Precise surface engineering is essential for robust characterization of extracellular vesicles and their interactions with biologically relevant interfaces. In this study, Au substrates were modified with C6 self-assembled monolayers (SAMs) bearing different terminal groups after multiple cleaning protocols to optimize monolayer compactness and interfacial quality. Surface area and functionality were further enhanced by gold nanoparticle (AuNP) deposition and secondary SAM formation, enabling layer-by-layer assembly of glycan-based polysaccharide nanostructures. Interface fabrication and growth were monitored by electrochemical methods and atomic force microscopy (AFM). Extracellular vesicles (EVs) from MDA-MB-231 breast cancer cells and benign RWPE-1 (control) cells were affinity isolated using magnetic microparticles, chromatographically preconcentrated, and subjected to protein-corona removal prior to analysis. The impact of the protein corona on antibody-mediated recognition was evaluated by ELISA and revealed markedly improved accessibility of EV surface markers following corona removal. Interactions of EVs with extracellular-matrix-mimicking glycan interfaces were investigated using surface plasmon resonance (SPR). Sensorgrams were analyzed using a physics-informed neural-network-assisted model to extract dissociation constants while reducing the influence of bulk refractive-index contributions typical of vesicle samples. The developed nanobiointerfaces enabled sensitive characterization of EV binding behavior and revealed distinct interaction phenotypes of malignant-derived and non-malignant-derived EVs toward glycan-based surfaces. These findings demonstrate that protein-corona composition and glycan-mediated interactions significantly influence EV recognition and highlight the potential of glycan-based nanobiointerfaces as tools for studying extracellular-vesicle biology, which may contribute to future liquid-biopsy development.
Capturing dynamic cellular processes in live cells requires fast imaging with very high resolution beyond the diffraction limit. Fluctuation-based super-resolution techniques overcome this limit by exploiting correlations in fluorescence blinking, but they typically require hundreds of frames and computationally intensive post-processing, prohibiting real-time imaging of fast cellular events. Recent deep learning approaches aim to increase temporal resolution; however, many rely on extensive pre-processing or large, complex models that increase training costs and inference latency, preventing real-time deployment. To address this, we employ a lightweight recurrent neural network model that integrates sequential low-resolution frames to extract spatio-temporally correlated signals. It significantly improves temporal resolution by reducing the required number of frames down to as few as 8 frames while doubling the spatial resolution in an inference time under 30 ms. Furthermore, gentle imaging conditions are essential for extracting reliable biologically relevant information, especially in long-term experiments. Our method is suitable for live-cell imaging under extreme signal/noise ratio conditions, allowing imaging under very low laser intensities to prevent photodamage. By combining simulation-based training with an efficient network architecture, we introduce real-time super-resolution fluctuation imaging (RESURF), a deep-learning-based real-time super-resolution fluctuation imaging framework. We demonstrate that RESURF generalizes across different biological structures and can be readily adapted to various microscope setups using a small data set for transfer learning. The accompanying data set, comprising simulations and experiments across multiple subcellular structures and labeling strategies, establishes a benchmarking platform for fluctuation-based super-resolution techniques. RESURF offers a practical, low-latency deep-learning framework for high-throughput imaging and real-time, smart live-cell super-resolution imaging.
Neurons form functional connections in neuronal networks of the brain. Neurotransmission refers to the information flow of electrical signals between neurons, and changes in the strength of this flow characterize brain functions. An evaluation method for neuronal information flow strength is necessary to elucidate the basic principles of brain function. To analyze the strength of information flow, identifying information transmission between time series of electrical spikes in neuronal networks, such as spike trains, is required. In this study, we evaluated the information flow strength in neuronal networks using transfer entropy (TE), an analysis method based on information theory, to elucidate causal relationships between two spike trains. Cultured rat hippocampal neuronal networks were used as living brain models, and extracellular monitoring of action potentials (expressed as spikes) was performed using microelectrode arrays. Spike trains of spontaneous activity and stimulus-evoked responses were measured in multiple neurons, and the causal relationship between electrode pairs was evaluated as an index of information flow between neurons using TE. From the results of spontaneous activity and evoked responses, it was suggested that TE values between electrodes increased with culture days and that the information flow strength was enhanced by network maturation. Furthermore, the correlation between TE values and neuronal population distance was evaluated using TE analysis. We found that neurons that received strong inputs slightly overlapped in their spontaneous activity and evoked responses. These findings suggest that spontaneous activity and evoked responses exhibit similar patterns in neuronal networks. In the graph theoretical analysis based on TE values, the network topology exhibited changes that strengthened information flow over 70 days in culture. Therefore, TE analysis is an effective tool for estimating the information flow between neurons based on neuronal electrical activity recorded at multiple sites.
