A Brief History of Single-Particle Tracking of the Epidermal Growth Factor Receptor

Single molecule tracking based drug screening

The single-molecule tracking of transmembrane receptors in living cells has provided significant insights into signaling mechanisms, such as mobility and clustering upon their activation/inactivation, making it a potential screening method for drug discovery. Here we show that single-molecule tracking-based screening can be used to explore compounds both detectable and undetectable by conventional methods for disease-related receptors. Using an automated system for a fast large-scale single-molecule analysis, we screen for epidermal growth factor receptor (EGFR) from 1134 of FDA approved drugs. The 18 hit compounds include all EGFR-targeted tyrosine kinase inhibitors (TKIs) in the library that suppress any phosphorylation-dependent mobility shift of EGFR, proving the concept of this approach. The remaining hit compounds are not reported as EGFR-targeted drugs and do not inhibit EGF-induced EGFR phosphorylation. These non-TKI compounds affect the mobility and/or clustering of EGFR without EGF and induce EGFR internalization, to impede EGFR-dependent cell growth. Thus, single-molecule tracking provides an alternative modality for discovering therapeutics on various receptor functions with previously untargeted mechanisms.

Evaluation of particle tracking codes for dispersing particles in porous media

Particle tracking (PT) is a popular technique in microscopy, microfluidics and colloidal transport studies, where image analysis is used to reconstruct trajectories from bright spots in a video. The performance of many PT algorithms has been rigorously tested for directed and Brownian motion in open media. However, PT is frequently used to track particles in porous media where complex geometries and viscous flows generate particles with high velocity variability over time. Here, we present an evaluation of four PT algorithms for a simulated dispersion of particles in porous media across a range of particle speeds and densities. Of special note, we introduce a new velocity-based PT linking algorithm (V-TrackMat) that achieves high accuracy relative to the other PT algorithms. Our findings underscore that traditional statistics, which revolve around detection and linking proficiency, fall short in providing a holistic comparison of PT codes because they tend to underpenalize aggressive linking techniques. We further elucidate that all codes analyzed show a decrease in performance due to high speeds, particle densities, and trajectory noise. However, linking algorithms designed to harness velocity data show superior performance, especially in the case of high-speed advective motion. Lastly, we emphasize how PT error can influence transport analysis.

Trajectory Analysis in Single-Particle Tracking: From Mean Squared Displacement to Machine Learning Approaches

Single-particle tracking is a powerful technique to investigate the motion of molecules or particles. Here, we review the methods for analyzing the reconstructed trajectories, a fundamental step for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean squared displacement (MSD), highlighting the sometimes-neglected factors potentially affecting the accuracy of the results. We then report methods that exploit the distribution of parameters other than displacements, e.g., angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in the MSD analysis. Hidden Markov Models are also used for this purpose, and these allow for the identification of different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field-trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on a combination of the different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

Cholesterol suppresses spontaneous activation of EGFR-mediated signal transduction

Epidermal growth factor receptor (EGFR)-mediated signal transduction controls cell growth and proliferation. The signaling pathway is regulated so that it is activated only by external EGF stimuli, but the mechanisms that prevent EGF-independent spontaneous activation of EGFR-mediated signaling are unknown. Here we report cholesterol depletion activates EGFR-mediated signaling without EGF. We applied automated single-molecule imaging to EGFR and characterized the lateral diffusion and cluster formation on cholesterol-depleted and cholesterol-supplemented membranes. In cells in which cholesterol was depleted by methyl-β-cyclodextrin (MβCD) treatment, EGFR exhibited a reduction in lateral diffusion, an acceleration of cluster formation, and autophosphorylation without EGF. Concurrently, extracellular signal-regulated kinase (ERK), which is regulated by EGFR-mediated signaling, exhibited phosphorylation and nuclear translocation without EGF. These cholesterol depletion-induced changes were similar, albeit less efficient, to those that occurred with EGF stimulation in normal cells without MβCD, indicating the spontaneous activation of EGFR signaling. The exogenous supplementation of cholesterol suppressed the MβCD-induced spontaneous activation of EGFR and ERK nuclear translocation. Single-molecule imaging of EGFR in a large number of cells revealed cell-to-cell heterogeneity, with a sub-population showing a high ability for spontaneous activation. These results provide evidence that EGFR-mediated signaling is properly regulated by cholesterol metabolism to prevent uncontrolled spontaneous activation.

