Biophysical Reports

Fluorescent reporters such as fluorescent proteins or chemigenetic indicators are indispensable tools for studying biological processes using light microscopy. Choosing an appropriate fluorescent tag is a crucial step in experimental design not only for imaging but also for quantitative measurements such as fluorescence fluctuation spectroscopy. Two key parameters should be considered: Fluorescent brightness and photo-bleaching. Change to fluorescence intensity due to photobleaching is relatively easy to assess in different biological environments, while brightness is more elusive. Here, we develop and employ a fluorescence correlation spectroscopy (FCS) based excitation scan assay that determines fluorescent protein performance and validate it in tissue culture and zebrafish embryos. We employ our FCS pipeline to compare a set of 10 established fluorescent proteins as well as HALO and SNAP tags for both cellular imaging and measurements of diffusion dynamics with FCS. We show that mNeonGreen outperforms mEGFP in tissue culture and zebrafish embryos. We also compare StayGold variants against other green fluorescent proteins and chemigenetic reporters in tissue culture. Overall, we present a broadly applicable approach for determining fluorescent reporter brightness in the living system of interest.

Quantitative knowledge of nanoparticle properties is desirable in a large number of scientific and technological applications, but measurements with a high degree of precision usually prove to be challenging. Among a range of available methodologies, optical techniques with single particle sensitivity are especially interesting because they can reveal intrinsic hetero-geneities in a fast non-invasive manner. Recently, we presented interferometric nanoparticle tracking analysis (iNTA) as a highly sensitive label-free technique that is capable of determining the size, concentration and index of refraction of different subpopulations in a suspension mixture. Here, we enhance this method with biochemical specificity through multicolor fluorescence detection at the single-molecule sensitivity limit. We benchmark the performance of the combined technique, which we name iNTA-F, by distinguishing populations of fluorescent and non-fluorescent nanoparticles of different material, size, and fluorescence intensity, with an emphasis on the characterization of lipid vesicles and biological extracellular vesicles (EVs).

Fluorescence imaging of dense cellular regions of interest (ROIs) in cells using fluorescence microscopy provides detailed images with pixels that report ensemble- and time-averaged biomolecular data, due to the diffraction limit when super-resolution modalities are not used and acquisition times are slower than typical biomolecular mobilities. The fluorescently-tagged biomolecules that are undergoing imaging can be more heterogeneous and dynamic, all within the dimensions of a single acquired image pixel. The ability to acquire data one biomolecule at a time within a given ROI can help recover some of the underlying biomolecular subpopulations that are otherwise averaged out. In this work, we present a relatively simple approach to achieving single-biomolecule photon bursts, BLeaching In-cell Single-molecule burstS (BLISS). We reveal millisecond photon bursts arising from clusters of mCherry-tagged heterochromatin protein 1 (mCherry-HP1) within heterochromatin biomolecular condensates in undifferentiated mouse embryonic stem cells (ESCs). Fluorescence lifetimes of these bursts are substantially lower than the averaged-out values observed per pixel in fluorescence lifetime imaging microscopy (FLIM), attributed to higher density in mCherry-HP1 clusters. These higher density clusters are observed primarily in undifferentiated ESCs. Two days after retinoic acid (RA) induction of differentiation, these bursts are rarely observed. In summary, using BLISS, we revealed a rare subpopulation of dense mCherry-HP1 clusters characterized by rapid, millisecond dynamics. These clusters are part of heterochromatin biomolecular condensates in ESCs at the pluripotent state, which would be otherwise averaged out in diffraction-limited fluorescence microscopy.

It is an essential element of mechanobiology to measure the forces of biological cells. In microparticle traction force microscopy, they are inferred from the deformation of elastic microparticles. Two complementary variants have been introduced before: the volume method, which reconstructs surface stresses from the displacements of fiducial markers embedded inside the particles, and the surface method, which infers stresses directly from the deformation of the particle surface. However, a systematic comparison of the two methods has been lacking. Here, we quantitatively compare both approaches using simulated traction fields representing biologically relevant loading scenarios. We find that the surface method consistently reconstructs traction profiles with substantially lower errors than the volume method, which suffers from displacement tracking and stress calculation at the surface. At high noise levels, however, the performance gap becomes smaller. To compare the performance of the two methods in a realistic experimental setting, we developed DNA-based hydrogel microparticles equipped with both fluorescent surface labels and embedded fluorescent nanoparticles, enabling the direct comparison of the two methods within the same system. Compression experiments produced traction profiles consistent with Hertzian contact mechanics and confirmed the trends observed in the simulations. While our computational workflow establishes a framework to apply both methods, our experimental workflow establishes DNA microparticles as versatile and biocompatible probes for measuring cellular forces.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional two-dimensional single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from three-dimensional single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria, and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