Conduction velocity slows along axons, yet the right-skewed distribution of the terminal-to-initial velocity ratio ρ = vend/vstart has length-invariant mean and variance. A bounded multiplicative framework is introduced in which local geometric and kinetic factors compound proportionally but only within a finite distal domain set by termination conditions that saturate the effective multiplicative depth. The model accounts for the observed stability of the slowdown distribution across lengths and yields discriminating experimental signatures. More generally, it suggests that robust function can emerge through constrained variability rather than structural uniformity.
Schizophrenia is a multidimensional psychiatric disorder lacking a unifying systems-level framework. We introduce a cortical brain entropy architecture that characterizes the spatial and hierarchical organization of functional entropy across the cerebral cortex. In large-scale neuroimaging data, this architecture differentiates schizophrenia from health and captures multidimensional network variation. Entropy alterations follow structured cortical organization, revealing coordinated disruptions within association networks. These findings identify cortical brain entropy architecture as a compact systems-level marker of schizophrenia heterogeneity and establish a quantitative link between macroscale cortical entropy and clinical symptom dimensions.
The crystal structure of a chitooligosaccharide deacetylase (COD) from the marine bacterium Vibrio campbellii (formerly V. harveyi), referred to as VhCOD, exhibits a homodimeric assembly, consistent with previously reported X-ray structures of related Vibrio CODs. Here, we investigated whether this dimeric assembly is retained in solution. Native polyacrylamide gel electrophoresis (native PAGE) analysis revealed that VhCOD is monomeric in solution, with dimeric species present only as a minor population. Small-angle X-ray scattering further indicated that VhCOD preferentially adopts a monomeric state under dilute solution conditions. Analysis of the published crystal structures using PISA/jsPISA (Protein Interfaces, Surfaces and Assemblies/JavaScript version) predicted relatively weak monomer-monomer interactions and suggested that homodimer formation occurs only at sufficiently high protein concentrations (>5 mg·mL-1). Chemical cross-linking experiments showed that macromolecular crowding reagents promote the formation of cross-linked dimer species. Taken together, we concluded that homodimerization of Vibrio CODs arises under crowded conditions rather than representing a dominant state. This interpretation is consistent with the physiological context of VhCOD as a secretory protein that is translocated through the crowded periplasm, where transient dimerization may be relevant prior to final export across the outer membrane.
Transthyretin (TTR) amyloidosis is one of the most common forms of systemic amyloidosis, involving deposits of pathogenic TTR aggregates in tissues and organs throughout the body. TTR aggregation is initiated by the dissociation of a native TTR tetramer into a monomeric intermediate, which subsequently misfolds and assembles into insoluble aggregates. Using an efficient 19F-NMR aggregation assay, we previously showed that designed peptide inhibitors can interact with multiple TTR species. However, quantifying species-specific binding affinities has remained difficult because the populations of these TTR species change over time and include a low-abundance monomeric intermediate. Here, we develop a quantitative method to extract species-dependent binding affinities directly from population-resolved 19F-NMR aggregation data. Using diflunisal as a model compound, we determine its binding affinities for both the tetramer and the monomeric intermediate under acidic, aggregating conditions. At acidic pH, tetramer binding becomes approximately 2-fold tighter, and monomer binding becomes 15-fold stronger, compared to neutral pH. We then apply this method to previously collected 19F-NMR aggregation data for designed peptide inhibitors. The results show that concatenating two capping peptides increases their binding affinity to both TTR tetramers and monomeric intermediates by about 2-fold, relative to the same peptides mixed separately at equal concentrations. Our method enables direct, quantitative comparison of species-dependent inhibitor binding, providing mechanistic insights useful for designing and optimizing TTR aggregation inhibitors.
