Automated single-molecule imaging in living cells

The impact of common redox mediators on cellular health: a comprehensive study

Electrochemistry has become a key technique for studying biomolecular reactions and dynamics of living systems by using electron-transfer reactions to probe the complex interactions between biological redox molecules and their surrounding environments. To enable such measurements, redox mediators such as ferro/ferricyanide, ferrocene methanol, and tris(bipyridine) ruthenium(II) chloride are used. However, the impact of these exogeneous redox mediators on the health of cell cultures remains underexplored. Herein, we present the effects of three common redox mediators on the health of four of the most commonly used cell lines (Panc1, HeLa, U2OS, and MDA-MB-231) in biological studies. Cell health was assessed using three independent parameters: reactive oxygen species quantification by fluorescence flow cytometry, cell migration through scratch assays, and cell growth via luminescence assays. We show that as the concentration of mediator exceeds 1 mM, ROS increases in all cell types while cell viability plumets. In contrast, cell migration was only hindered at the highest concentration of each mediator. Our observations highlight the crucial role that optimized mediator concentrations play in ensuring accuracy when studying biological systems by electrochemical methods. As such, these findings provide a critical reference for selecting redox mediator concentrations for bioanalytical studies on live cells.

A high-throughput platform for single-molecule tracking identifies drug interaction and cellular mechanisms

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging >106 cells/day and screening >104 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

Bilateral regulation of EGFR activity and local PI(4,5)P2 dynamics in mammalian cells observed with superresolution microscopy

Anionic lipid molecules, including phosphatidylinositol-4,5-bisphosphate (PI(4,5)P2), are implicated in the regulation of epidermal growth factor receptor (EGFR). However, the role of the spatiotemporal dynamics of PI(4,5)P2 in the regulation of EGFR activity in living cells is not fully understood, as it is difficult to visualize the local lipid domains around EGFR. Here, we visualized both EGFR and PI(4,5)P2 nanodomains in the plasma membrane of HeLa cells using super-resolution single-molecule microscopy. The EGFR and PI(4,5)P2 nanodomains aggregated before stimulation with epidermal growth factor (EGF) through transient visits of EGFR to the PI(4,5)P2 nanodomains. The degree of coaggregation decreased after EGF stimulation and depended on phospholipase Cγ, the EGFR effector hydrolyzing PI(4,5)P2. Artificial reduction in the PI(4,5)P2 content of the plasma membrane reduced both the dimerization and autophosphorylation of EGFR after stimulation with EGF. Inhibition of PI(4,5)P2 hydrolysis after EGF stimulation decreased phosphorylation of EGFR-Thr654. Thus, EGFR kinase activity and the density of PI(4,5)P2 around EGFR molecules were found to be mutually regulated.

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.

Four-color single-molecule imaging system for tracking GPCR dynamics with fluorescent HiBiT peptide

Single-molecule imaging provides information on diffusion dynamics, oligomerization, and protein-protein interactions in living cells. To simultaneously monitor different types of proteins at the single-molecule level, orthogonal fluorescent labeling methods with different photostable dyes are required. G-protein-coupled receptors (GPCRs), a major class of drug targets, are prototypical membrane receptors that have been studied using single-molecule imaging techniques. Here we developed a method for labeling cell-surface GPCRs inspired by the HiBiT system, which utilizes the high affinity complementation between LgBiT and HiBiT fragments of the NanoLuc luciferase. We synthesized four fluorescence-labeled HiBiT peptides (F-FiBiTs) with a different color dye (Setau-488, TMR, SaraFluor 650 and SaraFluor 720). We constructed a multicolor total internal reflection fluorescence microscopy system that allows us to track four color dyes simultaneously. As a proof-of-concept experiment, we labeled an N-terminally LgBiT-fused GPCR (Lg-GPCR) with a mixture of the four F-FiBiTs and successfully tracked each dye within a cell at the single-molecule level. The F-FiBiT-labeled Lg-GPCRs showed agonist-dependent changes in the diffusion dynamics and accumulation into the clathrin-coated pits as observed with a conventional method using a C-terminally HaloTag-fused GPCR. Taking advantage of luciferase complementation by the F-FiBiT and Lg-GPCRs, the F-FiBiT was also applicable to bioluminescence plate-reader-based assays. By combining existing labeling methods such as HaloTag, SNAP-tag, and fluorescent proteins, the F-FiBiT method will be useful for multicolor single-molecule imaging and will enhance our understanding of GPCR signaling at the single-molecule level.

Probing and imaging phospholipid dynamics in live cells

Distinct phospholipid species display specific distribution patterns across cellular membranes, which are important for their structural and signaling roles and for preserving the integrity and functionality of the plasma membrane and organelles. Recent advancements in lipid biosensor technology and imaging modalities now allow for direct observation of phospholipid distribution, trafficking, and dynamics in living cells. These innovations have markedly advanced our understanding of phospholipid function and regulation at both cellular and subcellular levels. Herein, we summarize the latest developments in phospholipid biosensor design and application, emphasizing the contribution of cutting-edge imaging techniques to elucidating phospholipid dynamics and distribution with unparalleled spatiotemporal precision.