For decades, the photon counting histogram (PCH) was used as the sole method to quantify fluorophore numbers in a diffraction-limited focal volume. This technique combines spatial excitation profiles, and the distribution of photon counts to register the photon emission statistics of individual fluorophores. However, this approach has not yet been transferred to widefield fluorescent imaging due to the lack of fast and single photon sensitive camera sensors which can capture the photon emission statistics of a single fluorophore. Here, we explore avenues towards quantitative analysis of the active fluorophore number by leveraging recent advancements in single photon avalanche diode (SPAD) array technology. Binary exposures of a SPAD array can be synchronized with picosecond laser pulses to measure the PCH in a widefield setting. Then, by modeling the statistical relationship between the active fluorophore number and the PCH in a region of interest following a laser pulse, we can perform Bayesian inference of this number. The model is demonstrated experimentally by counting quantum dots and various numbers of fluorescent dye molecules bound to DNA origamis. We find that this method has several important applications in widefield microscopy, including enhanced localization microscopy and constrained fitting of multiple unresolvable fluorescent emitters.

Fluorescence Lifetime Imaging Microscopy (FLIM) enables quantitative mapping of molecular environments in living systems with high biochemical specificity. However, spatial overlap dictated by the diffraction-limited point spread function (PSF) causes a mixing of temporal signals: photons from neighboring emitters collected within the same pixel yield composite decay profiles, generating apparent intermediate lifetimes that can be mistaken for variations in the local molecular environment. We introduce a workflow that applies Mean-Shift Super-Resolution (MSSR) to raw intensity data to generate intensity-derived spatial masks prior to phasor-based lifetime analysis. The method is computationally efficient and preserves decay kinetics because it operates on intensity-derived spatial information rather than modifying temporal data. In U2OS cells labeled with spectrally-overlapping fluorophores, phasor analysis reveals an intermediate lifetime population localized at PSF-overlap interfaces, consistent with optical mixing rather than intrinsic lifetime heterogeneity. MSSR-derived masking suppressed this mixed population while preserving stable phasor cluster centers -i.e. the distribution of similar phasor coordinates in the phasor plane- for each fluorophore. Simulations of strictly monoexponential fluorescence decay emitters further show that blended lifetime decay profiles are present at separations up to 4{sigma} and becomes maximal near [~]1.6{sigma}, indicating that conventional spatial resolution criteria can underestimate lifetime cross-talk. Application of this workflow to three-component FLIM showed also a reduced overlap of pixel distributions in phasor plots while maintaining distinct lifetime signatures. Overall, MSSR-based spatial refinement provides an accessible strategy to improve the spatial resolution while maintaining accuracy of FLIM measurements.

Ultraweak photon emission is the spontaneous emission of extremely low levels of light from a broad range of biological systems. Recent studies have reported that UPE measured extracranially can serve as a potential non-invasive biomarker of brain activity. Here, we show that this interpretation suffers from serious problems. First, when observed under properly dark conditions, the UPE from the head is much weaker than what is reported in certain papers on brain UPE from human heads. Signals detected in these studies are overwhelmingly dominated by background light. Second, photons at wavelengths < 600 nm are strongly attenuated by scalp and skull tissues, and longer wavelengths fall largely outside the effective spectral sensitivity of the photomultiplier tubes (PMTs) used. As a consequence, even if UPE from the head is detected under properly background-free conditions, it is likely to be dominated by emission from the scalp rather than from the brain, certainly as long as PMTs are used. Our results emphasize the importance of careful experimental design to make genuine progress on this important question.