Variable-Angle Epifluorescence Microscopy for Single-Particle Tracking in the Plant ER

Single-particle tracking (SPT) of biomolecules in the plant endoplasmic reticulum has the potential to inform on the formation of protein-protein complexes, metabolons, and the transport of molecules through both the ER membrane and lumen. Plant cells are particularly challenging for observing and tracking single molecules due to their unique structure, size, and considerable autofluorescence. However, by using variable-angle or highly inclined epifluorescence microscopy (VAEM) and transient expression in tobacco, it is possible to observe single-particle dynamics in the ER. Selecting the appropriate fluorophore, and ensuring the correct fluorophore density in the ER, is essential for successful SPT. By using tuneable fluorophores, which can be photoconverted and photoactivated, it is possible to vary the density of visible fluorophores in the ER dynamically. Here we describe methods to prepare plant samples for VAEM and two methods for determining and analyzing single-particle tracks from VAEM time series.

Advanced optical imaging for the rational design of nanomedicines

Despite the enormous potential of nanomedicines to shape the future of medicine, their clinical translation remains suboptimal. Translational challenges are present in every step of the development pipeline, from a lack of understanding of patient heterogeneity to insufficient insights on nanoparticle properties and their impact on material-cell interactions. Here, we discuss how the adoption of advanced optical microscopy techniques, such as super-resolution optical microscopies, correlative techniques, and high-content modalities, could aid the rational design of nanocarriers, by characterizing the cell, the nanomaterial, and their interaction with unprecedented spatial and/or temporal detail. In this nanomedicine arena, we will discuss how the implementation of these techniques, with their versatility and specificity, can yield high volumes of multi-parametric data; and how machine learning can aid the rapid advances in microscopy: from image acquisition to data interpretation.

A perspective of fluorescence microscopy for cellular structural biology with EGFR as witness

The epidermal growth factor receptor (EGFR) is a poster child for the understanding of receptor behaviour, and of paramount importance to cell function and human health. Cloned almost forty years ago, the interest in EGFR's structure/function relationships remains unabated, not least because changes in oncogenic EGFR mutants are key drivers of the formation of lung and brain tumours. The structure of the assemblies formed by EGFR have been comprehensibly investigated by techniques such as high-resolution X-ray crystallography, NMR and all-atom molecular dynamics (MD) simulations. However, the complexity embedded in the portfolio of EGFR states that are only possible in the physiological environment of cells has often proved refractory to cell-free structural methods. Conversely, some key inroads made by quantitative fluorescence microscopy and super-resolution have depended on exploiting the wealth of structures available. Here, a brief personal perspective is provided on how quantitative fluorescence microscopy and super-resolution methods have cross-fertilised with cell-free-derived EGFR structural information. I primarily discuss areas in which my research group has made a contribution to fill gaps in EGFR's cellular structural biology and towards developing new tools to investigate macromolecular assemblies in cells.

Confinement of unliganded EGFR by tetraspanin nanodomains gates EGFR ligand binding and signaling

The epidermal growth factor receptor (EGFR) is a central regulator of cell physiology. EGFR is activated by ligand binding, triggering receptor dimerization, activation of kinase activity, and intracellular signaling. EGFR is transiently confined within various plasma membrane nanodomains, yet how this may contribute to regulation of EGFR ligand binding is poorly understood. To resolve how EGFR nanoscale compartmentalization gates ligand binding, we developed single-particle tracking methods to track the mobility of ligand-bound and total EGFR, in combination with modeling of EGFR ligand binding. In comparison to unliganded EGFR, ligand-bound EGFR is more confined and distinctly regulated by clathrin and tetraspanin nanodomains. Ligand binding to unliganded EGFR occurs preferentially in tetraspanin nanodomains, and disruption of tetraspanin nanodomains impairs EGFR ligand binding and alters the conformation of the receptor's ectodomain. We thus reveal a mechanism by which EGFR confinement within tetraspanin nanodomains regulates receptor signaling at the level of ligand binding.

