Biophysical Reports

Flipper-TR is a membrane dye sensitive to lipid packing widely used to probe membrane tension in live cells via fluorescence lifetime imaging microscopy (FLIM). However, no consensus currently exists on the optimal strategy for extracting lifetime values, particularly across varying experimental setups and biological systems. Here, we systematically compare multiple approaches to estimate Flipper-TR lifetime, including multi-exponential reconvolution fitting, tail fitting, mean photon arrival time (first moment), and phasor analysis. These estimators are tested against changes in photon budget, sample characteristics, microscope manufacturer, and laser frequency. This offers a comprehensive benchmark and decision-making framework for quantitative FLIM analysis of Flipper dyes in various contexts.

FRET imaging is an essential analytical method in biomedical research. The limited photon-budget experimentally available, however, imposes compromises between spatiotemporal and biochemical resolutions, photodamage and phototoxicity. The study of photon-statistics in biochemical imaging is thus important in guiding the efficient design of instrumentation and assays. Here, we show a comparative analysis of photon-statistics in FRET imaging demonstrating how the precision of FRET imaging varies vastly with imaging parameters. Therefore, we provide analytical and numerical tools for assay optimization. FLIM is a very robust technique with excellent photon-efficiencies but also intensity-based FRET imaging can reach very high precision by utilizing also information within acceptor fluorescence.

Single-molecule fluorescence resonance energy transfer (FRET) is a powerful technique based on dipole-dipole interaction between donor and acceptor fluorophores to observe inter- and intra-molecular dynamics in realtime with sensitivity to macro-molecular distances ([~] 2.5-10 nm). That said, some fluorophores have an inherent characteristic known as protein induced fluorescence enhancement (PIFE). PIFE is a photo-physical feature of dyes undergoing cis-trans transitions and occurs for protein-dye interactions closer than 3 nm. Here, the challenge is uncoupling the PIFE effect in the FRET data. Ignoring the PIFE effect in the analysis of the FRET data may lead to misinterpretation of the system under investigation. As a solution to this problem, we develop a computational framework based on Bayesian statistics to analyze the fluorescence lifetime signals of the donor and acceptor channels which allows us to uncouple the PIFE effects from the FRET. Our framework can extract any changes in the FRET efficiency simultaneously with any changes in the fluorescence lifetimes of the donor and acceptor due to the PIFE effect. In addition, our framework can provide other parameters, such as the donor and acceptor excitation rates, background photon rates, and detectors cross-talk ratios. Our framework extracts all these parameters by analyzing a single photon arrival time trace with only a few thousand photons.

Super-resolution light microscopy techniques facilitate the observation of nanometer-size biomolecules, which are 1-2 orders of magnitude smaller than the diffraction limit of light. Using super-resolution microscopy techniques, it is possible to observe fluorescence from two biomolecules in close proximity, however not necessarily in direct interaction. Using FRET-sensitized acceptor emission localization (FRETsael), we localize biomolecular interactions exhibiting FRET with nanometer accuracy, from two-color fluorescence lifetime imaging data. The concepts of FRETsael were tested first against simulations, in which the recovered localization accuracy is 20-30 nm for true-positive detections of FRET pairs. Further analyses of the simulation results report the conditions in which true-positive rates are maximal. We then show the capabilities of FRETsael on simulated samples of Actin-Vinculin and ER-ribosomes interactions, as well as on experimental samples of actin-myosin two-color confocal imaging. Conclusively, the FRETsael approach paves the way towards studying biomolecular interactions with improved spatial resolution from laser scanning confocal two-color fluorescence lifetime imaging. SignificanceFRET is used in fluorescence microscopy to report whether dye-labeled biomolecules of choice are close within distances of 10 nm or less, hence typical interaction distances. However, in many cases, using FRET imaging for the study of biomolecular interactions is difficult due to the high density of dye-labeled biomolecules and due to the existence of unbound dye-labeled biomolecules. In addition, the resolution of localizing molecules using light microscopy is diffraction limited. This work presents FRETsael, a new approach for localizing interacting biomolecules undergoing FRET, with improved resolution of 20-30 nm for confocal microscopy using search algorithms for local extrema in contribution to FRET using two-channel fluorescence intensity and lifetime data.