α-Synuclein (αSyn) is an intrinsically disordered protein that preferentially binds anionic membranes with lipid packing defects. Cholesterol is an abundant membrane component that regulates packing and organization within membranes, yet its effect on αSyn binding remains unclear as prior studies report both cholesterol-mediated enhancement and suppression. Here, we investigated whether these conflicting effects reflect differences in the intrinsic packing state of the phospholipid bilayer. Using a quantitative fluorescence microscopy-based binding assay, we measured αSyn binding preferences among reconstituted phosphatidylcholine/phosphatidylserine membranes with varied cholesterol content, lipid tail chemistry, and vesicle curvature. We found that cholesterol's effect depended on the underlying packing regime of the membrane. In defect-rich membranes, cholesterol reduced αSyn binding, consistent with cholesterol tightening lipid packing and reducing αSyn-accessible defects. In membranes with intermediate defect content, cholesterol enhanced binding, whereas tightly packed membranes remained largely insensitive to cholesterol except when high cholesterol content was combined with high membrane curvature. Curvature further shaped these responses, with high curvature compressing cholesterol-dependent differences between membrane compositions. These results show that cholesterol does not universally promote or inhibit αSyn binding. Instead, cholesterol regulates αSyn-membrane interactions through a packing-regime-dependent mechanism shaped by both lipid tail chemistry and membrane curvature. This framework helps reconcile opposing reports in the literature and highlights membrane physical state as a key determinant of how cholesterol modulates αSyn binding.
Embryonically, the vertebrate brain begins as an approximately uniform, fluid-filled epithelial tube that undergoes rapid volumetric expansion and regionalization to form the morphologically distinct primary brain vesicles. Hydrostatic pressure from fluid secretion into the inner lumen generates tension in the neural tube that has been implicated as a potential driver of cell proliferation during these early stages of brain development. However, a quantitatively rigorous view of 3D morphology and cellular proliferation has remained elusive. Here, we provide a standardized mapping for the mechanical and biological landscape of the developing neuroepithelium along anatomical axes. Using this 3D morphometric framework in chicken embryos, we show that localized curvature characterizes compartmental boundaries. While rapid inflation would typically be expected to stretch and thin the epithelium, we find the opposite: global expansion is coupled with significant tissue thickening, identifying the early brain as an active shell. Moreover, spatial patterns of thickness remain invariant to local curvature. Our results demonstrate a decoupling of geometry and growth, showing that spatially stable distributions of tissue thickness and mitotic activity are maintained throughout massive volumetric expansion, independent of the dramatic geometric reorganization driven by luminal pressure. We conclude that, while tension in the neuroepithelium may contribute to proliferative growth at some level, biological pre-pattern likely plays a driving role in the regionalized expansion of the early embryonic brain.
Visualizing and quantifying molecular responses to local forces exerted at cell adhesions is crucial to elucidate how physical forces control cellular behavior. Here, we combine optical tweezers with Förster resonance energy transfer (FRET) microscopy of the vinculin tension sensor, VinTS, to measure the response of vinculin, a key mechanical load-bearing protein, to an applied force. Fibroblasts expressing VinTS formed adhesions on fibronectin-coated, 3-μm-diameter, polystyrene beads. As the beads were displaced by the cell, we applied an optical trap to counteract this movement and increase the traction force required by the cell to maintain the bead's displacement. The median bead displacement after 5 min was ∼200 nm in all trapping conditions tested, from zero (no laser) up to 0.26 pN/nm, inducing counteracting forces in the 10-100 pN range. To maintain this displacement, vinculin recruitment increased at high stiffness (up to 35% in relative intensity), while vinculin tension increased only moderately in all trapping conditions (1%-2% decrease in absolute FRET efficiency). Vinculin recruitment was governed by stiffness rather than the magnitude of the traction force and was correlated with vinculin tension at 0.26 pN/nm but not at lower stiffness. In rare instances, vinculin puncta migrated a few micrometers away from the bead, exceeding the bead's movement speed while experiencing an increase in both vinculin intensity and tension. Taken together, the results suggest that combining an optical trap with vinculin tension measurements in living cells uncovers novel vinculin dynamics in the presence of a force.