Application of single-molecule analysis to singularity phenomenon of cells

Single-molecule imaging in living cells is an effective tool for elucidating the mechanisms of cellular phenomena at the molecular level. However, the analysis was not designed for throughput and requires high expertise, preventing it from reaching large scale, which is necessary when searching for rare cells that induce singularity phenomena. To overcome this limitation, we have automated the imaging procedures by combining our own focusing device, artificial intelligence, and robotics. The apparatus, called automated in-cell single-molecule imaging system (AiSIS), achieves a throughput that is a hundred-fold higher than conventional manual imaging operations, enabling the analysis of molecular events by individual cells across a large population. Here, using AiSIS, we demonstrate the single-molecule imaging of molecular behaviors and reactions related to tau protein aggregation, which is considered a singularity phenomenon in neurological disorders. Changes in the dynamics and kinetics of molecular events were observed inside and on the basal membrane of cells after the induction of aggregation. Additionally, to detect rare cells based on the molecular behavior, we developed a method to identify the state of individual cells defined by the quantitative distribution of molecular mobility and clustering. Using this method, cellular variations in receptor behavior were shown to decrease following ligand stimulation. This cell state analysis based on large-scale single-molecule imaging by AiSIS will advance the study of molecular mechanisms causing singularity phenomena.

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.

Microscopy and spectroscopy approaches to study GPCR structure and function

The GPCR signalling cascade is a key pathway responsible for the signal transduction of a multitude of physical and chemical stimuli, including light, odorants, neurotransmitters and hormones. Understanding the structural and functional properties of the GPCR cascade requires direct observation of signalling processes in high spatial and temporal resolution, with minimal perturbation to endogenous systems. Optical microscopy and spectroscopy techniques are uniquely suited to this purpose because they excel at multiple spatial and temporal scales and can be used in living objects. Here, we review recent developments in microscopy and spectroscopy technologies which enable new insights into GPCR signalling. We focus on advanced techniques with high spatial and temporal resolution, single-molecule methods, labelling strategies and approaches suitable for endogenous systems and large living objects. This review aims to assist researchers in choosing appropriate microscopy and spectroscopy approaches for a variety of applications in the study of cellular signalling.

A dynamic partitioning mechanism polarizes membrane protein distribution

The plasma membrane is widely regarded as the hub of the numerous signal transduction activities. Yet, the fundamental biophysical mechanisms that spatiotemporally compartmentalize different classes of membrane proteins remain unclear. Using multimodal live-cell imaging, here we first show that several lipid-anchored membrane proteins are consistently depleted from the membrane regions where the Ras/PI3K/Akt/F-actin network is activated. The dynamic polarization of these proteins does not depend upon the F-actin-based cytoskeletal structures, recurring shuttling between membrane and cytosol, or directed vesicular trafficking. Photoconversion microscopy and single-molecule measurements demonstrate that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane which enable their selective segregation. When these diffusion coefficients are incorporated into an excitable network-based stochastic reaction-diffusion model, simulations reveal that the altered affinity mediated selective partitioning is sufficient to drive familiar propagating wave patterns. Furthermore, normally uniform integral and lipid-anchored membrane proteins partition successfully when membrane domain-specific peptides are optogenetically recruited to them. We propose "dynamic partitioning" as a new mechanism that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins during various physiological processes where membrane polarizes.

Unravelling the Mystery inside Cells by Using Single-Molecule Fluorescence Imaging

Live-cell imaging is a powerful technique to study the dynamics and mechanics of various biological molecules like proteins, organelles, DNA, and RNA. With the rapid evolution of optical microscopy, our understanding of how these molecules are implicated in the cells' most critical physiological roles deepens. In this review, we focus on how spatiotemporal nanoscale live-cell imaging at the single molecule level allows for profound contributions towards new discoveries in life science. This review will start by summarizing how single-molecule tracking has been used to analyze membrane dynamics, receptor-ligand interactions, protein-protein interactions, inner- and extra-cellular transport, gene expression/transcription, and whole organelle tracking. We then move on to how current authors are trying to improve single-molecule tracking and overcome current limitations by offering new ways of labeling proteins of interest, multi-channel/color detection, improvements in time-lapse imaging, and new methods and programs to analyze the colocalization and movement of targets. We later discuss how single-molecule tracking can be a beneficial tool used for medical diagnosis. Finally, we wrap up with the limitations and future perspectives of single-molecule tracking and total internal reflection microscopy.

Single-molecule tracking of Nanog and Oct4 in living mouse embryonic stem cells uncovers a feedback mechanism of pluripotency maintenance

Nanog and Oct4 are core transcription factors that form part of a gene regulatory network to regulate hundreds of target genes for pluripotency maintenance in mouse embryonic stem cells (ESCs). To understand their function in the pluripotency maintenance, we visualised and quantified the dynamics of single molecules of Nanog and Oct4 in a mouse ESCs during pluripotency loss. Interestingly, Nanog interacted longer with its target loci upon reduced expression or at the onset of differentiation, suggesting a feedback mechanism to maintain the pluripotent state. The expression level and interaction time of Nanog and Oct4 correlate with their fluctuation and interaction frequency, respectively, which in turn depend on the ESC differentiation status. The DNA viscoelasticity near the Oct4 target locus remained flexible during differentiation, supporting its role either in chromatin opening or a preferred binding to uncondensed chromatin regions. Based on these results, we propose a new negative feedback mechanism for pluripotency maintenance via the DNA condensation state-dependent interplay of Nanog and Oct4.