Understanding protein oligomerization in living cells is essential for elucidating cellular signaling and regulation, yet quantitative analysis remains challenging due to heterogeneous expression levels, dynamic interactions, and limited access to absolute protein concentrations. Here, we present a standardized, open-source framework for quantifying protein assemblies in living cells by integrating fluorescence lifetime and anisotropy imaging (heteroFRET and homoFRET) with molecular brightness-based concentration estimation and image analysis. Using natural variants of a vertebrate GPCR, the melanocortin-4 receptor (MC4R-A and MC4R-B2), as a model system, we demonstrate how to discriminate monomers, dimers, and higher-order oligomers, extract inter-fluorophore distance distributions, and determine association constants under physiologically relevant conditions in living cells. Standard fluorescent protein tags report on proximity and oligomerization via Homo- and HeteroFRET. Association constants are quantified using the variable protein expression in living cells and the spectroscopy readouts. By high-content imaging we overcome the biological noise and attain data qualities comparable to conventional biochemical in vitro assays. Intensity- and fluctuation-based segmentation further extends the accessible concentration range within individual cells, improving affinity analysis robustness. Our results establish quantitative image spectroscopy on living cells as quantitative tool for investigating protein-protein interactions under physiologically relevant conditions. All computational workflows are implemented in open-source software and are accompanied by detailed protocols and analysis scripts, enabling reproducible application and adaptation. Beyond GPCRs, this framework provides a practical and transferable methodology for quantitative studies on protein-protein interactions, mechanistic studies and drug discovery in complex cellular environments.

Electric charges play a fundamental role in shaping the structure, function, and interactions of biomolecules, yet precisely measuring these charges at the single-molecule level remains a significant technical challenge. Here, we introduce a novel experimental methodology that utilizes plasmonic nanocavities to quantify molecular electric charges in solution with high sensitivity. Our approach exploits an externally applied electric field to induce the spatial redistribution of charged molecules confined within a planar metallic nanocavity, while simultaneously leveraging nanocavity-induced fluorescence lifetime modulation as a highly sensitive readout. We demonstrate the feasibility of this method through proof-of-concept experiments, where we measure the fluorescence lifetimes of positively and negatively charged fluorescent dye molecules as a function of the applied electric field across the cavity. The experimental results are validated through a rigorous theoretical framework, incorporating statistical thermodynamics and electrodynamic modeling to accurately describe the observed data. The proposed method offers a calibration-free, experimentally simple, and rapid alternative to existing charge measurement techniques, opening new avenues for precise quantification of molecular electric charges down to the single-molecule level.

Quantitative fluorescence emission anisotropy microscopy reveals the organization of fluorescently labelled cellular components and allows for their characterization in terms of changes in either rotational diffusion or homo-Forsters energy transfer characteristics in living cells. These properties provide insights into molecular organization, such as orientation, confinement and oligomerization in situ. Here we elucidate how quantitative measurements of anisotropy using multiple microscope systems may be made, by bringing out the main parameters that influence the quantification of fluorescence emission anisotropy. We focus on a variety of parameters that contribute to errors associated with the measurement of emission anisotropy in a microscope. These include the requirement for adequate photon counts for the necessary discrimination of anisotropy values, the influence of extinction coefficients of the illumination source, the detector system, the role of numerical aperture and excitation wavelength. All these parameters also affect the ability to capture the dynamic range of emission anisotropy necessary for quantifying its reduction due to homo-FRET and other processes. Finally, we provide easily implementable tests to assess whether homo-FRET is a cause for the observed emission depolarization.

Forster Resonance Energy Transfer (FRET) is a powerful technique for the detection and characterization of biomolecular interactions and conformational changes with sub-nanometer spatial resolution and a temporal resolution down to the timescale of fluorescence. While the technique is widely adopted in structural biology and biophysics, the evolution of single-molecule FRET has led to experimental setups with sophisticated optical layouts, multi-laser excitation schemes and time-resolved detection electronics. We here present an accessible alternative towards single-molecule FRET based on Brick-MIC, a recently introduced 3D-printed micro-spectroscopy platform. The FRET-Brick uses continuous-wave excitation at 488 nm with a minimal set of opto-mechanical components and photomultiplier detectors (PMTs). With this we were able to significantly reduce the setup complexity retaining single-molecule sensitivity with dyes matching the sensitivity of PMTs. To maximize the photon output of Alexa488, ATTO488 (donors), Alexa555, ATTO542 and Cy3B (acceptors), we introduce ferrocene-derivatives as photostabilizers that increase both dye brightness and remove dark-states. We benchmark the performance of the FRET-Brick with fluorophore-labelled oligonucleotide reference structures also in comparison to accessible volume simulations, and by detecting conformational changes in bacterial substrate binding proteins. Our work demonstrates that qualitative and quantitative smFRET measurements are possible with the minimalistic and cost-effective FRET-Brick.

