution. Here we look at the tools that have been / are being / need to be provided by chemical biology to address these challenges. In particular, we highlight the utility of molecular probes that help to better measure mechanical forces and flux through key signalling pathways. Chemical biology can be used to both build biosensors to visualize, but also actuators to perturb biological processes. An emergent theme is the possibility to multiplex measurements of multiple cellular processes. Advances in microscopy automation now allow us to acquire datasets for 1000's of cells. This produces high dimensional datasets that require computer vision approaches that automate image analysis. The high dimensionality of these datasets are often not immediately accessible to human intuition, and, similarly to 'omics technologies, require statistical approaches for their exploitation. The field of biosensor imaging is therefore experiencing a multidisciplinary transition that will enable it to realize its full potential as a tool to provide a deeper appreciation of cell physiology.

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.

Electrically synchronizing and modulating the dynamics of ERK activation to regulate cell fate

Intracellular signaling dynamics play fundamental roles in cell biology. Precise modulation of the amplitude, duration, and frequency of signaling activation will be a powerful approach to investigate molecular mechanisms as well as to engineer signaling to control cell behaviors. Here, we showed a practical approach to achieve precise amplitude modulation (AM), frequency modulation (FM), and duration modulation (DM) of MAP kinase activation. Alternating current (AC) electrical stimulation induced synchronized ERK activation. Amplitude and duration of ERK activation were controlled by varying stimulation strength and duration. ERK activation frequencies were arbitrarily modulated with trains of short AC applications with accurately defined intervals. Significantly, ERK dynamics coded by well-designed AC can rewire PC12 cell fate independent of growth factors. This technique can be used to synchronize and modulate ERK activation dynamics, thus would offer a practical way to control cell behaviors in vivo without the use of biochemical agents or genetic manipulation.

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Alternating-current (AC) electric field activates ERK independently of growth factors

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AC stimulation length modulates the amplitude and duration of ERK activation

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On-off time interval of AC modulates the frequency of ERK activation peaks

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Electrical modulation of ERK dynamics promotes neuronal differentiation of PC12 cells

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.

Continuous variable responses and signal gating form kinetic bases for pulsatile insulin signaling and emergence of resistance

Evolutionarily conserved insulin signaling is central to nutrient sensing, storage, and utilization across tissues. Dysfunctional insulin signaling is associated with metabolic disorders, cancer, and aging. Hence, the pathway components have emerged as key targets for pharmacological interventions in addition to insulin administration itself. Despite this, activation–inactivation dynamics of individual components, which exert regulatory control in a physiological context, is poorly understood. Now, with our systems-based approach, we reveal kinetic parameters, which define the flow of information through both metabolic and growth-factor arms and thus determine signaling architecture. We also provide a kinetic basis for 1) the advantage of pulsatile-fasted insulin signaling that enables fed-insulin response and 2) the detrimental impact of repeat fed-insulin inputs that causes resistance.

Understanding kinetic control of biological processes is as important as identifying components that constitute pathways. Insulin signaling is central for almost all metazoans, and its perturbations are associated with various developmental disorders, metabolic diseases, and aging. While temporal phosphorylation changes and kinetic constants have provided some insights, constant or variable parameters that establish and maintain signal topology are poorly understood. Here, we report kinetic parameters that encode insulin concentration and nutrient-dependent flow of information using iterative experimental and mathematical simulation-based approaches. Our results illustrate how dynamics of distinct phosphorylation events collectively contribute to selective kinetic gating of signals and maximum connectivity of the signaling cascade under normo-insulinemic but not hyper-insulinemic states. In addition to identifying parameters that provide predictive value for maintaining the balance between metabolic and growth-factor arms, we posit a kinetic basis for the emergence of insulin resistance. Given that pulsatile insulin secretion during a fasted state precedes a fed response, our findings reveal rewiring of insulin signaling akin to memory and anticipation, which was hitherto unknown. Striking disparate temporal behavior of key phosphorylation events that destroy the topology under hyper-insulinemic states underscores the importance of unraveling regulatory components that act as bandwidth filters. In conclusion, besides providing fundamental insights, our study will help in identifying therapeutic strategies that conserve coupling between metabolic and growth-factor arms, which is lost in diseases and conditions of hyper-insulinemia.

