Comert Kural

Measuring protein kinetics in living cells remains challenging due to the complexity of intracellular environments and the limitations of live-cell imaging. Clathrin-mediated endocytosis (CME) provides a model system in which protein assembly dynamics encode functional outcomes, yet conventional approaches rely on reconstructing full trajectories of individual events, making them sensitive to tracking errors and difficult to extend to dense or in vivo systems. Here, we review growth rate–based analysis of clathrin assembly as an alternative framework for quantifying endocytic kinetics. By extracting local rates of fluorescence intensity change from short temporal segments, this approach bypasses trajectory reconstruction and instead yields growth rate distributions that robustly capture ensemble dynamics. The standard deviation of these distributions serves as a quantitative metric of kinetic variability and distinguishes distinct dynamical regimes. We highlight how growth-rate analysis reveals key regulatory mechanisms, including membrane tension–dependent modulation of CME and spatiotemporal heterogeneity across cells and tissues, and discuss recent advances leveraging deep learning to infer dynamic behavior from single images. Together, these developments establish a scalable and minimally invasive strategy for measuring protein kinetics in living systems under physiologically relevant conditions.

Clathrin‐mediated endocytosis (CME) relies on the dynamic assembly and remodeling of clathrin coats to drive membrane curvature and vesicle formation at the plasma membrane. Although live‐cell fluorescence microscopy has provided critical insights into the timing and molecular composition of endocytic events, directly linking the nanoscale lateral organization of clathrin coats to their three‐dimensional progression in real time has remained challenging. Structural approaches such as electron microscopy provide detailed snapshots of clathrin architecture but are inherently static, whereas axial TIRF‐based methods report membrane‐proximal position with limited lateral resolution. Here, we introduce variable‐angle total internal reflection fluorescence structured illumination microscopy (vaTIRF‐SIM), a live‐cell imaging strategy that integrates lateral super‐resolution with dynamic axial sensitivity near the plasma membrane. By combining TIRF‐SIM with controlled variation of the evanescent field penetration depth, vaTIRF‐SIM enables simultaneous visualization of clathrin coat architecture and relative axial displacement with high spatial and temporal resolution. Applying this approach to de novo clathrin‐coated pits reveals coordinated lateral growth and progressive axial advancement from early stages of pit formation through maturation, consistent with early curvature generation that intensifies over time. Extending this analysis to clathrin plaques uncovers two distinct plaque‐associated endocytic behaviors: slowly maturing pits that originate at plaque peripheries and progress similarly to de novo pits and rapid plaque subdomain internalization events marked by accelerated axial progression. Together, these results establish vaTIRF‐SIM as an approach that, for the first time, enables direct real‐time coupling of nanoscale clathrin coat organization with axial progression during CME in living cells, demonstrated here in genome‐edited SUM‐159 cells expressing AP2‐EGFP from the endogenous locus.

Clathrin-mediated endocytosis (CME) relies on the dynamic assembly and remodeling of clathrin coats to drive membrane curvature and vesicle formation at the plasma membrane. Although live-cell fluorescence microscopy has provided critical insights into the timing and molecular composition of endocytic events, directly linking the nanoscale lateral organization of clathrin coats to their three-dimensional progression in real time has remained challenging. Structural approaches such as electron microscopy provide detailed snapshots of clathrin architecture but are inherently static, whereas axial TIRF-based methods report membrane-proximal position with limited lateral resolution. Here, we introduce variable-angle total internal reflection fluorescence structured illumination microscopy (vaTIRF-SIM), a live-cell imaging strategy that integrates lateral super-resolution with dynamic axial sensitivity near the plasma membrane. By combining TIRF-SIM with controlled variation of the evanescent field penetration depth, vaTIRF-SIM enables simultaneous visualization of clathrin coat architecture and relative axial displacement with high spatial and temporal resolution. Applying this approach to de novo clathrin-coated pits reveals coordinated lateral growth and progressive axial advancement from early stages of pit formation through maturation, consistent with early curvature generation that intensifies over time. Extending this analysis to clathrin plaques uncovers two distinct plaque-associated endocytic behaviors: slowly maturing pits that originate at plaque peripheries and progress similarly to de novo pits, and rapid plaque subdomain internalization events marked by accelerated axial progression. Together, these results establish vaTIRF-SIM as an approach that, for the first time, enables direct real-time coupling of nanoscale clathrin coat organization with axial progression during CME in living cells.