Influence of Chemical and Genetic Manipulations on Cellular Organelles Quantified by Label-Free Optical Diffraction Tomography

Label-free optical diffraction tomography provides three-dimensional imaging of cells and organelles, along with their refractive index (RI) and volume. These physical parameters are valuable for quantitative and accurate analysis of the subcellular microenvironment and its connections to intracellular biological properties. In biological and biochemical cell analysis, various invasive cell manipulations are used, such as temperature change, chemical fixation, live cell staining with fluorescent dye, and gene overexpression of exogenous proteins. However, it is not fully understood how these various manipulations affect the physicochemical properties of different organelles. In this study, we investigated the impact of these manipulations on the cellular properties of single HeLa cells. We found that after cell fixation and an increase in temperature, the RI value of organelles, such as the nucleus and cytoplasm, significantly decreased overall. Interestingly, unlike the cell nuclei, cytoplasmic RI values were hardly detected after membrane permeation, indicating that only intracytoplasmic components were largely lost. Additionally, our findings revealed that the expression of GFP and GFP-tagged proteins significantly increased the RI values of organelles in living cells compared to the less effective RI changes observed with chemical fluorescence staining for cell organelles. The result demonstrates that distinct types of invasive manipulations can alter the microenvironment of organelles in different ways. Our study sheds new light on how chemical and genetic manipulations affect organelles.

When Super-Resolution Microscopy Meets Microfluidics: Enhanced Biological Imaging and Analysis with Unprecedented Resolution

Super-resolution microscopy is rapidly developed in recent years, allowing biologists to extract more quantitative information on subcellular processes in live cells that is usually not accessible with conventional techniques. However, super-resolution imaging is not fully exploited because of the lack of an appropriate and multifunctional experimental platform. As an important tool in life sciences, microfluidics is capable of cell manipulation and the regulation of the cellular environment because of its superior flexibility and biocompatibility. The combination of microfluidics and super-resolution microscopy revolutionizes the study of complex cellular properties and dynamics, providing valuable insights into cellular structure and biological functions at the single-molecule level. In this perspective, an overview of the main advantages of microfluidic technology that are essential to the performance of super-resolution microscopy are offered. The main benefits of performing super-resolution imaging with microfluidic devices are highlighted and perspectives on the diverse applications that are facilitated by combining these two powerful techniques are provided.

Tracking the Message: Applying Single Molecule Localization Microscopy to Cellular RNA Imaging

RNA function is increasingly appreciated to be more complex than merely communicating between DNA sequence and protein structure. RNA localization has emerged as a key contributor to the intricate roles RNA plays in the cell, and the link between dysregulated spatiotemporal localization and disease warrants an exploration beyond sequence and structure. However, the tools needed to visualize RNA with precise resolution are lacking in comparison to methods available for studying proteins. In the past decade, many techniques have been developed for imaging RNA, and in parallel super resolution and single-molecule techniques have enabled imaging of single molecules in cells. Of these methods, single molecule localization microscopy (SMLM) has shown significant promise for probing RNA localization. In this review, we highlight current approaches that allow super resolution imaging of specific RNA transcripts and summarize challenges and future opportunities for developing innovative RNA labeling methods that leverage the power of SMLM.

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.

Super-resolution fluorescence microscopic imaging in pathogenesis and drug treatment of neurological disease

Since super-resolution fluorescence microscopic technology breaks the diffraction limit that has existed for a long time in optical imaging, it can observe the process of synapses formed between nerve cells and the protein aggregation related to neurological disease. Thus, super-resolution fluorescence microscopic imaging has significantly impacted several industries, including drug development and pathogenesis research, and it is anticipated that it will significantly alter the future of life science research. Here, we focus on several typical super-resolution fluorescence microscopic technologies, introducing their benefits and drawbacks, as well as applications in several common neurological diseases, in the hope that their services will be expanded and improved in the pathogenesis and drug treatment of neurological diseases.

Nanoconfinement-Enhanced Electrochemiluminescence for in Situ Imaging of Single Biomolecules

Direct imaging of electrochemical reactions at the single-molecule level is of potential interest in materials, diagnostic, and catalysis applications. Electrochemiluminescence (ECL) offers the opportunity to convert redox events into photons. However, it is challenging to capture single photons emitted from a single-molecule ECL reaction at a specific location, thus limiting high-quality imaging applications. We developed the nanoreactors based on Ru(bpy)₃²⁺-doped nanoporous zeolite nanoparticles (Ru@zeolite) for direct visualization of nanoconfinement-enhanced ECL reactions. Each nanoreactor not only acts as a matrix to host Ru(bpy)₃²⁺ molecules but also provides a nanoconfined environment for the collision reactions of Ru(bpy)₃²⁺ and co-reactant radicals to realize efficient in situ ECL reactions. The nanoscale confinement resulted in enhanced ECL. Using such nanoreactors as ECL probes, a dual-signal sensing protocol for visual tracking of a single biomolecule was performed. High-resolution imaging of single membrane proteins on heterogeneous cells was effectively addressed with near-zero backgrounds. This could provide a more sensitive tool for imaging individual biomolecules and significantly advance ECL imaging in biological applications.

The compact integration of a cascaded HCR circuit for highly reliable cancer cell discrimination

The accurate identification of multiple biomarkers involved in disease plays a vital role in effectively distinguishing cancer cells from normal cells, facilitating reliable cancer diagnosis. Motivated by this knowledge, we have engineered a compact and clamped cascaded DNA circuit for specifically discriminating cancer cells from normal cells via the amplified multi-microRNA imaging strategy. The proposed DNA circuit combines the traditional cascaded DNA circuit with multiply localized responsive character through the elaboration of two super-hairpin reactants, thus concurrently streamlining the circuit components and realizing localization-intensified cascaded signal amplification. In parallel, the multiple microRNA-stimulated sequential activations of the compact circuit, combined with a handy logic operation, significantly elevated the cell-discriminating reliability. Applications of the present DNA circuit in vitro and in cellular imaging experiments were executed with expected results, therefore illustrating that our DNA circuit is useful for precise cell discrimination and further clinical diagnosis.