The Utility of Fluorescence Recovery after Photobleaching (FRAP) to Study the Plasma Membrane

The plasma membrane of mammalian cells is involved in a wide variety of cellular processes, including, but not limited to, endocytosis and exocytosis, adhesion and migration, and signaling. The regulation of these processes requires the plasma membrane to be highly organized and dynamic. Much of the plasma membrane organization exists at temporal and spatial scales that cannot be directly observed with fluorescence microscopy. Therefore, approaches that report on the membrane's physical parameters must often be utilized to infer membrane organization. As discussed here, diffusion measurements are one such approach that has allowed researchers to understand the subresolution organization of the plasma membrane. Fluorescence recovery after photobleaching (or FRAP) is the most widely accessible method for measuring diffusion in a living cell and has proven to be a powerful tool in cell biology research. Here, we discuss the theoretical underpinnings that allow diffusion measurements to be used in elucidating the organization of the plasma membrane. We also discuss the basic FRAP methodology and the mathematical approaches for deriving quantitative measurements from FRAP recovery curves. FRAP is one of many methods used to measure diffusion in live cell membranes; thus, we compare FRAP with two other popular methods: fluorescence correlation microscopy and single-particle tracking. Lastly, we discuss various plasma membrane organization models developed and tested using diffusion measurements.

Nanomaterials for Fluorescence and Multimodal Bioimaging

Bioconjugated nanomaterials replace molecular probes in bioanalysis and bioimaging in vitro and in vivo. Nanoparticles of silica, metals, semiconductors, polymers, and supramolecular systems, conjugated with contrast agents and drugs for image-guided (MRI, fluorescence, PET, Raman, SPECT, photodynamic, photothermal, and photoacoustic) therapy infiltrate into preclinical and clinical settings. Small bioactive molecules like peptides, proteins, or DNA conjugated to the surfaces of drugs or probes help us to interface them with cells and tissues. Nevertheless, the toxicity and pharmacokinetics of nanodrugs, nanoprobes, and their components become the clinical barriers, underscoring the significance of developing biocompatible next-generation drugs and contrast agents. This account provides state-of-the-art advancements in the preparation and biological applications of bioconjugated nanomaterials and their molecular, cell, and in vivo applications. It focuses on the preparation, bioimaging, and bioanalytical applications of monomodal and multimodal nanoprobes composed of quantum dots, quantum clusters, iron oxide nanoparticles, and a few rare earth metal ion complexes.

Determination of oligomeric organization of membrane proteins from native membranes at nanoscale-spatial and single-molecule resolution

The oligomeric organization of membrane proteins in native cell membranes is a critical regulator of their function. High-resolution quantitative measurements of oligomeric assemblies and how they change under different conditions are indispensable to the understanding of membrane protein biology. We report a single-molecule imaging technique (Native-nanoBleach) to determine the oligomeric distribution of membrane proteins directly from native membranes at an effective spatial resolution of ∼10 nm. We achieved this by capturing target membrane proteins in "native nanodiscs" with their proximal native membrane environment using amphipathic copolymers. We established this method using structurally and functionally diverse membrane proteins with well-established stoichiometries. We then applied Native-nanoBleach to quantify the oligomerization status of a receptor tyrosine kinase (TrkA) and a small GTPase (KRas) under conditions of growth-factor binding or oncogenic mutations, respectively. Native-nanoBleach provides a sensitive, single-molecule platform to quantify membrane protein oligomeric distributions in native membranes at an unprecedented spatial resolution.

