High-Content Imaging Platform for Profiling Intracellular Signaling Network Activity in Living Cells

Reversing pathological cell states: the road less travelled can extend the therapeutic horizon

Acquisition of omics data advances at a formidable pace. Yet, our ability to utilize these data to control cell phenotypes and design interventions that reverse pathological states lags behind. Here, we posit that cell states are determined by core networks that control cell-wide networks. To steer cell fate decisions, core networks connecting genotype to phenotype must be reconstructed and understood. A recent method, cell state transition assessment and regulation (cSTAR), applies perturbation biology to quantify causal connections and mechanistically models how core networks influence cell phenotypes. cSTAR models are akin to digital cell twins enabling us to purposefully convert pathological states back to physiologically normal states. While this capability has a range of applications, here we discuss reverting oncogenic transformation.

Smart genetically-encoded biosensors for the chemical monitoring of living systems

Genetically-encoded biosensors provide the all-optical and non-invasive visualization of dynamic biochemical events within living systems, which has allowed the discovery of profound new insights. Twenty-five years of biosensor development has steadily improved their performance and has provided us with an ever increasing biosensor repertoire. In this feature article, we present recent advances made in biosensor development and provide a perspective on the future direction of the field.

Spectrally Tunable Förster Resonance Energy Transfer-Based Biosensors Using Organic Dye Grafting

Biosensors based on Förster resonance energy transfer (FRET) have revolutionized cellular biology by allowing the direct measurement of biochemical processes in situ. Many genetically encoded sensors make use of fluorescent proteins that are limited in spectral versatility and that allow few ways to change the spectral properties once the construct has been created. In this work, we developed genetically encoded FRET biosensors based on the chemigenetic SNAP and HaloTag domains combined with matching organic fluorophores. We found that the resulting constructs can display comparable responses, kinetics, and reversibility compared to their fluorescent protein-based ancestors, but with the added advantage of spectral versatility, including the availability of red-shifted dye pairs. However, we also find that the introduction of these tags can alter the sensor readout, showing that careful validation is required before applying such constructs in practice. Overall, our approach delivers an innovative methodology that can readily expand the spectral variety and versatility of FRET-based biosensors.

Identification of cell type-specific correlations between ERK activity and cell viability upon treatment with ERK1/2 inhibitors

Increased MAPK signaling is a hallmark of various cancers and is a central regulator of cell survival. Direct ERK1/2 inhibition is considered a promising approach to avoid ERK1/2 reactivation caused by upstream kinases BRAF, MEK1/2, and KRAS, as well as by receptor tyrosine kinase inhibitors, but the dynamics and selectivity of ERK1/2 inhibitors are much less studied compared with BRAF or MEK inhibitors. Using ERK1/2 and downstream kinase ELK1 reporter cell lines of lung cancer (H1299; NRAS^Q61K), colon cancer (HCT-116; KRAS^G13D), neuroblastoma (SH-SY5Y), and leukemia (U937), we examined the relationship between ERK inhibition and drug-induced toxicity for five ERK inhibitors: SCH772984, ravoxertinib, LY3214996, ulixertinib, and VX-11e, as well as one MEK inhibitor, PD0325901. Comparing cell viability and ERK inhibition revealed different ERK dependencies for these cell lines. We identify several drugs, such as SCH772984 and VX-11e, which induce excessive toxicity not directly related to ERK1/2 inhibition in specific cell lines. We also show that PD0325901, LY3214996, and ulixertinib are prone to ERK1/2 reactivation over time. We distinguished two types of ERK1/2 reactivation: the first could be reversed by adding a fresh dose of inhibitors, while the second persists even after additional treatments. We also showed that cells that became resistant to the MEK1/2 inhibitor PD0325901 due to ERK1/2 reactivation remained sensitive to ERK1/2 inhibitor ulixertinib. Our data indicate that correlation of ERK inhibition with drug-induced toxicity in multiple cell lines may help to find more selective and effective ERK1/2 inhibitors.