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.

HS, an Ancient Molecular Recognition and Information Storage Glycosaminoglycan, Equips HS-Proteoglycans with Diverse Matrix and Cell-Interactive Properties Operative in Tissue Development and Tissue Function in Health and Disease

Heparan sulfate is a ubiquitous, variably sulfated interactive glycosaminoglycan that consists of repeating disaccharides of glucuronic acid and glucosamine that are subject to a number of modifications (acetylation, de-acetylation, epimerization, sulfation). Variable heparan sulfate chain lengths and sequences within the heparan sulfate chains provide structural diversity generating interactive oligosaccharide binding motifs with a diverse range of extracellular ligands and cellular receptors providing instructional cues over cellular behaviour and tissue homeostasis through the regulation of essential physiological processes in development, health, and disease. heparan sulfate and heparan sulfate-PGs are integral components of the specialized glycocalyx surrounding cells. Heparan sulfate is the most heterogeneous glycosaminoglycan, in terms of its sequence and biosynthetic modifications making it a difficult molecule to fully characterize, multiple ligands also make an elucidation of heparan sulfate functional properties complicated. Spatio-temporal presentation of heparan sulfate sulfate groups is an important functional determinant in tissue development and in cellular control of wound healing and extracellular remodelling in pathological tissues. The regulatory properties of heparan sulfate are mediated via interactions with chemokines, chemokine receptors, growth factors and morphogens in cell proliferation, differentiation, development, tissue remodelling, wound healing, immune regulation, inflammation, and tumour development. A greater understanding of these HS interactive processes will improve therapeutic procedures and prognoses. Advances in glycosaminoglycan synthesis and sequencing, computational analytical carbohydrate algorithms and advanced software for the evaluation of molecular docking of heparan sulfate with its molecular partners are now available. These advanced analytic techniques and artificial intelligence offer predictive capability in the elucidation of heparan sulfate conformational effects on heparan sulfate-ligand interactions significantly aiding heparan sulfate therapeutics development.

A dynamic partitioning mechanism polarizes membrane protein distribution

The plasma membrane is widely regarded as the hub of the signal transduction network activities that drives numerous physiological responses, including cell polarity and migration. Yet, the symmetry breaking process in the membrane, that leads to dynamic compartmentalization of different proteins, remains poorly understood. Using multimodal live-cell imaging, here we first show that multiple endogenous and synthetic lipid-anchored proteins, despite maintaining stable tight association with the inner leaflet of the plasma membrane, were unexpectedly depleted from the membrane domains where the signaling network was spontaneously activated such as in the new protrusions as well as within the propagating ventral waves. Although their asymmetric patterns resembled those of standard peripheral "back" proteins such as PTEN, unlike the latter, these lipidated proteins did not dissociate from the membrane upon global receptor activation. Our experiments not only discounted the possibility of recurrent reversible translocation from membrane to cytosol as it occurs for weakly bound peripheral membrane proteins, but also ruled out the necessity of directed vesicular trafficking and cytoskeletal supramolecular structure-based restrictions in driving these dynamic symmetry breaking events. Selective photoconversion-based protein tracking assays suggested that these asymmetric patterns instead originate from the inherent ability of these membrane proteins to "dynamically partition" into distinct domains within the plane of the membrane. Consistently, single-molecule measurements showed that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane. When these profiles were incorporated into an excitable network-based stochastic reaction-diffusion model of the system, simulations revealed that our proposed "dynamic partitioning" mechanism is sufficient to give rise to familiar asymmetric propagating wave patterns. Moreover, we demonstrated that normally uniform integral and lipid-anchored membrane proteins in Dictyostelium and mammalian neutrophil cells can be induced to partition spatiotemporally to form polarized patterns, by optogenetically recruiting membrane domain-specific peptides to these proteins. Together, our results indicate "dynamic partitioning" as a new mechanism of plasma membrane organization, that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins in different physiological processes.

Deep learning in single-molecule imaging and analysis: recent advances and prospects

Single-molecule microscopy is advantageous in characterizing heterogeneous dynamics at the molecular level. However, there are several challenges that currently hinder the wide application of single molecule imaging in bio-chemical studies, including how to perform single-molecule measurements efficiently with minimal run-to-run variations, how to analyze weak single-molecule signals efficiently and accurately without the influence of human bias, and how to extract complete information about dynamics of interest from single-molecule data. As a new class of computer algorithms that simulate the human brain to extract data features, deep learning networks excel in task parallelism and model generalization, and are well-suited for handling nonlinear functions and extracting weak features, which provide a promising approach for single-molecule experiment automation and data processing. In this perspective, we will highlight recent advances in the application of deep learning to single-molecule studies, discuss how deep learning has been used to address the challenges in the field as well as the pitfalls of existing applications, and outline the directions for future development.