Cell migration through confined spaces is a critical step in cancer metastasis, yet the spatial regulation of endocytosis and adhesion dynamics during this process remains poorly understood. To investigate this, we adapted a microfluidic platform that generates stable, spatially linear biochemical gradients across 5 μm-tall migration channels. COMSOL simulations and optical calibration using FITC-dextran confirmed that gradients form reliably within 5 min. The microdevice also supports long-term live imaging and is compatible with both spinning disk confocal and total internal reflection fluorescence structured illumination microscopy modalities, enabling high-resolution visualization of adhesion and endocytic structures. By leveraging this platform for spatially restricted drug delivery, we locally applied the endocytic inhibitor Dyngo-4a to either the front or rear of migrating cells. This revealed that front-targeted endocytic inhibition preserved or increased leading-edge enrichment of paxillin and the clathrin adaptor AP-2, whereas rear-targeted inhibition eliminated paxillin polarity and reduced AP-2 polarity. These changes were accompanied by a significant increase in cell migration speed under front-targeted inhibition, while rear-targeted inhibition had no significant effect on speed and neither treatment altered persistence. Together, these findings suggest that endocytic polarity regulates adhesion dynamics and cell migration under confinement, offering a mechanistic insight into processes relevant to cancer cell invasion.

Clathrin-mediated endocytosis (CME) is a vital cellular process that exhibits spatial and temporal heterogeneity in its dynamics, traditionally studied through labor-intensive time-lapse microscopy and single particle tracking. To overcome the limitations posed by phototoxicity, temporal undersampling, and computational complexity, we introduce a deep learning framework that infers CME dynamics from single fluorescence images. Using a modified U-Net architecture, our model predicts spatial maps of the standard deviation (SD) of clathrin coat growth rates—an established metric of CME activity—directly from static frames of AP2-eGFP–labeled cells. The network was trained on paired image data and SD maps derived from experimentally tracked endocytic events. The model accurately recapitulates dynamic features such as front–rear asymmetry in migrating cells and responses to membrane tension alterations, demonstrating strong agreement with traditional time-lapse-derived metrics. This approach eliminates the need for trajectory reconstruction or prolonged imaging, enabling real-time, non-invasive assessment of endocytic dynamics across diverse biological contexts. Our results highlight the potential of deep learning to extract dynamic biophysical information from static imaging data and establish a scalable methodology for probing CME and related subcellular processes.

Cell migration through confined spaces is a critical step in cancer metastasis, yet the spatial regulation of endocytosis and adhesion dynamics during this process remains poorly understood. To address this, we developed a microfluidic platform that generates stable, spatially linear biochemical gradients across 5 μm-tall migration channels while limiting confounding flow-induced shear stress (2 ). COMSOL simulations and optical calibration using FITC-dextran confirmed that gradients form reliably within 5 minutes. The microdevice also supports long-term live imaging and is compatible with both spinning disk confocal and total internal reflection fluorescence structured illumination microscopy modalities, enabling high-resolution visualization of adhesion and endocytic structures. Localized application of the endocytic inhibitor Dyngo-4a to the front or rear of migrating cells revealed that front-targeted inhibition significantly increased the enrichment of paxillin and the clathrin adaptor AP-2 at the leading edge, whereas rear-targeted inhibition completely abolished their front-rear asymmetry. These changes were accompanied by enhanced migration speed and persistence, particularly under front-targeted inhibition. Together, these findings highlight the critical role of spatially coordinated endocytosis in sustaining polarized adhesion and persistent cell movement. Our platform offers a powerful tool for dissecting subcellular mechanisms of migration under confinement and provides a broadly applicable framework for probing spatially localized signaling in engineered microenvironments.