Single cell imaging of ERK and Akt activation dynamics and heterogeneity induced by G protein-coupled receptors

Kinases play key roles in signaling networks that are activated by G-protein-coupled receptors (GPCRs). Kinase activities are generally inferred from cell lysates, hiding cell-to-cell variability. To study the dynamics and heterogeneity of ERK and Akt proteins, we employed high-content biosensor imaging with kinase translocation reporters. The kinases were activated with GPCR ligands. We observed ligand concentration-dependent response kinetics to histamine, α2-adrenergic and S1P receptor stimulation. By using G-protein inhibitors, we observed that Gq mediated the ERK and Akt responses to histamine. In contrast, Gi was necessary for ERK and Akt activation in response to α2-adrenergic receptor activation. ERK and Akt were also strongly activated by S1P, showing high heterogeneity at the single-cell level, especially for ERK. Cluster analysis of time series derived from 68,000 cells obtained under the different conditions revealed several distinct populations of cells that display similar response dynamics. ERK response dynamics to S1P showed high heterogeneity, which was reduced by the inhibition of Gi. To conclude, we have set up an imaging and analysis strategy that reveals substantial cell-to-cell heterogeneity in kinase activity driven by GPCRs.

Summary: High-content biosensor imaging with kinase translocation reporters reveals substantial cell-to-cell heterogeneity in kinase activity driven by G-protein-coupled receptors.

Deciphering cell signaling networks with massively multiplexed biosensor barcoding

Genetically encoded fluorescent biosensors are powerful tools for monitoring biochemical activities in live cells, but their multiplexing capacity is limited by the available spectral space. We overcome this problem by developing a set of barcoding proteins that can generate over 100 barcodes and are spectrally separable from commonly used biosensors. Mixtures of barcoded cells expressing different biosensors are simultaneously imaged and analyzed by deep learning models to achieve massively multiplexed tracking of signaling events. Importantly, different biosensors in cell mixtures show highly coordinated activities, thus facilitating the delineation of their temporal relationship. Simultaneous tracking of multiple biosensors in the receptor tyrosine kinase signaling network reveals distinct mechanisms of effector adaptation, cell autonomous and non-autonomous effects of KRAS mutations, as well as complex interactions in the network. Biosensor barcoding presents a scalable method to expand multiplexing capabilities for deciphering the complexity of signaling networks and their interactions between cells.

Simultaneous readout of multiple FRET pairs using photochromism

Förster resonant energy transfer (FRET) is a powerful mechanism to probe associations in situ. Simultaneously performing more than one FRET measurement can be challenging due to the spectral bandwidth required for the donor and acceptor fluorophores. We present an approach to distinguish overlapping FRET pairs based on the photochromism of the donor fluorophores, even if the involved fluorophores display essentially identical absorption and emission spectra. We develop the theory underlying this method and validate our approach using numerical simulations. To apply our system, we develop rsAKARev, a photochromic biosensor for cAMP-dependent protein kinase (PKA), and combine it with the spectrally-identical biosensor EKARev, a reporter for extracellular signal-regulated kinase (ERK) activity, to deliver simultaneous readout of both activities in the same cell. We further perform multiplexed PKA, ERK, and calcium measurements by including a third, spectrally-shifted biosensor. Our work demonstrates that exploiting donor photochromism in FRET can be a powerful approach to simultaneously read out multiple associations within living cells.

Performing multiple FRET measurements at once can be challenging. Here the authors report a method to discriminate between overlapping FRET pairs, even if the fluorophores display almost identical absorption and emission spectra, based on the photochromism of the donor fluorophores.

Multiplexed Optical Sensors in Arrayed Islands of Cells for multimodal recordings of cellular physiology

Cells typically respond to chemical or physical perturbations via complex signaling cascades which can simultaneously affect multiple physiological parameters, such as membrane voltage, calcium, pH, and redox potential. Protein-based fluorescent sensors can report many of these parameters, but spectral overlap prevents more than ~4 modalities from being recorded in parallel. Here we introduce the technique, MOSAIC, Multiplexed Optical Sensors in Arrayed Islands of Cells, where patterning of fluorescent sensor-encoding lentiviral vectors with a microarray printer enables parallel recording of multiple modalities. We demonstrate simultaneous recordings from 20 sensors in parallel in human embryonic kidney (HEK293) cells and in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), and we describe responses to metabolic and pharmacological perturbations. Together, these results show that MOSAIC can provide rich multi-modal data on complex physiological responses in multiple cell types.

Profiling Cell Signaling Networks at Single-cell Resolution

Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.

