The mitogen-activated protein kinase network, wired to dynamically function at multiple scales.

The mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling network is a key transducer of signals from various receptors, including receptor tyrosine kinases (RTKs). It controls cell-cycle entry, survival, motility, differentiation, as well as other fates. After four decades of studying this pathway with biochemical methods, the use of fluorescent biosensors has revealed dynamic behaviors such as ERK pulsing, oscillations, and amplitude-modulated activity. Different RTKs equip the MAPK network with specific feedback mechanisms to encode these different ERK dynamics, which are then subsequently decoded into cytoskeletal events and transcriptional programs, actuating cellular fates. Recently, collective ERK wave behaviors have been observed in multiple systems to coordinate cytoskeletal dynamics with fate decisions within cell collectives. This emphasizes that a correct understanding of this pathway requires studying it at multiple scales.

Transformer-based spatial-temporal detection of apoptotic cell death in live-cell imaging.

Intravital microscopy has revolutionized live-cell imaging by allowing the study of spatial-temporal cell dynamics in living animals. However, the complexity of the data generated by this technology has limited the development of effective computational tools to identify and quantify cell processes. Amongst them, apoptosis is a crucial form of regulated cell death involved in tissue homeostasis and host defense. Live-cell imaging enabled the study of apoptosis at the cellular level, enhancing our understanding of its spatial-temporal regulation. However, at present, no computational method can deliver robust detection of apoptosis in microscopy timelapses. To overcome this limitation, we developed ADeS, a deep learning-based apoptosis detection system that employs the principle of activity recognition. We trained ADeS on extensive datasets containing more than 10,000 apoptotic instances collected both in vitro and in vivo, achieving a classification accuracy above 98% and outperforming state-of-the-art solutions. ADeS is the first method capable of detecting the location and duration of multiple apoptotic events in full microscopy timelapses, surpassing human performance in the same task. We demonstrated the effectiveness and robustness of ADeS across various imaging modalities, cell types, and staining techniques. Finally, we employed ADeS to quantify cell survival in vitro and tissue damage in mice, demonstrating its potential application in toxicity assays, treatment evaluation, and inflammatory dynamics. Our findings suggest that ADeS is a valuable tool for the accurate detection and quantification of apoptosis in live-cell imaging and, in particular, intravital microscopy data, providing insights into the complex spatial-temporal regulation of this process.

Automatic detection of spatio-temporal signaling patterns in cell collectives.

Increasing experimental evidence points to the physiological importance of space-time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.

The MAPK/ERK channel capacity exceeds 6 bit/hour.

Living cells utilize signaling pathways to sense, transduce, and process information. As the extracellular stimulation often has rich temporal characteristics which may govern dynamic cellular responses, it is important to quantify the rate of information flow through the signaling pathways. In this study, we used an epithelial cell line expressing a light-activatable FGF receptor and an ERK activity reporter to assess the ability of the MAPK/ERK pathway to transduce signal encoded in a sequence of pulses. By stimulating the cells with random light pulse trains, we demonstrated that the MAPK/ERK channel capacity is at least 6 bits per hour. The input reconstruction algorithm detects the light pulses with 1-min accuracy 5 min after their occurrence. The high information transmission rate may enable the pathway to coordinate multiple processes including cell movement and respond to rapidly varying stimuli such as chemoattracting gradients created by other cells.

A Dimerosesquiterpene and Sesquiterpene Lactones from Artemisia argyi Inhibiting Oncogenic PI3K/AKT Signaling in Melanoma Cells.

