A guide to accurate fluorescence microscopy colocalization measurements

Biomolecular interactions are fundamental to the vast majority of cellular processes, and identification of the major interacting components is usually the first step toward an understanding of the mechanisms that govern various cell functions. Thus, statistical image analyses that can be performed on fluorescence microscopy images of fixed or live cells have been routinely applied for biophysical and cell biological studies. These approaches measure the fraction of interacting particles by analyzing dual color fluorescence images for colocalized pixels. Colocalization algorithms have proven to be effective, although the dynamic range and accuracy of these measurements has never been well established. Spatial image cross-correlation spectroscopy (ICCS), which cross-correlates spatial intensity fluctuations recorded in images from two detection channels simultaneously, has also recently been shown to be an effective measure of colocalization as well. Through simulations, imaging of fluorescent antibodies adsorbed on glass and cell measurements, we show that ICCS performs much better than standard colocalization algorithms at moderate to high densities of particles, which are often encountered in cellular systems. Furthermore, it was found that the density ratio between the two labeled species of interest plays a major role in the accuracy of the colocalization analysis. By applying a direct and systematic comparison between the standard, fluorescence microscopy colocalization algorithm and spatial ICCS, we show regimes where each approach is applicable, and more importantly, where they fail to yield accurate results.     

Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells

We introduce a new extension of image correlation spectroscopy (ICS) and image cross-correlation spectroscopy (ICCS) that relies on complete analysis of both the temporal and spatial correlation lags for intensity fluctuations from a laser-scanning microscopy image series. This new approach allows measurement of both diffusion coefficients and velocity vectors (magnitude and direction) for fluorescently labeled membrane proteins in living cells through monitoring of the time evolution of the full space-time correlation function. By using filtering in Fourier space to remove frequencies associated with immobile components, we are able to measure the protein transport even in the presence of a large fraction (>90%) of immobile species. We present the background theory, computer simulations, and analysis of measurements on fluorescent microspheres to demonstrate proof of principle, capabilities, and limitations of the method. We demonstrate mapping of flow vectors for mixed samples containing fluorescent microspheres with different emission wavelengths using space time image cross-correlation. We also present results from two-photon laser-scanning microscopy studies of alpha-actinin/enhanced green fluorescent protein fusion constructs at the basal membrane of living CHO cells. Using space-time image correlation spectroscopy (STICS), we are able to measure protein fluxes with magnitudes of mum/min from retracting lamellar regions and protrusions for adherent cells. We also demonstrate the measurement of correlated directed flows (magnitudes of mum/min) and diffusion of interacting alpha5 integrin/enhanced cyan fluorescent protein and alpha-actinin/enhanced yellow fluorescent protein within living CHO cells. The STICS method permits us to generate complete transport maps of proteins within subregions of the basal membrane even if the protein concentration is too high to perform single particle tracking measurements.     

Advances in Image Correlation Spectroscopy: Measuring Number Densities,Aggregation States,and Dynamics of Fluorescently labeled Macromolecules in Cells

A brief historical outline of fluorescence fluctuation correlation techniques is presented, followed by an in-depth review of the theory and development of image correlation techniques, including: image correlation spectroscopy (ICS), temporal ICS (TICS), image cross-correlation spectroscopy (ICCS), spatiotemporal ICS (STICS), k-space ICS (kICS), raster ICS (RICS), and particle ICS (PICS). These techniques can be applied to analyze image series acquired on commercially available laser scanning or total internal reflection fluorescence microscopes, and are used to determine the number density, aggregation state, diffusion coefficient, velocity, and interaction fraction of fluorescently labeled molecules or particles. A comprehensive review of the application of ICS techniques to a number of systems, including cell adhesion, membrane receptor aggregation and dynamics, virus particle fusion, and fluorophore photophysics, is presented.     