The regulation of intracellular pH (pHin) and the maintenance of a proton motive force (Δp) are vital processes for cellular viability. Escherichia coli employs different amino acid decarboxylase acid resistance (AR) systems: specifically, Gad (glutamate-dependent), Cad (lysine-dependent), and Adi (arginine-dependent) systems for pHin and pHex regulation under acidic conditions. This study elucidated the pH-dependent roles of these AR systems in the formation and regulation of the Δp components (membrane potential [ΔΨ] and transmembrane proton gradient [ΔpH]) and proton flux rate (JH+) during fermentation at different levels of acid stress: (no stress [pH 7.6], mild acid stress [pH 6.5], moderate acid stress [pH 5.8], and sublethal acid stress [pH 5.4]). The regulatory role of AR systems in Δp and pH homeostasis demonstrated significant special contingent at levels of acid stress. Moreover, AR systems affected the Δp components and the proton flux rate from the cytoplasm to the external environment. Under no acid stress, the Gad system played a role in the regulation of ΔpH by maintaining a higher extracellular pH (pHex). The Adi system demonstrated significance in balancing of Δp components, and the observed compensatory variation in balancing both ΔΨ and ΔpH in ΔadiY mutant emphasized the critical role of Adi in maintaining Δp stability under mild acid stress, pH 6.5. The Cad system was important in regulating ΔpH under moderate acid stress levels by influencing pHin. Under sublethal acid stress, all AR systems were crucially involved in ΔpH regulation and JH+. Thus, our data show that each AR system possesses a crucial and distinct role in Δp formation that is highly dependent on the acid stress level. Moreover, the role of one AR system was, in most cases, not fully compensated by the others, underscoring the importance of these AR systems individually in pH homeostasis in E. coli during fermentation.
How distinct cytoskeletal structures assemble and maintain their characteristic sizes on different timescales while drawing from a shared pool of subunits remains an open question in cell biology. Experiments indicate that mechanisms promoting the disassembly of these structures and replenishing the pool may play a vital role. Here, we compare two disassembly models: one with a constant monomer loss rate and another that is size dependent, where structures lose filament fragments through severing. Using analytical calculations and simulations, we examine their effects on the assembly of two structure types, filaments and bundles composed of linear filaments, both in isolation and when co-assembling in a shared pool. We find that both models control assembly and regulate structure size in distinct ways. However, the assembly of both structures to their steady-state size is accelerated with severing, accompanied by a faster decay of autocorrelations in their length fluctuations. Moreover, we find that severing can regulate multiple structures assembling from a shared pool, constraining them to defined sizes. Our study identifies key parameters governing assembly kinetics and fluctuation dynamics associated with each disassembly mode, highlights measurable quantities such as coefficient of variation and bundle tapering that can help distinguish between different disassembly mechanisms, and reveals specific signatures of structures assembling in a limited monomer pool. Together, these results provide a framework for experiments to identify assembly-control mechanisms in cytoskeletal structures and elucidate the role specific disassembly modes can have in modulating structure formation and maintenance.
Platelets are small, anucleate cells critical for hemostasis and thrombosis. Within platelet plugs and narrow capillaries, they often encounter spatially confining microenvironments. To examine how confinement influences platelet properties, we employed microcontact printing to generate fibrinogen micropatterns of varying sizes and shapes. Platelets cultured on these micropatterns adapted both their morphology and mechanical characteristics. Scanning ion conductance microscopy revealed changes in area, aspect ratio, and height, while fluorescence microscopy showed F-actin redistribution toward the periphery. Confinement reduced platelet stiffness in a size-dependent but shape-independent manner. To explore the role of intracellular signaling, we examined cyclic guanosine monophosphate (cGMP), a key inhibitor of platelet activation, adhesion, and aggregation. Treatment with a cGMP analog preserved F-actin redistribution but prevented stiffness changes in response to confinement, indicating that cGMP inhibits stiffness modulation without affecting cytoskeletal reorganization.
Phenylacetylglutamine (PAGln) and phenylacetylglycine (PAGly) are small molecules derived from the metabolism of phenylalanine by gut microbiota. Elevated levels of PAGln and PAGly in serum have been associated with increased risks for cardiovascular diseases. It has been suggested that PAGln and PAGly reduce cardiac contraction by blunting the adrenergic response during sympathetic stimulation. However, little is known about whether the effect of PAGln and PAGly on the heart function is associated with an alteration of intracellular Ca2+ homeostasis. Here, we studied the effect of PAGly on Ca2+ regulation in mouse ventricular myocytes, as PAGly is the predominant phenylalanine metabolite in rodent's serum. Analysis of cytosolic Ca2+ dynamics revealed that PAGly (100 μM) increases action potential-induced Ca2+ transients and sarcoplasmic reticulum Ca2+ load. These effects of PAGly were significantly smaller than those produced by the adrenergic receptor agonist isoproterenol (ISO; 0.1 μM). The adrenergic receptor blocker propranolol (10 μM) and the protein kinase A inhibitor H89 (10 μM) prevented the PAGly effects on intracellular Ca2+ dynamics. Further analysis of Ca2+ regulation revealed that pretreatment of cardiomyocytes with PAGly reduced the stimulatory effect of ISO on intracellular Ca2+ dynamics. Concurrently, PAGly did not produce any stimulatory effects on intracellular Ca2+ in the presence of ISO. In conclusion, PAGly regulates intracellular Ca2+ dynamics in ventricular myocytes by activating the adrenergic receptor-mediated signaling, but less efficiently than selective adrenergic agonists. By interacting with adrenergic receptors, PAGly might blunt the stimulatory effect of sympathetic stimulation.