The apparent pKa of ionizable lipids in lipid nanoparticles (LNPs) is a key determinant of RNA encapsulation during formulation and endosomal release after cellular uptake. However, it is difficult to predict the effective pKa of a given ionizable lipid solely from its solution pKa, because it is sensitive to the membranes composition, as well as solution conditions such as the salt concentration. We developed a simple continuum electrostatics model, based on Gouy-Chapman theory, to predict the shift in effective pKa for ionizable lipids in lipid bilayers as a function of salt concentration and membrane composition. We derive equations for the surface potential and fraction of lipids charged, which are solved self-consistently as a function of solution pH to extract the titration curve and effective pKa. The model shows that the shift in effective pKa is largest when the concentration of titratable lipid is high, and the effect is diminished by increasing salt concentration. We provide a python implementation of the model and an interactive notebook that will allow users to further easily explore the predicted pKa shifts as a function of formulation variables.

Single-molecule localization microscopy (SMLM) methods enable fluorescence imaging of biological specimens with nanometer-scale resolution. Although fluorophore localization precision is theoretically limited only by photon statistics, in practice the resolution of SMLM images is often degraded by physical drift of the sample and/or the microscope during data acquisition. At present, correcting this effect requires either specialized stabilization systems or computationally intensive post-processing, and established drift correction algorithms based on image cross-correlation suffer from limited temporal resolution. In this study we introduce COMET, a new method for SMLM drift estimation which achieves a substantially higher precision, accuracy, and temporal resolution compared with existing algorithmic approaches. We demonstrate that improved drift estimation translates directly into higher SMLM image resolution, limited by localization precision rather than drift artifacts. COMET is applicable to all types of SMLM data, operating directly on 2D or 3D localization datasets, and is readily integrated into analysis workflows. We benchmark its performance using both simulations and experiments, including STORM, MINFLUX, and Sequential OligoSTORM measurements, where long acquisition times make drift correction particularly challenging. COMET is published as an open-source, Python-based software project and is also available on open cloud-computing platforms.

Fluorescence resonance energy transfer (FRET) is the highly distance dependent (3-10 nm) transfer of energy from a donor to an acceptor fluorophore, with transfer efficiency inversely proportional to the distance between the fluorophores. Consequently FRET serves as a powerful spectroscopic ruler for probing molecular interactions. Whilst cell based FRET assays report bulk relative changes in FRET efficiency in a population, single molecule FRET (smFRET) is capable of deconvoluting these population averages into distinct structural states. However, the lack of universal benchmarks prevents the direct translation of in vitro distance measurements to the intracellular environment and vice versa. Here, we present a modular protein ladder designed to harmonize FRET data across diverse platforms. Using an engineered repeating TPR motif and self-labeling enzymes, we demonstrate that our standards yield consistent FRET efficiencies across expression systems (mammalian and bacterial) and labelling strategies (self labelling enzymes and click chemistry with non-canonical amino acids). By providing a predictable calibration curve, the ladder enables interpolation between different experimental FRET modalities, including confocal smFRET, flow cytometry based-FRET and Fluorescence Lifetime Imaging Microscopy FRET (FLIM-FRET). This is the necessary infrastructure to relate molecular distances from the test tube to the cell.

Mitochondrial membrane potential ({Delta}{Psi}m) is central to ATP production, ion homeostasis, and cell survival, reflecting the functional state of the inner mitochondrial membrane and oxidative phosphorylation. Accurate assessment of {Delta}{Psi}m is therefore essential for understanding mitochondrial physiology and dysfunction in health, ageing, and disease. Lipophilic cationic fluorescent dyes, such as TMRM and TMRE, are widely used to monitor {Delta}{Psi}m in live cells, enabling high-temporal-resolution imaging of both steady-state membrane potential and dynamic fluctuations. Beyond stable bioenergetic measurements, live-cell imaging reveals transient, reversible depolarisation events, known as mitochondrial "flickers." These events, observed across multiple cell types and imaging platforms, are often associated with brief openings of the mitochondrial permeability transition pore (mPTP) and may represent regulated mitochondrial excitability, rather than irreversible damage. While excessive or synchronised depolarisations may signal mitochondrial injury, transient flickers are increasingly viewed as potential signalling mechanisms within the mitochondrial network. This work discusses methodological considerations for {Delta}{Psi}m imaging, the biological significance of mitochondrial flickers, and the importance of distinguishing physiological events from probe- and light-induced artefacts, highlighting the emerging concept of mitochondria as dynamic and communicative bioenergetic networks.