Since the advent of stochastic localization microscopy approaches in 2006, the number of studies employing this strategy to investigate the sub-diffraction limit features of fluorescently labeled structures in biology, biophysics and solid state samples has increased exponentially. Underpinning all these approaches is the notion that the position of single molecules can be determined to high precision, provided enough photons are collected. The determination of exactly how precisely, has been demanded to formulas that try to approximate the so-called Cramer Rao Lower Bound based on input parameters such as the number of photons collected from the molecules, or the size of the camera pixel. These estimates should however be matched to the experimental localization precision, which can be easily determined if instead of looking at single beads, we study the distance between a pair. We revisit here a few key works, observing how these theoretical determinations tend to routinely underestimate the experimental localization precision, of the order of a factor two. A software-independent metric to determine, based on each individual setup, the appropriate value to set on the localization error of individual emitters is provided.

Forster resonance energy transfer (FRET) between fluorescent proteins (FPs) is widely used in the design of genetically encoded fluorescent biosensors, which are powerful tools for monitoring the dynamics of biochemical activities in live cells. FRET ratio, defined as the ratio between acceptor and donor signals, is often used as a proxy for the actual FRET efficiency, which must be corrected for signal crosstalk using donor-only and acceptor-only samples. However, the FRET ratio is highly sensitive to imaging conditions, making direct comparisons across different experiments and over time challenging. Inspired by a method for multiplexed biosensor imaging using barcoded cells, we reasoned that calibration standards with fixed FRET efficiency can be introduced into a subset of cells for normalization of biosensor signals. Our theoretical analysis indicated that the FRET ratio of high-FRET species relative to non-FRET species slightly decreases at high excitation intensity, suggesting the need for calibration using both high and low FRET standards. To test these predictions, we created FRET donor-acceptor pairs locked in "FRET-ON" and "FRET-OFF" conformations and introduced them into a subset of barcoded cells. Our results confirmed the theoretical predictions and showed that the calibrated FRET ratio is independent of imaging settings. We also provided a strategy for calculating the FRET efficiency. Together, our study presents a simple strategy for calibrated and highly multiplexed imaging of FRET biosensors, facilitating reliable comparisons across experiments and supporting long-term imaging applications.

Biomolecular dynamics are often strikingly heterogeneous, with individual molecules sampling different states and kinetics--violating the "average molecule" assumption. Yet FRET analyses cannot resolve such variability or distinguish states differing mainly in kinetics, rather than FRET efficiency, as molecular configurations are projected onto 1D FRET signals. Here we introduce BNP-FRET-Bin, inferring state numbers and their kinetics directly from FRET data. In doing so, we eliminate user-specified parameters and expose molecule-to-molecule heterogeneity revealing new biologically relevant Holliday junction states with near identical FRET efficiencies.

Nine fluorescent proteins (FPs) simultaneous imaging has been demonstrated in a single acquisition using fluorescence lifetime imaging microscopy (FLIM) combined with pulsed interleaved excitation (PIE) for three laser lines. We also show how to unmix spectrally similar FPs in a pixel-by-pixel manner with an analytical non-fitting solution.

Single-molecule localization microscopy achieves nanometer-scale resolution but fails to count molecular targets when multiple targets are in close proximity. DNA-PAINT uses reversible binding of fluorescently labeled probes to image molecular targets, but existing time-series based counting methods require prior knowledge of binding kinetics, calibration, or extensive data post-processing, which limits applicability across heterogeneous biological samples. Here, we present mCOAST, a calibration-free method that extracts molecular counts and kinetic parameters directly from a single DNA-PAINT intensity trace using cumulants. Unlike existing approaches, mCOAST requires no adjustable parameters, data normalization, or denoising. We demonstrate accurate counting for diffraction-limited clusters with up to 48 targets at high imager concentrations, with precision that improves, rather than decreases, as concentration increases. Critically, mCOAST counts targets in individual clusters despite kinetic heterogeneity across samples or between experiments. This paves the way towards quantitative imaging and counting in uncalibrated biological systems, such as living cells.

We present a fluorescence fluctuation image correlation analysis method that can rapidly and simultaneously measure the diffusion coefficient, photoblinking rates, and fraction of diffusing particles of fluorescent molecules in cells. Unlike other image correlation techniques, we demonstrated that our method could be applied irrespective of a non-uniformly distributed, immobile blinking fluorophore population. This allows us to measure blinking and transport dynamics in complex cell morphologies, a benefit for a range of super-resolution fluorescence imaging approaches that rely on probe emission blinking. Furthermore, we showed that our technique could be applied without directly accounting for photobleaching. We successfully employed our technique on several simulations with realistic EMCCD noise and photobleaching models, as well as on Dronpa-C12 labeled beta-actin in living NIH/3T3 and HeLa cells. We found that the diffusion coefficients measured using our method were consistent with previous literature values. We further found that photoblinking rates measured in the live HeLa cells varied as expected with changing excitation power.