Drosophila models have proven invaluable for studying skeletal and cardiac muscle diseases. While permeabilized indirect flight muscle (IFM) and jump muscle fibers from Drosophila yield insightful mechanical data, these preparations cannot resolve the kinetics of activation and relaxation because calcium diffusion into the fiber core is rate limited at this scale. In contrast, myofibrils have a diameter of only 1-3 μm, making them ideal for measuring physiologically relevant activation and relaxation rates. However, previous attempts using IFMs failed to produce myofibrils that generated measurable active force, likely due to the muscle's inherently low force output. Therefore, instead of using IFMs as the source, we developed a method to isolate myofibrils from the Drosophila jump muscle. By applying brief, low-amplitude sonication to permeabilized jump muscles, we isolated myofibrils that produced 19.8 ± 10.5 mN/mm2 net active tension, the first active force measurements from an insect myofibril, with an activation rate of 8.2 ± 4.0 s-1. Jump muscle myofibrils exhibited the typical biphasic relaxation seen in vertebrates: an initial slow, linear phase lasting 75.6 ± 21.1 ms, followed by a fast exponential decay with a rate constant of 19.7 ± 9.6 s-1. We also characterized myofibrils from jump muscles transgenically expressing a Drosophila larval body wall myosin isoform (EMB), which we previously reported displays slower actin-binding and detachment kinetics. EMB expression caused a 1.6-fold increase in active tension and a 38% slower activation rate compared with controls but did not change relaxation parameters. These characterizations and comparisons highlight the scientific value of expressing customizable sarcomeric proteins in transgenic Drosophila jump muscle myofibrils to elucidate their contributions to muscle activation and relaxation.
Escherichia coli swimming motility is powered by the flagellar motor, a rotary nanomachine driven by inward proton flux through its torque-generating stators. How these proton currents arise from proton motive force is often described using a simple circuit model, in which the membrane acts as a capacitor discharging through the flagellar motors and other resistive proton channels. By monitoring the swimming activity of E. coli expressing a light-driven outward proton pump, we probe the dynamical response of the system under tunable optical driving and test the limits of simplified circuit-based description. Our results show that the flagellar motors are not the main sink for proton motive force discharge. Instead, other membrane channels carry a larger proton current and exhibit a nonlinear resistive behavior. Using the same experimental approach, we directly quantify proteorhodopsin pumping activity as a function of illumination wavelength and compare it with previously reported absorption spectra.
Although the transduction process has been well studied in hair cells, the possible presence of mechanical perturbations in the hair cell soma has not been explored in nonmammalian species. Hair cell mechanotransduction involves rapid biophysical events that remain difficult to observe in intact tissue. We developed a label-free optical method to image active motility within the soma during both spontaneous and mechanically driven hair bundle motion. Localized light-intensity fluctuations were detected at distinct focal planes, particularly near the periphery and basal pole of the soma. These optical signals exhibited spectral components that matched those of the hair bundle and were substantially reduced when mechanotransduction channel gating was disrupted, indicating that the somatic activity reflects physiological processes linked to mechanotransduction. Activity hotspots consistently aligned with regions of ionic channels and synaptic contacts, and strong stimulation produced phase-locked somatic responses that diminished after tip-link disruption. These findings parallel reports of mechanical correlates of neuronal activity and support the presence of an optical signature of transduction within the soma. Our results demonstrate that wide-field, label-free imaging can resolve intrinsic optical events in semi-intact sensory epithelia, offering a promising approach for noninvasive studies of hair cell and afferent-neuron signaling.