Field model for multistate lateral diffusion of various transmembrane proteins observed in living Dictyostelium cells

The lateral diffusion of transmembrane proteins on plasma membranes is a fundamental process for various cellular functions. Diffusion properties specific for individual protein species have been extensively studied, but the common features among protein species are poorly understood. Here, we systematically studied the lateral diffusion of various transmembrane proteins in the lower eukaryote Dictyostelium discoideum cells using a hidden Markov model for single-molecule trajectories obtained experimentally. As common features, all membrane proteins that had from one to ten transmembrane regions adopted three free diffusion states with similar diffusion coefficients regardless of their structural variability. All protein species reduced their mobility similarly upon the inhibition of microtubule or actin cytoskeleton dynamics, or myosin II. The relationship between protein size and the diffusion coefficient was consistent with the Saffman-Delbrück model, meaning that membrane viscosity is a major determinant of lateral diffusion, but protein size is not. These protein species-independent properties of multistate free diffusion were explained simply and quantitatively by free diffusion on the three membrane regions with different viscosities, which is in sharp contrast to the complex diffusion behavior of transmembrane proteins in higher eukaryotes.

Structure and dynamics of the EGFR/HER2 heterodimer

HER2 belongs to the human epidermal growth factor receptor tyrosine kinase family. Its overexpression or hyperactivation is a leading cause for multiple types of cancers. HER2 functions mainly through dimerization with other family members, such as EGFR. However, the molecular details for heterodimer assembly have not been completely understood. Here, we report cryo-EM structures of the EGF- and epiregulin-bound EGFR/HER2 ectodomain complexes at resolutions of 3.3 Å and 4.5 Å, respectively. Together with the functional analyses, we demonstrate that only the dimerization arm of HER2, but not that of EGFR, is essential for their heterodimer formation and signal transduction. Moreover, we analyze the differential membrane dynamics and transient interactions of endogenous EGFR and HER2 molecules in genome-edited cells using single-molecule live-cell imaging. Furthermore, we show that the interaction with HER2 could allow EGFR to resist endocytosis. Together, this work deepens our understanding of the unique structural properties and dynamics of the EGFR/HER2 complex.

Targeting the HER3 pseudokinase domain with small molecule inhibitors

HER3 is a potent oncogenic growth factor receptor belonging to the human epidermal growth factor (HER/EGFR) family of receptor tyrosine kinases. In contrast to other EGFR family members, HER3 is a pseudokinase, lacking functional kinase activity. As such, efforts to develop small molecule tyrosine kinase inhibitors against this family member have been limited. In response to HER3-specific growth factors such as neuregulin (NRG, also known as heregulin or HRG), HER3 must couple with catalytically active family members, including its preferred partner HER2. Dimerization of the intracellular HER2:HER3 kinase domains is a critical part of the activation mechanism and HER3 plays a specialized role as an allosteric activator of the active HER2 kinase partner. Intriguingly, many pseudokinases retain functionally important nucleotide binding capacity, despite loss of kinase activity. We demonstrated that occupation of the nucleotide pocket of the pseudokinase HER3 retains functional importance for growth factor signaling through oncogenic HER2:HER3 heterodimers. Mutation of the HER3 nucleotide pocket both disrupts signaling and disrupts HER2:HER3 dimerization. Conversely, ATP competitive drugs which bind to HER3, but not HER2, can stabilize HER2:HER3 dimers, induce signaling and promote cell growth in breast cancer models. This indicates a nucleotide-dependent conformational role for the HER3 kinase domain. Critically, our recent proof-of-concept work demonstrated that HER3-directed small molecule inhibitors can also disrupt HER2:HER3 dimerization and signaling, supporting the prospect that HER3 can be a direct drug target despite its lack of intrinsic activity. In this chapter we will describe methods for identifying and validating small molecule inhibitors against the HER3 pseudokinase.