PlotTwist: A web app for plotting and annotating continuous data

Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtained from measurements that are performed as a function of another quantitative variable, e.g., time, length, concentration, or wavelength. The results from these types of experiments are often used to generate plots that visualize the measured variable on a continuous, quantitative scale. To simplify state-of-the-art data visualization and annotation of data from such experiments, an open-source tool was created with R/shiny that does not require coding skills to operate it. The freely available web app accepts wide (spreadsheet) and tidy data and offers a range of options to normalize the data. The data from individual objects can be shown in 3 different ways: (1) lines with unique colors, (2) small multiples, and (3) heatmap-style display. Next to this, the mean can be displayed with a 95% confidence interval for the visual comparison of different conditions. Several color-blind-friendly palettes are available to label the data and/or statistics. The plots can be annotated with graphical features and/or text to indicate any perturbations that are relevant. All user-defined settings can be stored for reproducibility of the data visualization. The app is dubbed PlotTwist and runs locally or online: https://huygens.science.uva.nl/PlotTwist.

PlotTwist: A web app for plotting and annotating continuous data

Experimental data can broadly be divided in discrete or continuous data. Continuous data are obtained from measurements that are performed as a function of another quantitative variable, e.g., time, length, concentration, or wavelength. The results from these types of experiments are often used to generate plots that visualize the measured variable on a continuous, quantitative scale. To simplify state-of-the-art data visualization and annotation of data from such experiments, an open-source tool was created with R/shiny that does not require coding skills to operate it. The freely available web app accepts wide (spreadsheet) and tidy data and offers a range of options to normalize the data. The data from individual objects can be shown in 3 different ways: (1) lines with unique colors, (2) small multiples, and (3) heatmap-style display. Next to this, the mean can be displayed with a 95% confidence interval for the visual comparison of different conditions. Several color-blind-friendly palettes are available to label the data and/or statistics. The plots can be annotated with graphical features and/or text to indicate any perturbations that are relevant. All user-defined settings can be stored for reproducibility of the data visualization. The app is dubbed PlotTwist and runs locally or online: https://huygens.science.uva.nl/PlotTwist.

Physical biology of GPCR signalling dynamics inferred from fluorescence spectroscopy and imaging

The physical biology of G protein-coupled receptor (GPCR) signalling can be inferred from imaging of single molecules and single living cells. In this opinion paper, we highlight recent developments in technologies to study GPCR signalling in vitro and in cyto. We start from mobility and localisation characteristics of single receptors in membranes. Subsequently, we discuss the kinetics of shifts in receptor-conformation equilibrium due to allosteric binding events and G protein activation. We continue with recent insights into downstream signalling and the role of delayed negative feedback to suppress GPCR signalling. Finally, we discuss new strategies to reveal how the multiplex signalling responses of cells to ligand mixtures, mediated by their entire receptor arsenal, can be disentangled, using single-cell data.

Biofunctionalized Materials Featuring Feedforward and Feedback Circuits Exemplified by the Detection of Botulinum Toxin A

Feedforward and feedback loops are key regulatory elements in cellular signaling and information processing. Synthetic biology exploits these elements for the design of molecular circuits that enable the reprogramming and control of specific cellular functions. These circuits serve as a basis for the engineering of complex cellular networks, opening the door for numerous medical and biotechnological applications. Here, a similar principle is applied. Feedforward and positive feedback circuits are incorporated into biohybrid polymer materials in order to develop signal-sensing and signal-processing devices. This concept is exemplified by the detection of the proteolytic activity of the botulinum neurotoxin A. To this aim, site-specific proteases are incorporated into receiver, transmitter, and output materials, and their release, diffusion, and/or activation are wired according to a feedforward or a positive feedback circuit. The development of a quantitative mathematical model enables analysis and comparison of the performance of both systems. The flexible design could be easily adapted to detect other toxins or molecules of interest. Furthermore, cellular signaling or gene regulatory pathways could provide additional blueprints for the development of novel biohybrid circuits. Such information-processing, material-embedded biological circuits hold great promise for a variety of analytical, medical, or biotechnological applications.