Characteristic ERK1/2 signaling dynamics distinguishes necroptosis from apoptosis

ERK1/2 involvement in cell death remains unclear, although many studies have demonstrated the importance of ERK1/2 dynamics in determining cellular responses. To untangle how ERK1/2 contributes to two cell death programs, we investigated ERK1/2 signaling dynamics during hFasL-induced apoptosis and TNF-induced necroptosis in L929 cells. We observed that ERK1/2 inhibition sensitizes cells to apoptosis while delaying necroptosis. By monitoring ERK1/2 activity by live-cell imaging using an improved ERK1/2 biosensor (EKAR4.0), we reported differential ERK1/2 signaling dynamics between cell survival, apoptosis, and necroptosis. We also decrypted a temporally shifted amplitude- and frequency-modulated (AM/FM) ERK1/2 activity profile in necroptosis versus apoptosis. ERK1/2 inhibition, which disrupted ERK1/2 signaling dynamics, prevented TNF and IL-6 gene expression increase during TNF-induced necroptosis. Using an inducible cell line for activated MLKL, the final executioner of necroptosis, we showed ERK1/2 and its distinctive necroptotic ERK1/2 activity dynamics to be positioned downstream of MLKL.

New mouse models for high resolution and live imaging of planar cell polarity proteins in vivo

The collective polarization of cellular structures and behaviors across a tissue plane is a near universal feature of epithelia known as planar cell polarity (PCP). This property is controlled by the core PCP pathway, which consists of highly conserved membrane-associated protein complexes that localize asymmetrically at cell junctions. Here, we introduce three new mouse models for investigating the localization and dynamics of transmembrane PCP proteins: Celsr1, Fz6 and Vangl2. Using the skin epidermis as a model, we characterize and verify the expression, localization and function of endogenously tagged Celsr1-3xGFP, Fz6-3xGFP and tdTomato-Vangl2 fusion proteins. Live imaging of Fz6-3xGFP in basal epidermal progenitors reveals that the polarity of the tissue is not fixed through time. Rather, asymmetry dynamically shifts during cell rearrangements and divisions, while global, average polarity of the tissue is preserved. We show using super-resolution STED imaging that Fz6-3xGFP and tdTomato-Vangl2 can be resolved, enabling us to observe their complex localization along junctions. We further explore PCP fusion protein localization in the trachea and neural tube, and discover new patterns of PCP expression and localization throughout the mouse embryo.

Nongenetic control of receptor signaling dynamics using a DNA-based optochemical tool

Optochemical tools that can modulate the activity of the target protein provide an opportunity for studying and regulating the related biological processes. Here we present a DNA-based nongenetic optochemical tool that can control the dynamics of growth factor signaling. This photo-caged mimicry of growth factor can be a promising tool for elucidating a linkage between the dynamics of signaling and the resulting biological outcomes, as well as for manipulating cellular functions and the fate of living cells.

Frequency-preference response in covalent modification cycles under substrate sequestration conditions

Covalent modification cycles (CMCs) are basic units of signaling systems and their properties are well understood. However, their behavior has been mostly characterized in situations where the substrate is in excess over the modifying enzymes. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations, leading to substrate sequestration by the enzymes. In this enzyme-in-excess regime, CMCs have been shown to exhibit signal termination, the ability of the product to return to a stationary value lower than its peak in response to constant stimulation, while this stimulation is still active, with possible implications for the ability of systems to adapt to environmental inputs. We characterize the conditions leading to signal termination in CMCs in the enzyme-in-excess regime. We also demonstrate that this behavior leads to a preferred frequency response (band-pass filters) when the cycle is subjected to periodic stimulation, whereas the literature reports that CMCs investigated so far behave as low-pass filters. We characterize the relationship between signal termination and the preferred frequency response to periodic inputs and we explore the dynamic mechanism underlying these phenomena. Finally, we describe how the behavior of CMCs is reflected in similar types of responses in the cascades of which they are part. Evidence of protein abundance in vivo shows that enzymes and substrates are present in comparable concentrations, thus suggesting that signal termination and frequency-preference response to periodic inputs are also important dynamic features of cell signaling systems, which have been overlooked.

Oncogenic mutant RAS signaling activity is rescaled by the ERK/MAPK pathway

Activating mutations in RAS are present in ~ 30% of human tumors, and the resulting aberrations in ERK/MAPK signaling play a central role in oncogenesis. However, the form of these signaling changes is uncertain, with activating RAS mutants linked to both increased and decreased ERK activation in vivo. Rationally targeting the kinase activity of this pathway requires clarification of the quantitative effects of RAS mutations. Here, we use live‐cell imaging in cells expressing only one RAS isoform to quantify ERK activity with a new level of accuracy. We find that despite large differences in their biochemical activity, mutant KRAS isoforms within cells have similar ranges of ERK output. We identify roles for pathway‐level effects, including variation in feedback strength and feedforward modulation of phosphatase activity, that act to rescale pathway sensitivity, ultimately resisting changes in the dynamic range of ERK activity while preserving responsiveness to growth factor stimuli. Our results reconcile seemingly inconsistent reports within the literature and imply that the signaling changes induced by RAS mutations early in oncogenesis are subtle.