It Takes More than Two to Tango: Complex, Hierarchal, and Membrane-Modulated Interactions in the Regulation of Receptor Tyrosine Kinases

The search for an understanding of how cell fate and motility are regulated is not a purely scientific undertaking, but it can also lead to rationally designed therapies against cancer. The discovery of tyrosine kinases about half a century ago, the subsequent characterization of certain transmembrane receptors harboring tyrosine kinase activity, and their connection to the development of human cancer ushered in a new age with the hope of finding a treatment for malignant diseases in the foreseeable future. However, painstaking efforts were required to uncover the principles of how these receptors with intrinsic tyrosine kinase activity are regulated. Developments in molecular and structural biology and biophysical approaches paved the way towards better understanding of these pathways. Discoveries in the past twenty years first resulted in the formulation of textbook dogmas, such as dimerization-driven receptor association, which were followed by fine-tuning the model. In this review, the role of molecular interactions taking place during the activation of receptor tyrosine kinases, with special attention to the epidermal growth factor receptor family, will be discussed. The fact that these receptors are anchored in the membrane provides ample opportunities for modulatory lipid-protein interactions that will be considered in detail in the second part of the manuscript. Although qualitative and quantitative alterations in lipids in cancer are not sufficient in their own right to drive the malignant transformation, they both contribute to tumor formation and also provide ways to treat cancer. The review will be concluded with a summary of these medical aspects of lipid-protein interactions.

Expectation maximization based framework for joint localization and parameter estimation in single particle tracking from segmented images

Single Particle Tracking (SPT) is a well known class of tools for studying the dynamics of biological macromolecules moving inside living cells. In this paper, we focus on the problem of localization and parameter estimation given a sequence of segmented images. In the standard paradigm, the location of the emitter inside each frame of a sequence of camera images is estimated using, for example, Gaussian fitting (GF), and these locations are linked to provide an estimate of the trajectory. Trajectories are then analyzed by using Mean Square Displacement (MSD) or Maximum Likelihood Estimation (MLE) techniques to determine motion parameters such as diffusion coefficients. However, the problems of localization and parameter estimation are clearly coupled. Motivated by this, we have created an Expectation Maximization (EM) based framework for simultaneous localization and parameter estimation. We demonstrate this framework through two representative methods, namely, Sequential Monte Carlo combined with Expectation Maximization (SMC-EM) and Unscented Kalman Filter combined with Expectation Maximization (U-EM). Using diffusion in two-dimensions as a prototypical example, we conduct quantitative investigations on localization and parameter estimation performance across a wide range of signal to background ratios and diffusion coefficients and compare our methods to the standard techniques based on GF-MSD/MLE. To demonstrate the flexibility of the EM based framework, we do comparisons using two different camera models, an ideal camera with Poisson distributed shot noise but no readout noise, and a camera with both shot noise and the pixel-dependent readout noise that is common to scientific complementary metal-oxide semiconductor (sCMOS) camera. Our results indicate our EM based methods outperform the standard techniques, especially at low signal levels. While U-EM and SMC-EM have similar accuracy, U-EM is significantly more computationally efficient, though the use of the Unscented Kalman Filter limits U-EM to lower diffusion rates.

Epidermal Growth Factor Receptor: Key to Selective Intracellular Delivery

Epidermal growth factor receptor (EGFR) is an integral surface protein mediating cellular response to a number of growth factors. Its overexpression and increased activation due to mutations is one of the most common traits of many types of cancer. Development and clinical use of the agents, which block EGFR activation, became a prime example of the personalized targeted medicine. However, despite the obvious success in this area, cancer cure remains unattainable in most cases. Because of that, as well as the result of the search for possible ways to overcome the difficulties of treatment, a huge number of new treatment methods relying on the use of EGFR overexpression and its changes to destroy cancer cells. Modern data on the structure, functioning, and intracellular transport of EGFR, its natural ligands, as well as signaling cascades triggered by the EGFR activation, peculiarities of the EGFR expression and activation in oncological disorders, as well as applied therapeutic approaches aimed at blocking EGFR signaling pathway are summarized and analyzed in this review. Approaches to the targeted delivery of various chemotherapeutic agents, radionuclides, immunotoxins, photosensitizers, as well as the prospects for gene therapy aimed at cancer cells with EGFR overexpression are reviewed in detail. It should be noted that increasing attention is being paid nowadays to the development of multifunctional systems, either carrying several different active agents, or possessing several environment-dependent transport functions. Potentials of the systems based on receptor-mediated endocytosis of EGFR and their possible advantages and limitations are discussed.