A library of more than 2500 plant extracts was screened for activity on oncogenic signaling in melanoma cells. The ethyl acetate extract from the aerial parts of Artemisia argyi displayed pronounced inhibition of the PI3K/AKT pathway. Active compounds were tracked with the aid of HPLC-based activity profiling, and altogether 21 active compounds were isolated, including one novel dimerosequiterpenoid (1), one new disesquiterpenoid (2), three new guaianolides (3-5), 12 known sesquiterpenoids (6-17), and four known flavonoids (19-22). A new eudesmanolide derivative (13b) was isolated as an artifact formed by methanolysis. Compound 1 is the first adduct comprising a sesquiterpene lactone and a methyl jasmonate moiety. The absolute configurations of compounds 1 and 3-18 were established by comparison of their experimental and calculated ECD spectra. The absolute configuration for 2 was determined by X-ray diffraction analysis. Guaianolide 8 was the most potent sesquiterpene lactone, inhibiting the PI3K/AKT pathway with an IC50 value of 8.9 ± 0.9 µM.

Flavonoids from Ericameria nauseosa inhibiting PI3K/AKT pathway in human melanoma cells.

The PI3K/AKT and MAPK/ERK pathways are frequently mutated in metastatic melanoma. In a screen of over 2500 plant extracts, the dichloromethane extract of Ericameria nauseosa significantly inhibited oncogenic activity of AKT in MM121224 human melanoma cells. This extract was analyzed by analytical HPLC, and the column effluent was fractionated and tested for activity to generate the so-called HPLC-based activity profile. Compounds eluting within active time-windows of the chromatogram were subsequently isolated in a larger scale to afford 11 flavones (1-11), four flavanones (12-15), two diterpenes (16, 17), and a seco-caryophyllene (18). All isolated compounds were tested for activity, whereby only flavonoids were found active. Of these, flavones were shown to be more active than the flavanones. The most potent flavone was compound 9, that was displaying an IC50 of 14.7 ± 1.4 µM on AKT activity in MM121224 cells. The terpenoids (16-18) were found to be inactive in the assay. Both diterpenes, a grindelic acid derivative (16) and an ent-neo-clerodane (17) were identified as new natural products. Their absolute configuration was established by ECD. Compound 17 is the first description of a clerodane type diterpene in the genus Ericameria.

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.

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.

Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics.

Combining single-cell measurements of ERK activity dynamics with perturbations provides insights into the MAPK network topology. We built circuits consisting of an optogenetic actuator to activate MAPK signaling and an ERK biosensor to measure single-cell ERK dynamics. This allowed us to conduct RNAi screens to investigate the role of 50 MAPK proteins in ERK dynamics. We found that the MAPK network is robust against most node perturbations. We observed that the ERK-RAF and the ERK-RSK2-SOS negative feedback operate simultaneously to regulate ERK dynamics. Bypassing the RSK2-mediated feedback, either by direct optogenetic activation of RAS, or by RSK2 perturbation, sensitized ERK dynamics to further perturbations. Similarly, targeting this feedback in a human ErbB2-dependent oncogenic signaling model increased the efficiency of a MEK inhibitor. The RSK2-mediated feedback is thus important for the ability of the MAPK network to produce consistent ERK outputs, and its perturbation can enhance the efficiency of MAPK inhibitors.

Combining Activity Profiling with Advanced Annotation to Accelerate the Discovery of Natural Products Targeting Oncogenic Signaling in Melanoma.

The discovery of bioactive natural products remains a time-consuming and challenging task. The ability to link high-confidence metabolite annotations in crude extracts with activity would be highly beneficial to the drug discovery process. To address this challenge, HPLC-based activity profiling and advanced UHPLC-HRMS/MS metabolite profiling for annotation were combined to leverage the information obtained from both approaches on a crude extract scaled down to the submilligram level. This strategy was applied to a subset of an extract library screening aiming to identify natural products inhibiting oncogenic signaling in melanoma. Advanced annotation and data organization enabled the identification of compounds that were likely responsible for the activity in the extracts. These compounds belonged to two different natural product scaffolds, namely, brevipolides from a Hyptis brevipes extract and methoxylated flavonoids identified in three different extracts of Hyptis and Artemisia spp. Targeted isolation of these prioritized compounds led to five brevipolides and seven methoxylated flavonoids. Brevipolide A (1) and 6-methoxytricin (9) were the most potent compounds from each chemical class and displayed AKT activity inhibition with an IC50 of 17.6 ± 1.6 and 4.9 ± 0.2 µM, respectively.