Accuracy and dynamic range of spatial image correlation and cross-correlation spectroscopy

We present a comprehensive study of the accuracy and dynamic range of spatial image correlation spectroscopy (ICS) and image cross-correlation spectroscopy (ICCS). We use simulations to model laser scanning microscopy imaging of static subdiffraction limit fluorescent proteins or protein clusters in a cell membrane. The simulation programs allow us to control the spatial imaging sampling variables and the particle population densities and interactions and introduce and vary background and counting noise typical of what is encountered in digital optical microscopy. We systematically calculate how the accuracy of both image correlation methods depends on practical experimental collection parameters and characteristics of the sample. The results of this study provide a guide to appropriately plan spatial image correlation measurements on proteins in biological membranes in real cells. The data presented map regimes where the spatial ICS and ICCS provide accurate results as well as clearly showing the conditions where they systematically deviate from acceptable accuracy. Finally, we compare the simulated data with standard confocal microscopy using live CHO cells expressing the epidermal growth factor receptor fused with green fluorescent protein (GFP/EGFR) to obtain typical values for the experimental variables that were investigated in our study. We used our simulation results to estimate a relative precision of 20% for the ICS measured receptor density of 64 microm(-2) within a 121 x 98 pixel subregion of a single cell.     

Imaging Barriers to Diffusion by Pair Correlation Functions

Molecular diffusion and transport are fundamental processes in physical, chemical, biochemical, and biological systems. However, current approaches to measure molecular transport in cells and tissues based on perturbation methods such as fluorescence recovery after photobleaching are invasive, fluctuation correlation methods are local, and single-particle tracking requires the observation of isolated particles for relatively long periods of time. We propose to detect molecular transport by measuring the time cross-correlation of fluctuations at a pair of locations in the sample. When the points are farther apart than two times the size of the point spread function, the maximum of the correlation is proportional to the average time a molecule takes to move from a specific location to another. We demonstrate the method by simulations, using beads in solution, and by measuring the diffusion of molecules in cellular membranes. The spatial pair cross-correlation method detects barriers to diffusion and heterogeneity of diffusion because the time of the correlation maximum is delayed in the presence of diffusion barriers. This noninvasive, sensitive technique follows the same molecule over a large area, thereby producing a map of molecular flow. It does not require isolated molecules, and thus many molecules can be labeled at the same time and within the point spread function.     

Tracking Image Correlation: Combining Single-Particle Tracking and Image Correlation

The interactions and coordination of biomolecules are crucial for most cellular functions. The observation of protein interactions in live cells may provide a better understanding of the underlying mechanisms. After fluorescent labeling of the interacting partners and live-cell microscopy, the colocalization is generally analyzed by quantitative global methods. Recent studies have addressed questions regarding the individual colocalization of moving biomolecules, usually by using single-particle tracking (SPT) and comparing the fluorescent intensities in both color channels. Here, we introduce a new method that combines SPT and correlation methods to obtain a dynamical 3D colocalization analysis along single trajectories of dual-colored particles. After 3D tracking, the colocalization is computed at each particle’s position via the local 3D image cross correlation of the two detection channels. For every particle analyzed, the output consists of the 3D trajectory, the time-resolved 3D colocalization information, and the fluorescence intensity in both channels. In addition, the cross-correlation analysis shows the 3D relative movement of the two fluorescent labels with an accuracy of 30 nm. We apply this method to the tracking of viral fusion events in live cells and demonstrate its capacity to obtain the time-resolved colocalization status of single particles in dense and noisy environments.     

Fluorescence correlation spectroscopy for ultrasensitive DNA analysis in continuous flow capillary electrophoresis

Continuous flow capillary electrophoresis (CFCE) is non-separations based analytical technique based on the free solution electrophoretic mobility of biological molecules such as DNA, RNA, peptides, and proteins. The electrophoretic mobilities and translational diffusion constants of the analyte molecules are determined using single molecule detection methods, including fluorescence correlation spectroscopy (FCS). CFCE is used to resolve multiple components in a mixture of analytes, measure electrophoretic mobility shifts due to binding interactions, and study the hydrodynamic and electrostatic properties of biological molecules in solution. Often this information is obtained with greater speed and sensitivity than conventational separations-based capillary-zone electrophoresis. This paper will focus on the application of two-beam fluorescence cross-correlation spectroscopy as a versatile detection method for CFCE and explore several applications to the study of the solution properties of single-stranded DNA.     