Threonine phosphorylation regulates the molecular assembly and signaling of EGFR in cooperation with membrane lipids

The cytoplasmic domain of the receptor tyrosine kinases (RTKs) plays roles as a phosphorylation enzyme and a protein scaffold but the allocation of these two functions is not fully understood. We here analyzed assembly of the transmembrane (TM)-juxtamembrane (JM) region of EGFR, one of the best studied species of RTKs, by combining single-pair FRET imaging and a nanodisc technique. The JM domain of EGFR contains a threonine residue (Thr654) that is phosphorylated after ligand association. We observed that the TM-JM peptides of EGFR form anionic lipid-induced dimers and cholesterol-induced oligomers. The two forms involve distinct molecular interactions, with a bias towards oligomer formation upon threonine phosphorylation. We further analyzed the functions and oligomerization of whole EGFR molecules, with or without a substitution of Thr654 to alanine, in living cells. The results suggested an autoregulatory mechanism in which Thr654 phosphorylation causes a switch of the major function of EGFR from kinase activation dimers to scaffolding oligomers.

Fabrication of High-Density Vertical Closed Bipolar Electrode Arrays by Carbon Paste Filling Method for Two-Dimensional Chemical Imaging

In this study, a carbon paste filling method was proposed as a simple strategy for fabricating high-density bipolar electrode (BPE) arrays for bipolar electrochemical microscopy (BEM). High spatiotemporal resolution imaging was achieved using the fabricated BPE array. BEM, which is an emerging microscopic system in recent years, achieves label-free and high spatiotemporal resolution imaging of molecular distributions using high-density BPE arrays and electrochemiluminescence (ECL) signals. We devised a simple method to fabricate a BPE array by filling a porous plate with carbon paste and succeeded in fabricating a high-density BPE array (15 μm pitch). After a detailed observation of the surface of the BPE array using a scanning electron microscope, the basic electrochemical and ECL emission characteristics were evaluated using potassium ferricyanide solution as a sample solution. Moreover, inflow imaging of the sample molecules was conducted to evaluate the imaging ability of the prepared BPE array. In addition, Prussian Blue containing carbon ink was applied to the sample solution side of the BPE array to provide catalytic activity to hydrogen peroxide, and the quantification and inflow imaging of hydrogen peroxide by ECL signals was achieved. This simple fabrication method of the BPE array can accelerate the research and development of BEM. Furthermore, hydrogen peroxide imaging by BEM is an important milestone for achieving bioimaging with high spatiotemporal resolution such as biomolecule imaging using enzymes.

Triple-color single-molecule imaging for analysis of the role of receptor oligomers in signal transduction

Membrane receptors provide interfaces of various extracellular stimuli to transduce the signal into the cell. Receptors are required to possess such conflicting properties as high sensitivity and noise reduction for the cell to keep its homeostasis and appropriate responses. To understand the mechanisms by which these functions are achieved, single-molecule monitoring of the motilities of receptors and signaling molecules on the plasma membrane is one of the most direct approaches. This review article introduces several recent single-molecule imaging studies of receptors, including the author’s recent work on triple-color single-molecule imaging of G protein-coupled receptors. Based on these researches, advantages and perspectives of the single-molecule imaging approach to solving the mechanisms of receptor functions are illustrated.

Single-Molecule Clustering for Super-Resolution Optical Fluorescence Microscopy

Molecular assembly in a complex cellular environment is vital for understanding underlying biological mechanisms. Biophysical parameters (such as single-molecule cluster density, cluster-area, pairwise distance, and number of molecules per cluster) related to molecular clusters directly associate with the physiological state (healthy/diseased) of a cell. Using super-resolution imaging along with powerful clustering methods (K-means, Gaussian mixture, and point clustering), we estimated these critical biophysical parameters associated with dense and sparse molecular clusters. We investigated Hemaglutinin (HA) molecules in an Influenza type A disease model. Subsequently, clustering parameters were estimated for transfected NIH3T3 cells. Investigations on test sample (randomly generated clusters) and NIH3T3 cells (expressing Dendra2-Hemaglutinin (Dendra2-HA) photoactivable molecules) show a significant disparity among the existing clustering techniques. It is observed that a single method is inadequate for estimating all relevant biophysical parameters accurately. Thus, a multimodel approach is necessary in order to characterize molecular clusters and determine critical parameters. The proposed study involving optical system development, photoactivable sample synthesis, and advanced clustering methods may facilitate a better understanding of single molecular clusters. Potential applications are in the emerging field of cell biology, biophysics, and fluorescence imaging.

Super-resolution microscopy: a closer look at synaptic dysfunction in Alzheimer disease

The synapse has emerged as a critical neuronal structure in the degenerative process of Alzheimer disease (AD), in which the pathogenic signals of two key players - amyloid-β (Aβ) and tau - converge, thereby causing synaptic dysfunction and cognitive deficits. The synapse presents a dynamic, confined microenvironment in which to explore how key molecules travel, localize, interact and assume different levels of organizational complexity, thereby affecting neuronal function. However, owing to their small size and the diffraction-limited resolution of conventional light microscopic approaches, investigating synaptic structure and dynamics has been challenging. Super-resolution microscopy (SRM) techniques have overcome the resolution barrier and are revolutionizing our quantitative understanding of biological systems in unprecedented spatio-temporal detail. Here we review critical new insights provided by SRM into the molecular architecture and dynamic organization of the synapse and, in particular, the interactions between Aβ and tau in this compartment. We further highlight how SRM can transform our understanding of the molecular pathological mechanisms that underlie AD. The application of SRM for understanding the roles of synapses in AD pathology will provide a stepping stone towards a broader understanding of dysfunction in other subcellular compartments and at cellular and circuit levels in this disease.