High-Content Screening Pipeline for Natural Products Targeting Oncogenic Signaling in Melanoma.

The incidence of melanoma, the most fatal dermatological cancer, has dramatically increased over the last few decades. Modern targeted therapy with kinase inhibitors induces potent clinical responses, but drug resistance quickly develops. Combination therapy improves treatment outcomes. Therefore, novel inhibitors targeting aberrant proliferative signaling in melanoma via the MAPK/ERK and PI3K/AKT pathways are urgently needed. Biosensors were combined that report on ERK/AKT activity with image-based high-content screening and HPLC-based activity profiling. An in-house library of 2576 plant extracts was screened on two melanoma cell lines with different oncogenic mutations leading to pathological ERK/AKT activity. Out of 140 plant extract hits, 44 were selected for HPLC activity profiling. Active thymol derivatives and piperamides from Arnica montana and Piper nigrum were identified that inhibited pathological ERK and/or AKT activity. The pipeline used enabled an efficient identification of natural products targeting oncogenic signaling in melanoma.

Mining of Single-Cell Signaling Time-Series for Dynamic Phenotypes with Clustering.

Fluorescent live cell time-lapse microscopy is steadily contributing to our better understanding of the relationship between cell signaling and fate. However, large volumes of time-series data generated in these experiments and the heterogenous nature of signaling responses due to cell-cell variability hinder the exploration of such datasets. The population averages insufficiently describe the dynamics, yet finding prototypic dynamic patterns that relate to different cell fates is difficult when mining thousands of time-series. Here we demonstrate a protocol where we identify such dynamic phenotypes in a population of PC-12 cells that respond to a range of sustained growth factor perturbations. We use Time-Course Inspector, a free R/Shiny web application to explore and cluster single-cell time-series.

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.

Collective ERK/Akt activity waves orchestrate epithelial homeostasis by driving apoptosis-induced survival.

Cell death events continuously challenge epithelial barrier function yet are crucial to eliminate old or critically damaged cells. How such apoptotic events are spatio-temporally organized to maintain epithelial homeostasis remains unclear. We observe waves of extracellular-signal-regulated kinase (ERK) and AKT serine/threonine kinase (Akt) activity pulses that originate from apoptotic cells and propagate radially to healthy surrounding cells. This requires epidermal growth factor receptor (EGFR) and matrix metalloproteinase (MMP) signaling. At the single-cell level, ERK/Akt waves act as spatial survival signals that locally protect cells in the vicinity of the epithelial injury from apoptosis for a period of 3-4 h. At the cell population level, ERK/Akt waves maintain epithelial homeostasis (EH) in response to mild or intense environmental insults. Disruption of this spatial signaling system results in the inability of a model epithelial tissue to ensure barrier function in response to environmental insults.

CODEX, a neural network approach to explore signaling dynamics landscapes.

Current studies of cell signaling dynamics that use live cell fluorescent biosensors routinely yield thousands of single-cell, heterogeneous, multi-dimensional trajectories. Typically, the extraction of relevant information from time series data relies on predefined, human-interpretable features. Without a priori knowledge of the system, the predefined features may fail to cover the entire spectrum of dynamics. Here we present CODEX, a data-driven approach based on convolutional neural networks (CNNs) that identifies patterns in time series. It does not require a priori information about the biological system and the insights into the data are built through explanations of the CNNs' predictions. CODEX provides several views of the data: visualization of all the single-cell trajectories in a low-dimensional space, identification of prototypic trajectories, and extraction of distinctive motifs. We demonstrate how CODEX can provide new insights into ERK and Akt signaling in response to various growth factors, and we recapitulate findings in p53 and TGFß-SMAD2 signaling.

Systems analysis of RhoGEF and RhoGAP regulatory proteins reveals spatially organized RAC1 signalling from integrin adhesions.