Characterization of brightness and stoichiometry of bright particles by flow-fluorescence fluctuation spectroscopy

Characterization of bright particles at low concentrations by fluorescence fluctuation spectroscopy (FFS) is challenging, because the event rate of particle detection is low and fluorescence background contributes significantly to the measured signal. It is straightforward to increase the event rate by flow, but the high background continues to be problematic for fluorescence correlation spectroscopy. Here, we characterize the use of photon-counting histogram analysis in the presence of flow. We demonstrate that a photon-counting histogram efficiently separates the particle signal from the background and faithfully determines the brightness and concentration of particles independent of flow speed, as long as undersampling is avoided. Brightness provides a measure of the number of fluorescently labeled proteins within a complex and has been used to determine stoichiometry of protein complexes in vivo and in vitro. We apply flow-FFS to determine the stoichiometry of the group specific antigen protein within viral-like particles of the human immunodeficiency virus type-1 from the brightness. Our results demonstrate that flow-FFS is a sensitive method for the characterization of complex macromolecular particles at low concentrations.     

A New Methodology of Spatial Cross-Correlation Analysis

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.     

Quantification of Local Morphodynamics and Local GTPase Activity by Edge Evolution Tracking

Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6–8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.     

Fluorescence resonance energy transfer-based stoichiometry in living cells

Imaging of fluorescence resonance energy transfer (FRET) between fluorescently labeled molecules can measure the timing and location of intermolecular interactions inside living cells. Present microscopic methods measure FRET in arbitrary units, and cannot discriminate FRET efficiency and the fractions of donor and acceptor in complex. Here we describe a stoichiometric method that uses three microscopic fluorescence images to measure FRET efficiency, the relative concentrations of donor and acceptor, and the fractions of donor and acceptor in complex in living cells. FRET stoichiometry derives from the concept that specific donor-acceptor complexes will give rise to a characteristic FRET efficiency, which, if measured, can allow stoichiometric discrimination of interacting components. A first equation determines FRET efficiency and the fraction of acceptor molecules in complex with donor. A second equation determines the fraction of donor molecules in complex by estimating the donor fluorescence lost due to energy transfer. This eliminates the need for acceptor photobleaching to determine total donor concentrations and allows for repeated measurements from the same cell. A third equation obtains the ratio of total acceptor to total donor molecules. The theory and method were confirmed by microscopic measurements of fluorescence from cyan fluorescent protein (CFP), citrine, and linked CFP-Citrine fusion protein, in solutions and inside cells. Together, the methods derived from these equations allow sensitive, rapid, and repeatable detection of donor-, acceptor-, and donor-acceptor complex stoichiometry at each pixel in an image. By accurately imaging molecular interactions, FRET stoichiometry opens new areas for quantitative study of intracellular molecular networks.     

Quantitative Determination of Spatial Protein-Protein Correlations in Fluorescence Confocal Microscopy

To quantify spatial protein-protein proximity (colocalization) in paired microscopic images of two sets of proteins labeled by distinct fluorophores, we showed that the cross-correlation and the autocorrelation functions of image intensity consisted of fast and slowly decaying components. The fast component resulted from clusters of proteins specifically labeled, and the slow component resulted from image heterogeneity and a broadly-distributed background. To better evaluate spatial proximity between the two specifically labeled proteins, we extracted the fast-decaying component by fitting the sharp peak in correlation functions to a Gaussian function, which was then used to obtain protein-protein proximity index and the Pearson's correlation coefficient. We also employed the median-filter method as a universal approach for background reduction to minimize nonspecific fluorescence. We illustrated our method by analyzing computer-simulated images and biological images.     

Experimental evaluation of support vector machine-based and correlation-based approaches to automatic particle selection

The goal of this study is to evaluate the performance of software for automated particle-boxing, and in particular the performance of a new tool (TextonSVM) that recognizes the characteristic texture of particles of interest. As part of a high-throughput protocol, we use human editing that is based solely on class-average images to create final data sets that are enriched in what the investigator considers to be true-positive particles. The Fourier shell correlation (FSC) function is then used to characterize the homogeneity of different single-particle data sets that are derived from the same micrographs by two or more alternative methods. We find that the homogeneity is generally quite similar for class-edited data sets obtained by the texture-based method and by SIGNATURE, a cross-correlation-based method. The precision-recall characteristics of the texture-based method are, on the other hand, significantly better than those of the cross-correlation based method; that is to say, the texture-based approach produces a smaller fraction of false positives in the initial set of candidate particles. The computational efficiency of the two approaches is generally within a factor of two of one another. In situations when it is helpful to use a larger number of templates (exemplars), however, TextonSVM scales in a much more efficient way than do boxing programs that are based on localized cross-correlation.     