The H2A.Z-nuclesome code in mammals: emerging functions

H2A.Z is a histone variant that provides specific structural and docking-side properties to the nucleosome, resulting in diverse and specialised molecular and cellular functions. In this review, we discuss the latest studies uncovering new functional aspects of mammalian H2A.Z in gene transcription, including pausing and elongation of RNA polymerase II (RNAPII) and enhancer activity; DNA repair; DNA replication; and 3D chromatin structure. We also review the recently described role of H2A.Z in embryonic development, cell differentiation, neurodevelopment, and brain function. In conclusion, our cumulative knowledge of H2A.Z over the past 40 years, in combination with the implementation of novel molecular technologies, is unravelling an unexpected and complex role of histone variants in gene regulation and disease.

Potential of Single-Molecule Live-Cell Imaging for Chemical Translational Biology

Single-molecule live-cell imaging is the most direct approach for monitoring the motility of molecules in living cells. Considering the relationship between the motility of molecules and their function, information obtained from single-molecule imaging involves essential clues for understanding the regulatory mechanisms of the processes of target molecules, and translation to applied sciences such as drug discovery. In this Concept, examples of single-molecule imaging studies on G protein-coupled receptors (GPCRs) are mainly introduced, and recent techniques of single-molecule imaging for overcoming the limitation of single-molecule live-cell imaging are discussed. Based on these studies, the prospects of single-molecule imaging will be outlined.

Plasmon-enhanced fluorescence correlation spectroscopy for super-localized detection of nanoscale subcellular dynamics

In this report, we investigate plasmon-enhanced imaging fluorescence correlation spectroscopy (p-FCS). p-FCS takes advantage of extreme light confinement by localization at nanogap-based plasmonic nanodimer arrays (PNAs) for enhanced signal-to-noise ratio (SNR) and improved precision by registration with surface plasmon microscopy images. Theoretical results corroborate the enhancement by PNAs in the far-field. Near-field scanning optical microscopy was used to confirm near-field localization experimentally. Experimental confirmation was also conducted with fluorescent nanobeads. The concept was further applied to studying the diffusion dynamics of lysosomes in HEK293T cells stimulated by phorbol 12-myristate 13-acetate treatment. It was found that lysosomes demonstrate stronger super-diffusive behavior with relatively weaker sub-diffusion after stimulation. SNR measured of p-FCS was improved by 9.77 times over conventional FCS. This report is expected to serve as the foundation for an enhanced analytical tool to explore subcellular dynamics.

In-Cell Single-Molecule Analysis of Molecular State and Reaction Kinetics Coupling

Cellular signaling is regulated by the spatiotemporal dynamics and kinetics of molecular behavior. To investigate the mechanisms at the molecular level, fluorescence single-molecule analysis is an effective method owing to the direct observation of individual molecules in situ in cells and the results in quantitative information about the behavior. The integration of machine learning into this analysis modality enables the acquisition of behavioral features at all time points of all molecules. As a case study, we described a hidden Markov model-based approach to infer the molecular states of mobility and clustering for epidermal growth factor receptor (EGFR) along a single-molecule trajectory. We reveal a scheme of the receptor signaling through the dynamic coupling of the mobility and clustering states under the influence of a local membrane structure. As the activation process progressed, EGFR generally converged to an immobile cluster. This state exhibited high affinity with a specific cytoplasmic protein, shown by two-color single-molecule analysis, and could be a platform for downstream signaling. The method was effective for elucidating the biophysical mechanisms of signaling regulation when comprehensive analysis is possible for a huge number and multiple molecular species in the signaling pathway. Thus, a fully automated system for single-molecule analysis, in which indispensable expertise was replicated using artificial intelligence, has been developed to enable in-cell large-scale analysis. This system opens new single-molecule approaches for pharmacological applications as well as the basic sciences.

Natural Killer Cell Integrins and Their Functions in Tissue Residency

Integrins are transmembrane receptors associated with adhesion and migration and are often highly differentially expressed receptors amongst natural killer cell subsets in microenvironments. Tissue resident natural killer cells are frequently defined by their differential integrin expression compared to other NK cell subsets, and integrins can further localize tissue resident NK cells to tissue microenvironments. As such, integrins play important roles in both the phenotypic and functional identity of NK cell subsets. Here we review the expression of integrin subtypes on NK cells and NK cell subsets with the goal of better understanding how integrin selection can dictate tissue residency and mediate function from the nanoscale to the tissue environment.

Workflows of the Single-Molecule Imaging Analysis in Living Cells: Tutorial Guidance to the Measurement of the Drug Effects on a GPCR

Single-molecule imaging (SMI) is a powerful method to measure the dynamics of membrane proteins on the cell membrane. The single-molecule tracking (SMT) analysis provides information about the diffusion dynamics, the oligomer size distribution, and the particle density change. The affinity and on/off-rate of a protein-protein interaction can be estimated from the dual-color SMI analysis. However, it is difficult for trainees to determine quantitative information from the SMI movies. The present protocol guides the detailed workflows to measure the drug-activated dynamics of a G protein-coupled receptor (GPCR) and metabotropic glutamate receptor 3 (mGluR3), by using the total internal reflection fluorescence microscopy (TIRFM). This tutorial guidance comprises an open-source software, named smDynamicsAnalyzer, with which one can easily analyze the SMT dataset by just following the workflows after building a designated folder structure ( https://github.com/masataka-yanagawa/IgorPro8-smDynamicsAnalyzer ).