Rho GTPases are central regulators of the cytoskeleton and, in humans, are controlled by 145 multidomain guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). How Rho signalling patterns are established in dynamic cell spaces to control cellular morphogenesis is unclear. Through a family-wide characterization of substrate specificities, interactomes and localization, we reveal at the systems level how RhoGEFs and RhoGAPs contextualize and spatiotemporally control Rho signalling. These proteins are widely autoinhibited to allow local regulation, form complexes to jointly coordinate their networks and provide positional information for signalling. RhoGAPs are more promiscuous than RhoGEFs to confine Rho activity gradients. Our resource enabled us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling CDC42-RHOA crosstalk. Moreover, we show that integrin adhesions spatially segregate GEFs and GAPs to shape RAC1 activity zones in response to mechanical cues. This mechanism controls the protrusion and contraction dynamics fundamental to cell motility. Our systems analysis of Rho regulators is key to revealing emergent organization principles of Rho signalling.

Mining single-cell time-series datasets with Time Course Inspector.

SUMMARY: Thanks to recent advances in live cell imaging of biosensors, microscopy experiments can generate thousands of single-cell time-series. To identify sub-populations with distinct temporal behaviours that correspond to different cell fates, we developed Time Course Inspector (TCI)-a unique tool written in R/Shiny to combine time-series analysis with clustering. With TCI it is convenient to inspect time-series, plot different data views and remove outliers. TCI facilitates interactive exploration of various hierarchical clustering and cluster validation methods. We showcase TCI by analysing a single-cell signalling time-series dataset acquired using a fluorescent biosensor. AVAILABILITY AND IMPLEMENTATION: https://github.com/pertzlab/shiny-timecourse-inspector. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Temporal perturbation of ERK dynamics reveals network architecture of FGF2/MAPK signaling.

Stimulation of PC-12 cells with epidermal (EGF) versus nerve (NGF) growth factors (GFs) biases the distribution between transient and sustained single-cell ERK activity states, and between proliferation and differentiation fates within a cell population. We report that fibroblast GF (FGF2) evokes a distinct behavior that consists of a gradually changing population distribution of transient/sustained ERK signaling states in response to increasing inputs in a dose response. Temporally controlled GF perturbations of MAPK signaling dynamics applied using microfluidics reveal that this wider mix of ERK states emerges through the combination of an intracellular feedback, and competition of FGF2 binding to FGF receptors (FGFRs) and heparan sulfate proteoglycan (HSPG) co-receptors. We show that the latter experimental modality is instructive for model selection using a Bayesian parameter inference. Our results provide novel insights into how different receptor tyrosine kinase (RTK) systems differentially wire the MAPK network to fine-tune fate decisions at the cell population level.

Developmental Erk Signaling Illuminated.

How a small number of signaling pathways can be re-used in distinct embryonic contexts to control different fates remains unclear. In this issue of Developmental Cell, Johnson and Toettcher (2019) use optogenetic approaches to explore how different dynamic ERK signaling states control specific developmental fates in the Drosophila embryo.

Automated profiling of growth cone heterogeneity defines relations between morphology and motility.

Growth cones are complex, motile structures at the tip of an outgrowing neurite. They often exhibit a high density of filopodia (thin actin bundles), which complicates the unbiased quantification of their morphologies by software. Contemporary image processing methods require extensive tuning of segmentation parameters, require significant manual curation, and are often not sufficiently adaptable to capture morphology changes associated with switches in regulatory signals. To overcome these limitations, we developed Growth Cone Analyzer (GCA). GCA is designed to quantify growth cone morphodynamics from time-lapse sequences imaged both in vitro and in vivo, but is sufficiently generic that it may be applied to nonneuronal cellular structures. We demonstrate the adaptability of GCA through the analysis of growth cone morphological variation and its relation to motility in both an unperturbed system and in the context of modified Rho GTPase signaling. We find that perturbations inducing similar changes in neurite length exhibit underappreciated phenotypic nuance at the scale of the growth cone.