A brief history of the octopus imaging facility to celebrate its 10th anniversary

Octopus (Optics Clustered to OutPut Unique Solutions) celebrated in June 2020 its 10th birthday. Based at Harwell, near Oxford, Octopus is an open access, peer reviewed, national imaging facility that offers successful U.K. applicants supported access to single molecule imaging, confocal microscopy, several flavours of superresolution imaging, light sheet microscopy, optical trapping and cryoscanning electron microscopy. Managed by a multidisciplinary team, Octopus has so far assisted >100 groups of U.K. and international researchers. Cross-fertilisation across fields proved to be a strong propeller of success underpinned by combining access to top-end instrumentation with a strong programme of imaging hardware and software developments. How Octopus was born, and highlights of the multidisciplinary output produced during its 10-year journey are reviewed below, with the aim of celebrating a myriad of collaborations with the U.K. scientific community, and reflecting on their scientific and societal impact.

Live cell single molecule tracking and localization microscopy of bioorthogonally labeled plasma membrane proteins

Tracking the localization and mobility of individual proteins in live cells is key for understanding how they mediate their function. Such information can be obtained from single molecule imaging techniques including as Single Particle Tracking (SPT) and Single Molecule Localization Microscopy (SMLM). Genetic code expansion (GCE) combined with bioorthogonal chemistry offers an elegant approach for direct labeling of proteins with fluorescent dyes, holding great potential for improving protein labeling in single molecule applications. Here we calibrated conditions for performing SPT and live-SMLM of bioorthogonally labeled plasma membrane proteins in live mammalian cells. Using SPT, the diffusion of bioorthogonally labeled EGF receptor and the prototypical Shaker voltage-activated potassium channel (Kv) was measured and characterized. Applying live-SMLM to bioorthogonally labeled Shaker Kv channels enabled visualizing the plasma membrane distribution of the channel over time with ∼30 nm accuracy. Finally, by competitive labeling with two Fl-dyes, SPT and live-SMLM were performed in a single cell and both the density and dynamics of the EGF receptor were measured at single molecule resolution in subregions of the cell. We conclude that GCE and bioorthogonal chemistry is a highly suitable, flexible approach for protein labeling in quantitative single molecule applications that outperforms current protein live-cell labeling approaches.

Structure and Dynamics of the EGF Receptor as Revealed by Experiments and Simulations and Its Relevance to Non-Small Cell Lung Cancer

The epidermal growth factor receptor (EGFR) is historically the prototypical receptor tyrosine kinase, being the first cloned and the first where the importance of ligand-induced dimer activation was ascertained. However, many years of structure determination has shown that EGFR is not completely understood. One challenge is that the many structure fragments stored at the PDB only provide a partial view because full-length proteins are flexible entities and dynamics play a key role in their functionality. Another challenge is the shortage of high-resolution data on functionally important higher-order complexes. Still, the interest in the structure/function relationships of EGFR remains unabated because of the crucial role played by oncogenic EGFR mutants in driving non-small cell lung cancer (NSCLC). Despite targeted therapies against EGFR setting a milestone in the treatment of this disease, ubiquitous drug resistance inevitably emerges after one year or so of treatment. The magnitude of the challenge has inspired novel strategies. Among these, the combination of multi-disciplinary experiments and molecular dynamic (MD) simulations have been pivotal in revealing the basic nature of EGFR monomers, dimers and multimers, and the structure-function relationships that underpin the mechanisms by which EGFR dysregulation contributes to the onset of NSCLC and resistance to treatment.