An update on molecular counting in fluorescence microscopy

Bayesian Inference of Binding Kinetics from Fluorescence Time Series

The study of binding kinetics via the analysis of fluorescence time traces is often confounded by measurement noise and photophysics. Although photoblinking can be mitigated by using labels less likely to photoswitch, photobleaching generally cannot be eliminated. Current methods for measuring binding and unbinding rates are, therefore, limited by concurrent photobleaching events. Here, we propose a method to infer binding and unbinding rates alongside photobleaching rates using fluorescence intensity traces. Our approach is a two-stage process involving analyzing individual regions of interest (ROIs) with a hidden Markov model to infer the fluorescence intensity levels of each trace. We then use the inferred intensity level state trajectory from all of the ROIs to infer kinetic rates. Our method has several advantages, including the ability to analyze noisy traces, account for the presence of photobleaching events, and provide uncertainties associated with the inferred binding kinetics. We demonstrate the effectiveness and reliability of our method through simulations and data from DNA origami binding experiments.

Bayesian Inference of Binding Kinetics from Fluorescence Time Series

The study of binding kinetics via the analysis of fluorescence time traces is often confounded by measurement noise and photophysics. Although photoblinking can be mitigated by using labels less likely to photoswitch, photobleaching generally cannot be eliminated. Current methods for measuring binding and unbinding rates are therefore limited by concurrent photobleaching events. Here, we propose a method to infer binding and unbinding rates alongside photobleaching rates using fluorescence intensity traces. Our approach is a two-stage process involving analyzing individual regions of interest (ROIs) with a Hidden Markov Model to infer the fluorescence intensity levels of each trace. We then use the inferred intensity level state trajectory from all ROIs to infer kinetic rates. Our method has several advantages, including the ability to analyze noisy traces, account for the presence of photobleaching events, and provide uncertainties associated with the inferred binding kinetics. We demonstrate the effectiveness and reliability of our method through simulations and data from DNA origami binding experiments.

MultiMatch: geometry-informed colocalization in multi-color super-resolution microscopy

With recent advances in multi-color super-resolution light microscopy, it is possible to simultaneously visualize multiple subunits within biological structures at nanometer resolution. To optimally evaluate and interpret spatial proximity of stainings on such an image, colocalization analysis tools have to be able to integrate prior knowledge on the local geometry of the recorded biological complex. We present MultiMatch to analyze the abundance and location of chain-like particle arrangements in multi-color microscopy based on multi-marginal optimal unbalanced transport methodology. Our object-based colocalization model statistically addresses the effect of incomplete labeling efficiencies enabling inference on existent, but not fully observable particle chains. We showcase that MultiMatch is able to consistently recover existing chain structures in three-color STED images of DNA origami nanorulers and outperforms geometry-uninformed triplet colocalization methods in this task. MultiMatch generalizes to an arbitrary number of color channels and is provided as a user-friendly Python package comprising colocalization visualizations.

ProDOL: a general method to determine the degree of labeling for staining optimization and molecular counting

Determining the label to target ratio, also known as the degree of labeling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labeling is beneficial for fluorescence microscopy in general. Yet robust, versatile and easy-to-use tools for measuring cell-specific labeling efficiencies are not available. Here we present a DOL determination technique named protein-tag DOL (ProDOL), which enables fast quantification and optimization of protein-tag labeling. With ProDOL various factors affecting labeling efficiency, including substrate type, incubation time and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how human immunodeficiency virus-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adapter protein SLP-76 in signaling microclusters. ProDOL proved to be a versatile and robust tool for labeling calibration, enabling determination of labeling efficiencies, optimization of strategies and quantification of protein stoichiometry.

CaV1.3 channel clusters characterized by live-cell and isolated plasma membrane nanoscopy

A key player of excitable cells in the heart and brain is the L-type calcium channel CaV1.3. In the heart, it is required for voltage-dependent Ca2+-signaling, i.e., for controlling and modulating atrial cardiomyocyte excitation-contraction coupling. The clustering of CaV1.3 in functionally relevant channel multimers has not been addressed due to a lack of stoichiometric labeling combined with high-resolution imaging. Here, we developed a HaloTag-labeling strategy to visualize and quantify CaV1.3 clusters using STED nanoscopy to address the questions of cluster size and intra-cluster channel density. Channel clusters were identified in the plasma membrane of transfected live HEK293 cells as well as in giant plasma membrane vesicles derived from these cells that were spread on modified glass support to obtain supported plasma membrane bilayers (SPMBs). A small fraction of the channel clusters was colocalized with early and recycling endosomes at the membranes. STED nanoscopy in conjunction with live-cell and SPMB imaging enabled us to quantify CaV1.3 cluster sizes and their molecular density revealing significantly lower channel densities than expected for dense channel packing. CaV1.3 channel cluster size and molecular density were increased in SPMBs after treatment of the cells with the sympathomimetic compound isoprenaline, suggesting a regulated channel cluster condensation mechanism.

Quantitative determination of fluorescence labeling implemented in cell cultures

BACKGROUND

Labeling efficiency is a crucial parameter in fluorescence applications, especially when studying biomolecular interactions. Current approaches for estimating the yield of fluorescent labeling have critical drawbacks that usually lead them to be inaccurate or not quantitative.