Cell-to-cell diversification in ERBB-RAS-MAPK signal transduction that produces cell-type specific growth factor responses

Growth factors regulate cell fates, including their proliferation, differentiation, survival, and death, according to the cell type. Even when the response to a specific growth factor is deterministic for collective cell behavior, significant levels of fluctuation are often observed between single cells. Statistical analyses of single-cell responses provide insights into the mechanism of cell fate decisions but very little is known about the distributions of the internal states of cells responding to growth factors. Using multi-color immunofluorescent staining, we have here detected the phosphorylation of seven elements in the early response of the ERBB-RAS-MAPK system to two growth factors. Among these seven elements, five were analyzed simultaneously in distinct combinations in the same single cells. Although principle component analysis suggested cell-type and input specific phosphorylation patterns, cell-to-cell fluctuation was large. Mutual information analysis suggested that each cell type uses multitrack (bush-like) signal transduction pathways under conditions in which clear fate changes have been reported. The clustering of single-cell response patterns indicated that the fate change in a cell population correlates with the large entropy of the response, suggesting a bet-hedging strategy is used in decision making. A comparison of true and randomized datasets further indicated that this large variation is not produced by simple reaction noise, but is defined by the properties of the signal-processing network.

Individual Cloud-Based Fingerprint Operation Platform for Latent Fingerprint Identification Using Perovskite Nanocrystals as Eikonogen

Fingerprint formed through lifted papillary ridges is considered the best reference for personal identification. However, the currently available latent fingerprint (LFP) images often suffer from poor resolution, have a low degree of information, and require multifarious steps for identification. Herein, an individual Cloud-based fingerprint operation platform has been designed and fabricated to achieve high-definition LFPs analysis by using CsPbBr₃ perovskite nanocrystals (NCs) as eikonogen. Moreover, since CsPbBr₃ NCs have a special response to some fingerprint-associated amino acids, the proposed platform can be further used to detect metabolites on LFPs. Consequently, in virtue of Cloud computing and artificial intelligence (AI), this study has demonstrated a champion platform to realize the whole LFP identification analysis. In a double-blind simulative crime game, the enhanced LFP images can be easily obtained and used to lock the suspect accurately within one second on a smartphone, which can help investigators track the criminal clue and handle cases efficiently.

Large-scale single-molecule imaging aided by artificial intelligence

Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena, single-molecule imaging analysis has not been extended to a large scale of molecules in cells due to the low measurement throughput as well as required expertise. To overcome these problems, we have automated the imaging processes by using computer operations, robotics and artificial intelligence (AI). AI is an ideal substitute for expertise to obtain high-quality images for quantitative analysis. Our automated in-cell single-molecule imaging system, AiSIS, could analyze 1600 cells in 1 day, which corresponds to ∼ 100-fold higher efficiency than manual analysis. The large-scale analysis revealed cell-to-cell heterogeneity in the molecular behavior, which had not been recognized in previous studies. An analysis of the receptor behavior and downstream signaling was accomplished within a significantly reduced time frame and revealed the detailed activation scheme of signal transduction, advancing cell biology research. Furthermore, by combining the high-throughput analysis with our previous finding that a receptor changes its behavioral dynamics depending on the presence of a ligand/agonist or inhibitor/antagonist, we show that AiSIS is applicable to comprehensive pharmacological analysis such as drug screening. This AI-aided automation has wide applications for single-molecule analysis.

Differential nanoscale organisation of LFA-1 modulates T-cell migration

Effector T-cells rely on integrins to drive adhesion and migration to facilitate their immune function. The heterodimeric transmembrane integrin LFA-1 (αLβ2 integrin) regulates adhesion and migration of effector T-cells through linkage of the extracellular matrix with the intracellular actin treadmill machinery. Here, we quantified the velocity and direction of F-actin flow in migrating T-cells alongside single-molecule localisation of transmembrane and intracellular LFA-1. Results showed that actin retrograde flow positively correlated and immobile actin negatively correlated with T-cell velocity. Plasma membrane-localised LFA-1 forms unique nano-clustering patterns in the leading edge, compared to the mid-focal zone, of migrating T-cells. Deleting the cytosolic phosphatase PTPN22, loss-of-function mutations of which have been linked to autoimmune disease, increased T-cell velocity, and leading-edge co-clustering of pY397 FAK, pY416 Src family kinases and LFA-1. These data suggest that differential nanoclustering patterns of LFA-1 in migrating T-cells may instruct intracellular signalling. Our data presents a paradigm where T-cells modulate the nanoscale organisation of adhesion and signalling molecules to fine tune their migration speed, with implications for the regulation of immune and inflammatory responses.This article has an associated First Person interview with the first author of the paper.

Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine

Historically, the term "artificial intelligence" dates to 1956 when it was first used in a conference at Dartmouth College in the US. Since then, the development of artificial intelligence has in part been shaped by the field of neuroscience. By understanding the human brain, scientists have attempted to build new intelligent machines capable of performing complex tasks akin to humans. Indeed, future research into artificial intelligence will continue to benefit from the study of the human brain. While the development of artificial intelligence algorithms has been fast paced, the actual use of most artificial intelligence (AI) algorithms in biomedical engineering and clinical practice is still markedly below its conceivably broader potentials. This is partly because for any algorithm to be incorporated into existing workflows it has to stand the test of scientific validation, clinical and personal utility, application context, and is equitable as well. In this context, there is much to be gained by combining AI and human intelligence (HI). Harnessing Big Data, computing power and storage capacities, and addressing societal issues emergent from algorithm applications, demand deploying HI in tandem with AI. Very few countries, even economically developed states, lack adequate and critical governance frames to best understand and steer the AI innovation trajectories in health care. Drug discovery and translational pharmaceutical research stand to gain from AI technology provided they are also informed by HI. In this expert review, we analyze the ways in which AI applications are likely to traverse the continuum of life from birth to death, and encompassing not only humans but also all animal, plant, and other living organisms that are increasingly touched by AI. Examples of AI applications include digital health, diagnosis of diseases in newborns, remote monitoring of health by smart devices, real-time Big Data analytics for prompt diagnosis of heart attacks, and facial analysis software with consequences on civil liberties. While we underscore the need for integration of AI and HI, we note that AI technology does not have to replace medical specialists or scientists and rather, is in need of such expert HI. Altogether, AI and HI offer synergy for responsible innovation and veritable prospects for improving health care from prevention to diagnosis to therapeutics while unintended consequences of automation emergent from AI and algorithms should be borne in mind on scientific cultures, work force, and society at large.