Model-based particle picking for cryo-electron microscopy

We describe an algorithm for finding particle images in cryo-EM micrographs. The algorithm starts from a crude 3D map of the target particle, computed from a relatively small number of manually picked images, and then projects the map in many different directions to give synthetic 2D templates. The templates are clustered and averaged and then cross-correlated with the micrographs. A probabilistic model of the imaging process then scores cross-correlation peaks to produce the final picks. We give quantitative results on two quite different target particles: keyhole limpet hemocyanin and p97 AAA ATPase. On these particles our automatic particle picker shows human performance level, as measured by the Fourier shell correlations of 3D reconstructions.     

Three-chromophore FRET microscopy to analyze multiprotein interactions in living cells

Nearly every major process in a cell is carried out by assemblies of multiple dynamically interacting protein molecules. To study multi-protein interactions within such molecular machineries, we have developed a fluorescence microscopy method called three-chromophore fluorescence resonance energy transfer (3-FRET). This method allows analysis of three mutually dependent energy transfer processes between the fluorescent labels, such as cyan, yellow and monomeric red fluorescent proteins. Here, we describe both theoretical and experimental approaches that discriminate the parallel versus the sequential energy transfer processes in the 3-FRET system. These approaches were established in vitro and in cultured mammalian cells, using chimeric proteins consisting of two or three fluorescent proteins linked together. The 3-FRET microscopy was further applied to the analysis of three-protein interactions in the constitutive and activation-dependent complexes in single endosomal compartments. These data highlight the potential of 3-FRET microscopy in studies of spatial and temporal regulation of signaling processes in living cells.     

Focus on composition and interaction potential of single-pass transmembrane domains

Transmembrane domains (TMD) connect the inner with the outer world of a living cell. Single TMD containing (bitopic) receptors are of particular interest, because their oligomerization seems to be a common activation mechanism in cell signaling. We analyzed the composition of TMDs in bitopic proteins within the proteomes of 12 model organisms. The average number of strongly polar and charged residues decreases during evolution, while the occurrence of a dimerization motif, GxxxG, remains unchanged. This may reflect the avoidance of unspecific binding within a growing receptor interaction network. In addition, we propose a new experimental approach for studying helix-helix interactions in giant plasma membrane vesicles using scanning fluorescence cross-correlation spectroscopy. Measuring eGFP/mRFP tagged versions of cytokine receptors confirms the homotypic interactions of the erythropoietin receptor in contrast to the Interleukin-4 receptor chains. As a proof of principle, by swapping the TMDs, the interaction potential of erythropoietin receptor was partially transferred to Interleukin-4 receptor α and vice versa. Non-interacting receptors can therefore serve as host molecules for TMDs whose oligomerization capability must be assessed. Computational analysis of the free energy gain resulting from TMD dimer formation strongly corroborates the experimental findings, potentially allowing in silico pre-screening of interacting pairs.     

Studies of distribution,location and dynamic properties of EGFR on the cell surface measured by image correlation spectroscopy

In this work, we have studied the distribution and dynamic properties of Epidermal Growth Factor (EGF) receptors in the plasma membrane of fixed and live cells as well as the extent of co-localization of this transmembrane protein with proteins specific for three-membrane microdomains: membrane rafts, caveolae and clathrin-coated pits. This was achieved using a family of image-processing tools called image correlation spectroscopy (ICS), image cross-correlation spectroscopy (ICCS) and dynamic image correlation spectroscopy (DICS). Our results indicate that EGFR is diffusely distributed on the cell surface at 37°C and aggregates as the temperature is lowered to 4°C. This aggregation takes place within 15 min and is reversible. Changes in temperature also affect the diffusion of EGFR by two orders of magnitude. The dynamic properties of EGFR are similar to the dynamic properties of a GPI-anchored protein known to be present in membrane rafts, which motivated us to explore the extent of co-localization of EGFR with this membrane raft protein using ICCS. Our results indicate that more than half of the EGFR population is present in membrane rafts and smaller percentages are present in caveolae and clathrin-coated pits.