RESULTS

We present a method to quantify fluorescent-labeling efficiency that addresses the critical issues marring existing approaches. The method operates in the same conditions of the target experiments by exploiting a ratiometric evaluation with two fluorophores used in sequential reactions. We show the ability of the protocol to extract reliable quantification for different fluorescent probes, reagents concentrations, and reaction timing and to optimize labeling performance. As paradigm, we consider the labeling of the membrane-receptor TrkA through 4'-phosphopantetheinyl transferase Sfp in living cells, visualizing the results by TIRF microscopy. This investigation allows us to find conditions for demanding single and multi-color single-molecule studies requiring high degrees of labeling.

CONCLUSIONS

The developed method allows the quantitative determination and the optimization of staining efficiency in any labeling strategy based on stable reactions.

Quasi-equilibrium state based quantification of biological macromolecules in single-molecule localization microscopy

The stoichiometry of molecular components within supramolecular biological complexes is often an important property to understand their biological functioning, particularly within their native environment. While there are well established methods to determine stoichiometryin vitro, it is presently challenging to precisely quantify this propertyin vivo,especially with single molecule resolution that is needed for the characterization stoichiometry heterogeneity. Previous work has shown that optical microscopy can provide some information to this end, but it can be challenging to obtain highly precise measurements at higher densities of fluorophores. Here we provide a simple approach using already established procedures in single-molecule localization microscopy (SMLM) to enable precise quantification of stoichiometry within individual complexes regardless of the density of fluorophores. We show that by focusing on the number of fluorophore detections accumulated during the quasi equilibrium-state of this process, this method yields a 50-fold improvement in precision over values obtained from images with higher densities of active fluorophores. Further, we show that our method yields more correct estimates of stoichiometry with nuclear pore complexes and is easily adaptable to quantify the DNA content with nanodomains of chromatin within individual chromosomes inside cells. Thus, we envision that this straightforward method may become a common approach by which SMLM can be routinely employed for the accurate quantification of subunit stoichiometry within individual complexes within cells.

Measuring antigen expression of cancer cell lines and circulating tumour cells

When evaluating EpCAM-based enrichment technologies for circulating tumour cells (CTCs), the cell lines used should closely resemble real CTCs, meaning the EpCAM expression of CTCs needs to be known, but also the EpCAM expression of cell lines at different institutions and times is important. As the number of CTCs in the blood is low, we enriched CTCs through the depletion of leukocytes from diagnostic leukapheresis products of 13 prostate cancer patients and measured EpCAM expression using quantitative flow cytometry. Antigen expression was compared between multiple institutions by measuring cultures from each institution. Capture efficiency was also measured for one of the used cell lines. Results show CTCs derived from castration-sensitive prostate cancer patients have varying but relatively low EpCAM expression, with median expression per patient ranging from 35 to 89,534 (mean 24,993) molecules per cell. A large variation in the antigen expression of identical cell lines cultured at different institutions was found, resulting in recoveries when using the CellSearch system ranging from 12 up to 83% for the same cell line. We conclude that large differences in capture efficiency can occur while using the same cell line. To closely resemble real CTCs from castration-sensitive prostate cancer patients, a cell line with a relatively low EpCAM expression should be used, and its expression should be monitored frequently.

Determination of association equilibrium constant from single molecule fluorescence localization microscopy

Single molecule fluorescence localization microscopy provides molecular localization with a precision in the tens of nanometer range in the plane perpendicular to the light propagation. This opens the possibility to count molecules and correlate their locations, starting from a map of the actual positions in a single molecule super resolution image. Considering molecular pair correlation as an indication of interaction, and a way to discern them from free molecules, we describe a method to calculate thermodynamic equilibrium constants. In this work, we use as a test system two complementary homo-oligonucleotides, one strand marked with Cyanine 3.5 and the other with Alexa Fluor 647. Hybridization is controlled by the amount of each strand, temperature, and the ionic force, and measured in steady state emission. The same samples are examined in Stochastic Optical Reconstruction Microscopy (STORM) experiments with split-field simultaneous two-colour detection. The effect of multiblinking, labelling-detection efficiency, and determination of the critical distance for association are discussed. We consistently determine values in STORM coincident with those of the bulk experiment.

Photobleaching step analysis for robust determination of protein complex stoichiometries

The counting of discrete photobleaching steps in fluorescence microscopy is ideally suited to study protein complex stoichiometry in situ. The counting range of photobleaching step analysis has been significantly improved with more-sophisticated algorithms for step detection, albeit at an increasing computational cost and with the necessity for high-quality data. Here, we address concerns regarding robustness, automation, and experimental validation, optimizing both data acquisition and analysis. To make full use of the potential of photobleaching step analysis, we evaluate various labeling strategies with respect to their molecular brightness, photostability, and photoblinking. The developed analysis algorithm focuses on automation and computational efficiency. Moreover, we validate the developed methods with experimental data acquired on DNA origami labeled with defined fluorophore numbers, demonstrating counting of up to 35 fluorophores. Finally, we show the power of the combination of optimized trace acquisition and automated data analysis by counting labeled nucleoporin 107 in nuclear pore complexes of intact U2OS cells. The successful in situ application promotes this framework as a new resource enabling cell biologists to robustly determine the stoichiometries of molecular assemblies at the single-molecule level in an automated manner.