Mechanical forces transmitted through focal adhesions regulate cell behavior and disease progression, yet remain difficult to quantify at the molecular level. Genetically encoded FRET-based tension probes enable measurements of piconewton-scale forces across specific proteins in living cells, but their quantitative interpretation is highly sensitive to probe design and measurement modality. Here, we systematically compared vinculin tension sensors under identical experimental conditions, evaluating unloaded reference constructs, fluorophore pairs, mechanical sensor modules, and circularly permuted variants. Unloaded controls established a common no-force baseline and validated force-dependent readout. Among the fluorophore pairs tested, the green-red combination Clover-mScarlet-I yielded a higher unloaded FRET efficiency and hence a broader measurable dynamic range. Comparison of six mechanical sensor modules identified the binary-response sensors FL and CC-S2 as the most responsive, showing the largest force-dependent FRET changes and broadest FRET distributions. At the sub-focal adhesion level, CC-S2 reported the steepest proximal-to-distal tension gradient, indicating that vinculin tension increases sharply along peripheral adhesions and exceeds 10 piconewton. Circular permutation experiments revealed that fluorophore orientation has a strong, module-dependent influence on the measured FRET readout. Together, these results establish a comparative framework for interpreting FLIM-based vinculin tension measurements and provide practical design principles for selecting and engineering molecular tension probes.

The spatial resolution of optical imaging systems is fundamentally restricted by the diffraction limit. However, in widefield live-cell microscopy, the achievable resolution is further constrained by the specimen motion, which indicates the existence of a fundamental spatio-temporal resolution trade-off between signal accumulation during the full frame integration and the resulting motion blur. To improve the fidelity with which moving objects can be imaged, a quantitative understanding of this spatio-temporal trade-off is necessary. Here, we present a systematic analysis of motion-induced resolution dynamics measured with spectral signal-to-noise ratio (SSNR). We developed a simulation framework which models the image formation of objects undergoing arbitrary motion, to evaluate the degradation of the spatial resolution under translational and rotational dynamics. Our results demonstrate that for translating objects, the spatial resolution is anisotropically reduced as a function of the orientation of the object relative to the motion vector, leading to the spectral signal-to-noise ratio degrading by up to 50% and the resolution by up to 40% for a 90{degrees} change in the motion direction. Furthermore, we show that for rotational motion, conventional radially averaged metrics such as the Fourier Ring Correlation are not able to quantify the effects of angular blur. On the other hand, the SSNR is able to accurately quantify this degradation. These findings underscore the necessity of an object-oriented imaging approach, in which acquisition parameters such as exposure time are tuned to specific biological spatio-temporal characteristics to optimize the trade-off between motion blur and spatial fidelity.

Quantum effects in biology are unavoidable at the molecular scale; the unresolved question is whether they can remain functionally relevant across the timescale gap between femtosecond molecular dynamics and microsecond-to-millisecond biological function. Here we formalize this mismatch as an equilibrium-to-functionality gap and use tubulin as a stringent open-system test case. We combine secular Lindblad, Redfield, and hierarchical equations of motion (HEOM) treatments to quantify decoherence, non-perturbative relaxation, and the physical amplification required for functional relevance. Equilibrium dephasing yields a conservative [Formula] fs at 310 K, with a generic protein-bath baseline of {approx} 13 fs. A completed 30 ps HEOM trajectory for the full 1JFF tryptophan network shows distributed non-Markovian relaxation, with terminal purity Pur = 0.210 and stretched-exponential exponent {beta}KWW {approx} 0.44, confirming that Redfield is useful as a short-time perturbative comparator but not quantitatively interchangeable with HEOM in this intermediate-coupling regime. We introduce a coherence-utility criterion [U] = [K]{tau}coh/{tau}func, separating required amplification from empirically bounded gain. A thermodynamic uncertainty relation closure shows that neural-scale cascade amplification would require Pmin [~] 10-7 W, about five orders of magnitude above the local microtubule GTP budget. Frohlich pumping is found to be linewidth-gated rather than generically micron-scale; ordered-water cavity QED and geometric subradiance remain experimentally testable but severely constrained candidates. The result is not a model of consciousness, but a reproducible physical benchmark framework for evaluating biological quantum-coherence claims under explicit open-system, energetic, and experimental constraints. Six falsifiable experimental programmes are prioritized, and the full computational framework is released with a validation ledger, cryptographic audit trail, and living supplementary material. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/724047v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@19e4f42org.highwire.dtl.DTLVardef@65a719org.highwire.dtl.DTLVardef@1bd63beorg.highwire.dtl.DTLVardef@df77d8_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO Equilibrium tubulin coherence lies in the femtosecond regime, while functional neural timescales lie in the millisecond regime. Frohlich pumping, QED-cavity protection, and geometric subradiance remain experimentally discriminable non-equilibrium candidates requiring independently bounded amplification. C_FIG FundingThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Versioned computational scope of this releaseThis manuscript reports the theoretical framework, calibrated equilibrium baseline, Redfield/HEOM validation ledger, stratified Bayesian evidence synthesis, classical comparators, and falsifiable experimental design. The release-specific reproduction audit, including the current validation-check total and the SHA-256 fingerprints of the binary production artefacts (.npz, .pkl), is documented in LIVING_SI.md and outputs_data/raw_json/structur al/validation_report.json. A completed 30 ps HEOM production trajectory has been validated on constrained hardware; the master dataset contains the full 8-site population trajectory. A summary of those results is provided in [&#167;]2.2.5. All claims made below are restricted to the numerical and theoretical evidence reported in this manuscript and its associated repository artefacts. The public repository ships the calibrated phenomenological baseline for accessibility; the HEOM production artefacts serve as the non-perturbative validation benchmark. All source figure outputs associated with this release are maintained in the public repository under outputs_data/figures_final/.