Evading programmed cell death (PCD) is a hallmark of cancer that allows tumor cells to survive and proliferate unchecked. Endocytosis, the process by which cells internalize extracellular materials, has emerged as a key regulator of cell death pathways in cancer. Many tumor types exhibit dysregulated endocytic dynamics that fuel their metabolic demands, promote resistance to cytotoxic therapies, and facilitate immune evasion. This review examines the roles of endocytosis in apoptotic resistance and immune escape mechanisms utilized by cancer cells. We highlight how inhibiting endocytosis can sensitize malignant cells to therapeutic agents and restore susceptibility to PCD. Strategies to modulate endocytosis for enhanced cancer treatment are discussed, including targeting endocytic regulatory proteins, altering membrane biophysical properties, and inhibiting Rho-associated kinases. While promising, challenges remain regarding the specificity and selectivity of endocytosis-targeting agents. Nonetheless, harnessing endocytic pathways represents an attractive approach to overcome apoptotic resistance and could yield more effective therapies by rendering cancer cells vulnerable to PCD. Understanding the interplay between endocytosis and PCD regulation is crucial for developing novel anticancer strategies that selectively induce tumor cell death.

The transmembrane death receptor Fas transduces apoptotic signals upon binding its ligand, FasL. Although Fas is highly expressed in cancer cells, insufficient cell surface Fas expression desensitizes cancer cells to Fas-induced apoptosis. Here, we show that the increase in Fas microaggregate formation on the plasma membrane in response to the inhibition of endocytosis sensitizes cancer cells to Fas-induced apoptosis. We used a clinically accessible Rho-kinase inhibitor, fasudil, that reduces endocytosis dynamics by increasing plasma membrane tension. In combination with exogenous soluble FasL (sFasL), fasudil promoted cancer cell apoptosis, but this collaborative effect was substantially weaker in nonmalignant cells. The combination of sFasL and fasudil prevented glioblastoma cell growth in embryonic stem cell-derived brain organoids and induced tumor regression in a xenograft mouse model. Our results demonstrate that sFasL has strong potential for apoptosis-directed cancer therapy when Fas microaggregate formation is augmented by mechano-inhibition of endocytosis.

Integrin-based adhesion complexes are crucial in various cellular processes, including proliferation, differentiation, and motility. While the dynamics of canonical focal adhesion complexes (FAs) have been extensively studied, the regulation and physiological implications of the recently identified clathrin-containing adhesion complexes (CCACs) are still not well understood. In this study, we investigated the spatiotemporal mechanoregulations of FAs and CCACs in a breast cancer model. Employing single-molecule force spectroscopy coupled with live-cell fluorescence microscopy, we discovered that FAs and CCACs are mutually exclusive and inversely regulated complexes. This regulation is orchestrated through the modulation of plasma membrane tension, in combination with distinct modes of actomyosin contractility that can either synergize with or counteract this modulation. Our findings indicate that increased membrane tension promotes the association of CCACs at integrin αVβ5 adhesion sites, leading to decreased cancer cell proliferation, spreading, and migration. Conversely, lower membrane tension promotes the formation of FAs, which correlates with the softer membranes observed in cancer cells, thus potentially facilitating cancer progression. Our research provides novel insights into the biomechanical regulation of CCACs and FAs, revealing their critical and contrasting roles in modulating cancer cell progression.

Biological images captured by microscopes are characterized by heterogeneous signal-to-noise ratios (SNRs) due to spatially varying photon emission across the field of view convoluted with camera noise. State-of-the-art unsupervised structured illumination microscopy (SIM) reconstruction algorithms, commonly implemented in the Fourier domain, do not accurately model this noise and suffer from high-frequency artifacts, user-dependent choices of smoothness constraints making assumptions on biological features, and unphysical negative values in the recovered fluorescence intensity map. On the other hand, supervised methods rely on large datasets for training, and often require retraining for new sample structures. Consequently, achieving high contrast near the maximum theoretical resolution in an unsupervised, physically principled, manner remains an open problem. Here, we propose Bayesian-SIM (B-SIM), an unsupervised Bayesian framework to quantitatively reconstruct SIM data, rectifying these shortcomings by accurately incorporating known noise sources in the spatial domain. To accelerate the reconstruction process, we use the finite extent of the point-spread-function to devise a parallelized Monte Carlo strategy involving chunking and restitching of the inferred fluorescence intensity. We benchmark our framework on both simulated and experimental images, and demonstrate improved contrast permitting feature recovery at up to 25% shorter length scales over state-of-the-art methods at both high- and low-SNR. B-SIM enables unsupervised, quantitative, physically accurate reconstruction without the need for labeled training data, democratizing high-quality SIM reconstruction and expands the capabilities of live-cell SIM to lower SNR, potentially revealing biological features in previously inaccessible regimes.