Annibale and Lohse have recently suggested a way1 in which the two-dimensional fluorescence intensity fluctuation (2D FIF) spectrometry2 may be further refined. Their main suggestion is to include a step in the analysis process where a case-by-case inspection of individual regions of interest of a membrane allows for selection of portions of the membrane which are "as homogenous as possible" and thereby exclude intensity spots potentially related to other sub-cellular structures. By incorporating that proposal into an objective and reproducible algorithm, here we show that 2D FIF has a built-in capability to automatically filter out such contributions, and that further removal of inhomogeneities does not alter the final results.

Time-correlated single photon counting (TCSPC) coupled with confocal microscopy is a versatile biophysical tool that enables real-time monitoring of biomolecular dynamics across many timescales. With TCSPC, Fluorescence correlation spectroscopy (FCS) and pulsed interleaved excitation-Forster resonance energy transfer (PIE-FRET) are collected simultaneously on diffusing molecules to extract diffusion characteristics and proximity information. This article is a guide to calibrating FCS and PIE-FRET measurements with several biological samples including liposomes, streptavidin-coated quantum dots, proteins, and nucleic acids for reliable determination of diffusion coefficients and FRET efficiency. The FRET efficiency results are also compared to surface-attached single molecules using fluorescence lifetime imaging microscopy (FLIM-FRET). Combining the methods is a powerful approach to revealing mechanistic details of biological processes and pathways.

Sub-ms 3D tracking of individual molecules in living cells is an important goal for microscopy since it will enable measurements at the scale of diffusion limited macromolecular interactions. Here, we present a 3D tracking principle based on the true excitation point spread function and cross-entropy minimization for position localization of moving fluorescent reporters that approaches the relevant regime. When tested on beads moved on a stage, we reached 67nm lateral and 109nm axial precision with a time resolution of 0.84 ms at a photon count rate of 60kHz, coming close to the theoretical and simulated predictions. A critical step in the implementation was a new method for microsecond 3D PSF positioning that combines 3D holographic beam shaping and electro-optical deflection. For the analysis of tracking data, a new point estimator for diffusion was derived and evaluated by a detailed simulation of the 3D tracking principle applied to a fictive reaction-diffusion process in an E. coli-like geometry. Finally, we successfully applied these methods to track the Trigger Factor protein in living bacterial cells. Overall our results show that it is possible to reach sub-millisecond live-cell single-molecule tracking, but that it is still hard to resolve state transitions based on diffusivity at this time scale.

Our goal is to learn kinetic rates from single molecule FRET (smFRET) data even if these exceed the data acquisition rate. To achieve this, we develop a variant of our recently proposed hidden Markov jump process (HMJP) with which we learn transition kinetics from parallel measurements in donor and acceptor channels. Our HMJP generalizes the hidden Markov model (HMM) paradigm in two critical ways: (1) it deals with physical smFRET systems as they switch between conformational states in continuous time; (2) it estimates the transition rates between conformational states directly without having recourse to transition probabilities or assuming slow dynamics (as is necessary of the HMM). Our continuous time treatment learns transition kinetics and photon emission rates for dynamical regimes inaccessible to the HMM which treats system kinetics in discrete time. We validate the robustness of our framework on simulated data and demonstrate its performance on experimental data from FRET labeled Holliday junctions.

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.

Light nanoscopy is attracting widespread interest for the visualization of fluorescent structures at the nanometer scale, especially in cellular biology. To achieve nanoscale resolution, one has to surpass the diffraction limit--a fundamental phenomenon determining the spot size of focused light. Recently, a variety of methods have overcome this limit, yet in practice they are often constrained by the requirement of special fluorophores, nontrivial data processing, or high price and complex implementation. For this reason, confocal fluorescence microscopy that yields relatively low resolution is still the dominant method in biomedical sciences. It was shown that image scanning microscopy (ISM) with an array detector instead of a point detector could improve the resolution of confocal microscopy. Here we review the principles of the confocal microscopy and present a simple method based on ISM with a different image reconstruction approach, which can be easily implemented in any camera-based laser-scanning set-up to experimentally obtain the theoretical resolution limit of the confocal microscopy. Our method, Single Pixel Reconstruction Imaging (SPiRI) enables high-resolution 3D imaging utilizing image formation only from a single pixel of each of the recorded frames. We achieve experimental axial resolution of 330 nm, which was not shown before by basic confocal or ISM-based systems. Contrary to the majority of techniques, SPiRI method exhibits a low lateral-to-axial FWHM aspect ratio, which means a considerable improvement in 3D fluorescence imaging of cellular structures. As a demonstration of SPiRI application in biomedical sciences, we present a 3D structure of bacterial chromosome with excellent precision.