Developing active transport systems for microcargo delivery is challenging and requires overcoming the low Reynolds number constraints. We developed a bio-hybrid micro-swimmer, "chlamylipo" consisting of the green alga Chlamydomonas reinhardtii, encapsulated within a giant liposome. Although internal encapsulation offers cargo protection, it requires a mechanism to transmit the propulsion force across a closed membrane. We demonstrated that chlamylipo exhibited forward swimming and phototactic directional control. High-speed imaging of membrane shape and fluid flow revealed that the driving force originated from periodic membrane deformations and was accompanied by characteristic fluid dynamics. Flow analysis showed rapid oscillations at tens of hertz corresponding to flagellar beating, superimposed on slower axial migration at approximately 4 Hz associated with cell rotation. Corresponding flow signatures were also detected in the external fluid, indicating mechanical coupling across the lipid bilayer. Membrane domain tracking further showed that fluid motions inside and outside the membrane were coupled through viscous friction and membrane deformation, generating a characteristic four-vortex flow field consistent with a two-point force model. Together, these results suggest that membrane flow mainly reflects force transmission across the bilayer, whereas forward propulsion is primarily driven by periodic membrane deformation. This study elucidates the physical mechanism of force transmission in encapsulated swimmers, demonstrating that internal hydrodynamic power can effectively drive the motion of macroscopic containers. SignificanceThe development of autonomous micro-swimmers for targeted drug delivery is a major challenge in biophysics. We present "chlamylipo," a hybrid system in which a swimming alga is encapsulated inside a lipid vesicle. This study is significant because it demonstrates that an enclosed swimmer can propel a macroscopic container solely via hydrodynamic coupling across a closed membrane without direct external mechanical links. Furthermore, we achieved external directional control using phototaxis. This study provides physical insights into fluid-membrane interactions and proposes a novel strategy for designing light-guided active transport carriers.

Investigations of G protein-coupled receptors (GPCRs) interactions with non-visual arrestins in living cells are essential to understanding the complex molecular mechanisms of GPCR-based signaling. Quantitative analysis of these interactions remains challenging in live cells, particularly when attempting to repeatedly image distinct cellular regions with high precision. Here, we describe the implementation of an optical imaging stabilization approach that integrates the recently developed Focal Readjustment for Enhanced Vertical Resolution (FREVR) technology into a multiphoton microscope, enabling high-precision alternation between image-forming sample planes with < 20-nanometer repeatability and stability over time. Using this setup, we monitored the dynamic recruitment of arrestin-2 (Arr2) to the plasma membrane of HEK-293 cells expressing muscarinic acetylcholine M2 receptors (M2R) by alternatively imaging distinct planes of interest, the basolateral membrane and a membrane cross-section. Following stimulation of M2R by agonist ligand, we observed a pronounced redistribution of cytoplasmic arrestin-2 toward the plasma membrane in both cellular cross-sections and at the basolateral membrane. This method enables direct comparison of receptor and arrestin dynamics across regions of individual cells with very high precision, eliminating the need for averaging over numerous cells in order to denoise biologically relevant signals, and thereby capturing physiological cell-to-cell variability.