Dynamic colloidal nanoparticle assembly triggered by aptamer-receptor interactions on live cell membranes

Cells use dynamic systems such as enzyme cascades and signaling networks to control cellular functions. Synthetic dynamic systems that can be target-responsive have great potential to be applied for biomedical applications but the operation of such dynamic systems in complex cellular environments remains challenging. Here, we engineered an aptamer and DNA displacement reaction-based dynamic system that can transform its nanostructure in response to the epithelial cell adhesion molecule (EpCAM) on live cell membranes. The dynamic system consisted of a core nanoparticle and small satellite nanoparticles. With the modifications of different DNA hairpin strands and swing arm strands partially hybridized with an aptamer that specifically recognizes the EpCAM, the two separated particles can dynamically assemble into a core-satellite assembly by aptamer-receptor interactions on the cell membrane surface. The structural change of the system from separated particles to a core-satellite assembly generated plasmonic coupled hot spots for surface-enhanced Raman scattering (SERS) for sensitively capturing the dynamic structural change of the nanoassembly in the cellular environment. These concepts provide strategies for engineering dynamic nanotechnology systems for biological and biomedical applications in complex biological environments.

Needle Biopsy Adequacy in the Era of Precision Medicine and Value-Based Health Care

CONTEXT.—

Needle biopsy of diseased tissue is an essential diagnostic tool that is becoming even more important as precision medicine develops. However, the capability of this modality to efficiently provide samples adequate for diagnostic and prognostic analysis remains quite limited relative to current diagnostic needs. For physicians and patients, inadequate biopsy frequently leads to diagnostic delay, procedure duplication, or insufficient information about tumor biology leading to delay in treatment; for health systems, this results in substantial incremental costs and inefficient use of scarce specialized diagnostic resources.

OBJECTIVE.—

To review current needle biopsy technology, devices, and practice with a perspective to identify current limitations and opportunities for improvement in the context of advancing precision medicine.

DATA SOURCES.—

PubMed searches of fine-needle aspiration and core needle biopsy devices and similar technologies were made generally, by tissue site, and by adequacy as well as by health economics of these technologies.

CONCLUSIONS.—

Needle biopsy adequacy can be improved by recognizing the importance of this diagnostic tool by promoting common criteria for needle biopsy adequacy; by optimizing needle biopsy procedural technique, technologies, clinical practice, professional education, and quality assurance; and by bundling biopsy procedure costs with downstream diagnostic modalities to provide better accountability and incentives to improve the diagnostic process.

Surface trafficking of neurotransmitter receptors: From cultured neurons to intact brain preparations

Over the last decade, developments in single molecule imaging have changed our vision of synaptic physiology. By providing high spatio-temporal resolution maps of the molecular actors of neurotransmissions, these techniques have revealed that pre- and post-synaptic proteins are not randomly distributed but precisely organized at the nanoscale, and that this specific organization is dynamically regulated. At the centre of synaptic transmissions, neurotransmitter receptors have been shown to form nanodomains at synapses and to dynamically move in and out of these confinement areas through lateral diffusion within the membrane plane on millisecond timescales, thereby directly contributing to the regulation of synaptic transmission and plasticity. Since the vast majority of these discoveries originated from observations made on dissociated neurons lacking several features of brain tissue (e.g. three-dimensional organization, tissue density), they were initially considered with caution. However, the recent implementation of single-particle tracking (SPT) approaches in cultured and acute brain preparations confirmed that early findings on the dynamic properties of receptors at the surface of neurons can be extended to more physiological conditions. Taking example of dopamine D1 and NMDA glutamate receptors we here review our current knowledge of the features of neurotransmitter receptor surface diffusion in intact brain tissue. Through detailed comparison with cultured neurons, we also discuss how these biophysical properties are influenced by the complexity of the extracellular environment. This article is part of the special issue entitled 'Mobility and trafficking of neuronal membrane proteins'.

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

Single-particle tracking (SPT) has been used and developed over the last 25 years as a method to investigate molecular dynamics, structure, interactions, and function in the cellular context. SPT is able to show how fast and how far individual molecules move, identify different dynamic populations, measure the duration and strength of intermolecular interactions, and map out structures on the nanoscale in cells. In combination with other techniques such as macromolecular crystallography and molecular dynamics simulation, it allows us to build models of complex structures, and develop and test hypotheses of how these complexes perform their biological roles in health as well as in disease states. Here, we use the example of the epidermal growth factor receptor (EGFR), which has been studied extensively by SPT, demonstrating how the method has been used to increase our understanding of the receptor’s organization and function, including its interaction with the plasma membrane, its activation, clustering, and oligomerization, and the role of other receptors and endocytosis. The examples shown demonstrate how SPT might be employed in the investigation of other biomolecules and systems.