T cells selectively filter oscillatory signals on the minutes timescale

T cells experience complex temporal patterns of stimulus via receptor-ligand-binding interactions with surrounding cells. From these temporal patterns, T cells are able to pick out antigenic signals while establishing self-tolerance. Although features such as duration of antigen binding have been examined, our understanding of how T cells interpret signals with different frequencies or temporal stimulation patterns is relatively unexplored. We engineered T cells to respond to light as a stimulus by building an optogenetically controlled chimeric antigen receptor (optoCAR). We discovered that T cells respond to minute-scale oscillations of activation signal by stimulating optoCAR T cells with tunable pulse trains of light. Systematically scanning signal oscillation period from 1 to 150 min revealed that expression of CD69, a T cell activation marker, reached a local minimum at a period of ∼25 min (corresponding to 5 to 15 min pulse widths). A combination of inhibitors and genetic knockouts suggest that this frequency filtering mechanism lies downstream of the Erk signaling branch of the T cell response network and may involve a negative feedback loop that diminishes Erk activity. The timescale of CD69 filtering corresponds with the duration of T cell encounters with self-peptide-presenting APCs observed via intravital imaging in mice, indicating a potential functional role for temporal filtering in vivo. This study illustrates that the T cell signaling machinery is tuned to temporally filter and interpret time-variant input signals in discriminatory ways.

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.

In vivo Functional Genomics for Undiagnosed Patients: The Impact of Small GTPases Signaling Dysregulation at Pan-Embryo Developmental Scale

While individually rare, disorders affecting development collectively represent a substantial clinical, psychological, and socioeconomic burden to patients, families, and society. Insights into the molecular mechanisms underlying these disorders are required to speed up diagnosis, improve counseling, and optimize management toward targeted therapies. Genome sequencing is now unveiling previously unexplored genetic variations in undiagnosed patients, which require functional validation and mechanistic understanding, particularly when dealing with novel nosologic entities. Functional perturbations of key regulators acting on signals' intersections of evolutionarily conserved pathways in these pathological conditions hinder the fine balance between various developmental inputs governing morphogenesis and homeostasis. However, the distinct mechanisms by which these hubs orchestrate pathways to ensure the developmental coordinates are poorly understood. Integrative functional genomics implementing quantitative in vivo models of embryogenesis with subcellular precision in whole organisms contribute to answering these questions. Here, we review the current knowledge on genes and mechanisms critically involved in developmental syndromes and pediatric cancers, revealed by genomic sequencing and in vivo models such as insects, worms and fish. We focus on the monomeric GTPases of the RAS superfamily and their influence on crucial developmental signals and processes. We next discuss the effectiveness of exponentially growing functional assays employing tractable models to identify regulatory crossroads. Unprecedented sophistications are now possible in zebrafish, i.e., genome editing with single-nucleotide precision, nanoimaging, highly resolved recording of multiple small molecules activity, and simultaneous monitoring of brain circuits and complex behavioral response. These assets permit accurate real-time reporting of dynamic small GTPases-controlled processes in entire organisms, owning the potential to tackle rare disease mechanisms.

Optogenetic Approaches for the Spatiotemporal Control of Signal Transduction Pathways

Biological signals are sensed by their respective receptors and are transduced and processed by a sophisticated intracellular signaling network leading to a signal-specific cellular response. Thereby, the response to the signal depends on the strength, the frequency, and the duration of the stimulus as well as on the subcellular signal progression. Optogenetic tools are based on genetically encoded light-sensing proteins facilitating the precise spatiotemporal control of signal transduction pathways and cell fate decisions in the absence of natural ligands. In this review, we provide an overview of optogenetic approaches connecting light-regulated protein-protein interaction or caging/uncaging events with steering the function of signaling proteins. We briefly discuss the most common optogenetic switches and their mode of action. The main part deals with the engineering and application of optogenetic tools for the control of transmembrane receptors including receptor tyrosine kinases, the T cell receptor and integrins, and their effector proteins. We also address the hallmarks of optogenetics, the spatial and temporal control of signaling events.