Fluorescent proteins (FPs) are essential tools for biological imaging but are limited by photobleaching, a light-induced loss of fluorescence intensity that reduces spatial and temporal resolution. Despite extensive use, the molecular mechanisms underlying FP photobleaching remain poorly understood due to the diversity of FPs and the complexity of their photochemistry. Existing approaches either monitor fluorescence decay in live cells, reflecting imaging conditions but lacking molecular detail, or rely on in vitro spectroscopy of purified proteins, providing mechanistic insight but often limited to individual FPs. We introduce a quantitative workflow bridging these approaches by combining live-cell measurements with in vitro spectroscopy. In vitro measurements are performed on a dedicated setup that simultaneously monitors absorption, emission, and fluorescence decay during photobleaching. Applied to six FPs spanning different chromophores, emission ranges and sequences, this approach reveals that photobleaching strongly depends on FP. It involves multiple chemical pathways, including oxidation, dimerization, and backbone cleavage. Spectroscopic analysis uncovers a heterogeneous ensemble of photoproducts with distinct photophysical properties that can remain optically active during irradiation, including shortened fluorescence lifetimes or altered absorption spectra. These findings demonstrate that FP photobleaching cannot be described as a simple ON-OFF process but involves complex transformations affecting both fluorescence intensity and lifetime. Such transformations can introduce significant biases in quantitative imaging, particularly in advanced techniques such as FLIM and FRET. Finally, we introduce quantitative indicators enabling robust comparison of FP photostability across experimental conditions. This framework provides a comprehensive approach for understanding and quantifying photobleaching and its implications for fluorescence imaging.

Optical microscopy is fundamental to modern life-science research, yet interpreting its results requires precise modelling of point spread functions (PSFs) within complex environments. This manuscript introduces a versatile and efficient approach to wave-optical PSF calculations that extends existing frameworks by incorporating detection PSF modelling through the principle of reciprocity. Accompanying this work is a free MATLAB software package centred on a single, minimalistic core function, PlaneWaveExc.m, which utilizes a plane-wave superposition based on the Richards-Wolf model. Despite its simplicity, the framework accounts for "real-life" complexities such as systemic aberrations, arbitrary amplitude and phase modulations, and stratified media with complex-valued refractive indices. We demonstrate the softwares broad applicability through diverse case studies, including single-molecule imaging, STED microscopy, the segmented aperture of the James Webb Space Telescope, and coherent wide-field iSCAT microscopy. Each example is supported by dedicated scripts to facilitate adaptation for specific research needs.

Membrane binding is thought to trigger early aggregation of alpha-synuclein (aSyn) in neurons. However, live-cell measurements of membrane-proximal aggregation with high specificity remain challenging. We combine three- channel fluorescence lifetime imaging microscopy (FLIM) with Forster resonance energy transfer (FRET) in a model that uses FRET as a proximity filter. A membrane-tethered donor reports membrane-aSyn separation through lifetime changes, while an aSyn-labeled acceptor reports the aggregation state through its lifetime. We estimate per-cell lifetimes and mixture fractions for membrane-bound and membrane-unbound populations using a hierarchical expectation-maximization (EM) algorithm that pools information across pixels. We validate the estimator using Monte Carlo studies. Using experimental neuronal data, this method resolves changes in membrane-proximal aggregation and aggregate-associated lifetimes. This framework provides quantitative per-cell metrics linking membrane proximity and aggregation for comparative live-cell studies. SIGNIFICANCEMany studies map FRET signals pixel by pixel or average signals over whole cells. Neither approach reliably answers key biological questions: how much membrane-proximal aggregation exists in a given cell, and how does it change across conditions? Here, we combine three-channel FLIM-FRET with a hierarchical analysis that estimates per-cell lifetimes and fractions for bound and unbound populations by pooling information across pixels. This method shifts the focus from noisy images to cell-level metrics that support comparisons across treatments, time points, or genotypes. Simulations and neuronal data show improved accuracy under realistic photon budgets and reveal membrane-proximal aggregation effects that were unattainable otherwise. This approach is broadly applicable and extends beyond alpha-synuclein.