Genetically Encoded Fluorescent Biosensors Illuminate the Spatiotemporal Regulation of Signaling Networks

Cellular signaling networks are the foundation which determines the fate and function of cells as they respond to various cues and stimuli. The discovery of fluorescent proteins over 25 years ago enabled the development of a diverse array of genetically encodable fluorescent biosensors that are capable of measuring the spatiotemporal dynamics of signal transduction pathways in live cells. In an effort to encapsulate the breadth over which fluorescent biosensors have expanded, we endeavored to assemble a comprehensive list of published engineered biosensors, and we discuss many of the molecular designs utilized in their development. Then, we review how the high temporal and spatial resolution afforded by fluorescent biosensors has aided our understanding of the spatiotemporal regulation of signaling networks at the cellular and subcellular level. Finally, we highlight some emerging areas of research in both biosensor design and applications that are on the forefront of biosensor development.

Optical tools for understanding the complexity of β-cell signalling and insulin release

Following stimulation, pancreatic β-cells must orchestrate a plethora of signalling events to ensure the appropriate release of insulin and maintenance of normal glucose homeostasis. Failure at any point in this cascade leads to impaired insulin secretion, elevated blood levels of glucose and eventually type 2 diabetes mellitus. Likewise, β-cell replacement or regeneration strategies for the treatment of both type 1 and type 2 diabetes mellitus might fail if the correct cell signalling phenotype cannot be faithfully recreated. However, current understanding of β-cell function is complicated because of the highly dynamic nature of their intracellular and intercellular signalling as well as insulin release itself. β-Cells must precisely integrate multiple signals stemming from multiple cues, often with differing intensities, frequencies and cellular and subcellular localizations, before converging these signals onto insulin exocytosis. In this respect, optical approaches with high resolution in space and time are extremely useful for properly deciphering the complexity of β-cell signalling. An increased understanding of β-cell signalling might identify new mechanisms underlying insulin release, with relevance for future drug therapy and de novo stem cell engineering of functional islets.

RNA Polymerase Tags To Monitor Multidimensional Protein-Protein Interactions Reveal Pharmacological Engagement of Bcl-2 Proteins

We report the development of a new technology for monitoring multidimensional protein-protein interactions (PPIs) inside live mammalian cells using split RNA polymerase (RNAP) tags. In this new system, a protein-of-interest is tagged with an N-terminal split RNAP (RNAPN), and multiple potential binding partners are each fused to orthogonal C-terminal RNAPs (RNAPC). Assembly of RNAPN with each RNAPC is highly dependent on interactions between the tagged proteins. Each PPI-mediated RNAPN-RNAPC assembly transcribes from a separate promoter on a supplied DNA substrate, thereby generating a unique RNA output signal for each PPI. We develop and validate this new approach in the context of the Bcl-2 family of proteins. These key regulators of apoptosis are important cancer mediators, but are challenging to therapeutically target due to imperfect selectivity that leads to either off-target toxicity or tumor resistance. We demonstrate binary (1 × 1) and ternary (1 × 2) Bcl-2 PPI analyses by imaging fluorescent protein translation from mRNA outputs. Next, we perform a 1 × 4 PPI network analysis by direct measurement of four unique RNA signals via RT-qPCR. Finally, we use these new tools to monitor pharmacological engagement of Bcl-2 protein inhibitors, and uncover inhibitor-dependent competitive PPIs. The split RNAP tags improve upon other protein fragment complementation (PFC) approaches by offering both multidimensionality and sensitive detection using nucleic acid amplification and analysis techniques. Furthermore, this technology opens new opportunities for synthetic biology applications due to the versatility of RNA outputs for cellular engineering applications.

Competitive ligands facilitate dissociation of the complex of bifunctional inhibitor and protein kinase

Dissociation of the complex of a ligand and a protein usually follows the kinetic profile of the first order process and the rate of dissociation is not affected by the presence of competitive ligands. We discovered that dissociation of the complex between a bifunctional ligand and a protein kinase (the catalytic subunit of cAMP-dependent protein kinase), an enzyme possessing 2 different substrate binding sites, was accelerated (facilitated) over 50-fold in the presence of competitive ligands at higher concentrations. Structurally diverse compounds revealed >10-fold different efficiency for acceleration of dissociation of the complex. These results show that the kinetic behavior of flexible biomolecular complexes possessing two spatially separated contact areas is highly dynamic. This property of biomolecular complexes should be carefully considered for effective application of bifunctional ligands for regulation of activity of target proteins in cells.