Roadmap on biology in time varying environments

Biological organisms experience constantly changing environments, from sudden changes in physiology brought about by feeding, to the regular rising and setting of the Sun, to ecological changes over evolutionary timescales. Living organisms have evolved to thrive in this changing world but the general principles by which organisms shape and are shaped by time varying environments remain elusive. Our understanding is particularly poor in the intermediate regime with no separation of timescales, where the environment changes on the same timescale as the physiological or evolutionary response. Experiments to systematically characterize the response to dynamic environments are challenging since such environments are inherently high dimensional. This roadmap deals with the unique role played by time varying environments in biological phenomena across scales, from physiology to evolution, seeking to emphasize the commonalities and the challenges faced in this emerging area of research.

Quantifying persistence in the T-cell signaling network using an optically controllable antigen receptor

T cells discriminate between healthy and infected cells with remarkable sensitivity when mounting an immune response, which is hypothesized to depend on T cells combining stimuli from multiple antigen-presenting cell interactions into a more potent response. To quantify the capacity for T cells to accomplish this, we have developed an antigen receptor that is optically tunable within cell conjugates, providing control over the duration, and intensity of intracellular T-cell signaling. We observe limited persistence within the T-cell intracellular network on disruption of receptor input, with signals dissipating entirely in ~15 min, and directly show sustained proximal receptor signaling is required to maintain gene transcription. T cells thus primarily accumulate the outputs of gene expression rather than integrate discrete intracellular signals. Engineering optical control in a clinically relevant chimeric antigen receptor (CAR), we show that this limited signal persistence can be exploited to increase CAR-T cell activation threefold using pulsatile stimulation. Our results are likely to apply more generally to the signaling dynamics of other cellular networks.

Optogenetic delivery of trophic signals in a genetic model of Parkinson's disease

Optogenetics has been harnessed to shed new mechanistic light on current and future therapeutic strategies. This has been to date achieved by the regulation of ion flow and electrical signals in neuronal cells and neural circuits that are known to be affected by disease. In contrast, the optogenetic delivery of trophic biochemical signals, which support cell survival and are implicated in degenerative disorders, has never been demonstrated in an animal model of disease. Here, we reengineered the human and Drosophila melanogaster REarranged during Transfection (hRET and dRET) receptors to be activated by light, creating one-component optogenetic tools termed Opto-hRET and Opto-dRET. Upon blue light stimulation, these receptors robustly induced the MAPK/ERK proliferative signaling pathway in cultured cells. In PINK1B9 flies that exhibit loss of PTEN-induced putative kinase 1 (PINK1), a kinase associated with familial Parkinson's disease (PD), light activation of Opto-dRET suppressed mitochondrial defects, tissue degeneration and behavioral deficits. In human cells with PINK1 loss-of-function, mitochondrial fragmentation was rescued using Opto-dRET via the PI3K/NF-кB pathway. Our results demonstrate that a light-activated receptor can ameliorate disease hallmarks in a genetic model of PD. The optogenetic delivery of trophic signals is cell type-specific and reversible and thus has the potential to inspire novel strategies towards a spatio-temporal regulation of tissue repair.

Inferring the structures of signaling motifs from paired dynamic traces of single cells

Individual cells show variability in their signaling dynamics that often correlates with phenotypic responses, indicating that cell-to-cell variability is not merely noise but can have functional consequences. Based on this observation, we reasoned that cell-to-cell variability under the same treatment condition could be explained in part by a single signaling motif that maps different upstream signals into a corresponding set of downstream responses. If this assumption holds, then repeated measurements of upstream and downstream signaling dynamics in a population of cells could provide information about the underlying signaling motif for a given pathway, even when no prior knowledge of that motif exists. To test these two hypotheses, we developed a computer algorithm called MISC (Motif Inference from Single Cells) that infers the underlying signaling motif from paired time-series measurements from individual cells. When applied to measurements of transcription factor and reporter gene expression in the yeast stress response, MISC predicted signaling motifs that were consistent with previous mechanistic models of transcription. The ability to detect the underlying mechanism became less certain when a cell's upstream signal was randomly paired with another cell's downstream response, demonstrating how averaging time-series measurements across a population obscures information about the underlying signaling mechanism. In some cases, motif predictions improved as more cells were added to the analysis. These results provide evidence that mechanistic information about cellular signaling networks can be systematically extracted from the dynamical patterns of single cells.