Vibrational frequency profiling (VFP) using optical tweezers has emerged as a promising technique to characterize single-cell behavior for diagnostic applications. These applications include cancer screening, identifying bacterial resistance to antibiotics, and assessing cellular response to metabolic treatments. Previously, we demonstrated that vibrational profiling can successfully differentiate samples in real time using single-cell vibrational signatures. However, the sensitivity of this approach and its ability to be applied across variable experimental conditions and cell lines have not been well identified. This study builds on previous work, demonstrating the feasibility of our established vibrational analysis to quantitively assess whether changes in experimental design can improve model separation of different cell types.U251 human glioblastoma cells and A549 human lung carcinoma cells were used as our model system. We illustrate this capability through three examples: 1) comparing an open Petri dish to closed microfluidic chambers, 2) synchronizing cells in the cell cycle, and 3) altering medium viscosity. These factors were selected for their potential to influence signal quality and model accuracy. Vibrations were collected using optical tweezers, were Fourier transformed to produce power spectra, and were then parameterized using peak detection, extracting area under the curve values. Peaks were aggregated across samples and classified using partial least squares discriminant analysis. Partial least squares discriminant analysis classification was performed with 70/30 train-test splits of data and 10-fold cross-validation.Petri-dishes yielded a more well-classified sample than microfluidics chambers (F1 score 0.89 vs. 0.79). Synchronized cells reduced vibrational variability and improved classification (F1 score 0.83 vs. 0.79). Increased viscosity produced slight classifier improvements (F1 score 0.81 vs. 0.79). These findings demonstrate that VFPs are sensitive to the mechanical and environmental context of cell measurement, highlighting that careful standardization of experimental conditions is crucial for developing reproducible and clinically translatable VFP-based diagnostic platforms.
The human eye lens plays an essential role in vision by focusing light onto the retina. This transparent tissue consists of densely packed crystallin proteins that exhibit remarkable solubility despite minimal protein turnover. Post-translational modifications that accumulate over a lifetime can reduce crystallin solubility, resulting in the precipitation or phase separation of protein aggregates. Oxidation is a common type of modification that can cause such opacification of the lens, particularly in age-related cataract. Here, we study the oxidation of W163 in γS-crystallin, a structural lens protein that is particularly vulnerable to oxidative stress. We were motivated by previous findings reporting the oxidation of this residue in diseased and UV- and γ-irradiated samples. Using genetic code expansion (GCE), we incorporated an oxidation mimic, 5-hydroxytryptophan (5HTP), at position 163 of γS-crystallin (γS-W163(5HTP)). This subtle change in the structural and electronic properties of its side chain is hypothesized to destabilize the hydrophobic core of the C-terminal domain. γS-W163(5HTP) was characterized and compared to the wild-type (γS-WT). Although the overall fold and stability of the two proteins were comparable, the aggregation of γS-W163(5HTP) was triggered at notably lower temperatures compared to γS-WT. Subsequent investigation of this observation using both simulations and experiments suggests a potential mechanism for polymerization as well as oxidation-induced conformational changes that may cause susceptibility to thermal aggregation. Our findings highlight the utility of GCE platforms for systematically evaluating the impact of post-translational modifications on disease-related proteins.
In adult cardiomyocytes, the type 2a sarco/endoplasmic reticulum Ca2+-ATPase (SERCA2a) plays a vital role in intracellular Ca2+ regulation. Reduced SERCA2a function has been associated with decreased myocardial contraction and cardiac output in several heart diseases. Consequently, increasing SERCA2a activity is a high-priority target for treating cardiac pathologies associated with abnormal Ca2+ homeostasis. In our previous SERCA ATPase-based screening study, we identified several small molecules as potential activators of SERCA2a function, including Compound 9, a piperidinyl amide. With porcine cardiac sarcoplasmic reticulum (SR) preparations, we confirmed activation of both SERCA2a ATPase and Ca2+-uptake activities. In the current study, we analyzed the effect of Compound 9 on SERCA2a activity on intracellular Ca2+ dynamics in ventricular myocytes. Using FRET with human SERCA2a overexpressed in mammalian cells, we confirm that Compound 9 binds and alters SERCA structural dynamics independent of peptide regulators, including phospholamban (PLB). Confocal microscopy and in-cell Ca2+ imaging revealed that Compound 9 enhanced Ca2+ dynamics in mouse ventricular myocytes. Compound 9 (10 μM) increased the action potential-induced Ca2+ transients by 65% and SR Ca2+ load by 29%. Moreover, Compound 9 increased Ca2+ dynamics during adrenergic receptor stimulation and in PLB knockout cardiomyocytes, suggesting the stimulatory effect of Compound 9 is PLB independent. Overall, Compound 9 displays characteristics that can be beneficial to enhance cardiac intracellular Ca2+ dynamics by increasing SERCA2a function.
