Detecting Protein Complexes in Living Cells from Laser Scanning Confocal Image Sequences by the Cross Correlation Raster Image Spectroscopy Method

We describe a general method for detecting molecular complexes based on the analysis of single molecule fluorescence fluctuations from laser scanning confocal images. The method detects and quantifies complexes of two different fluorescent proteins noninvasively in living cells. Because in a raster scanned image successive pixels are measured at different times, the spatial correlation of the image contains information about dynamic processes occurring over a large time range, from the microseconds to seconds. The correlation of intensity fluctuations measured simultaneously in two channels detects protein complexes that carry two molecules of different colors. This information is obtained from the entire image. A map of the spatial distribution of protein complexes in the cell and their diffusion and/or binding properties can be constructed. Using this cross correlation raster image spectroscopy method, specific locations in the cell can be visualized where dynamics of binding and unbinding of fluorescent protein complexes occur. This fluctuation imaging method can be applied to commercial laser scanning microscopes thereby making it accessible to a large community of scientists.     

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.     

Measurement of monomer-oligomer distributions via fluorescence moment image analysis

We present higher-order moment analysis of fluorescence intensity fluctuations from individual laser scanning microscopy images applied to study monomer-oligomer distributions. We demonstrate that the number densities and brightness ratios of a mixed population of monomers and oligomers can be determined by analyzing higher-order moments of the fluorescence intensity fluctuations from individual images for specific ranges of densities and particle brightness ratios. Computer simulations and experiments with fluorescent microspheres and cells were performed to illustrate the detection limits and accuracy of this statistical approach. The simulation results show that the concentration of the dimer or oligomer population should be less than or equal to the monomeric concentration for the method to provide accurate results, and that the upper density detection limit of the population of monomers is one order-of-magnitude higher than the concentration of the oligomers. We implemented this technique to resolve two populations of fluorescent microspheres with different brightness ratios and we also applied the moment-analysis method to examine the distribution of aggregation states of PDGF-beta receptors in human fibroblast cells. The method was able to resolve a tetrameric population of the PDGF-beta receptors relative to the background distribution of nonspecifically bound fluorophore.     

On the analysis of high order moments of fluorescence fluctuations.

A simple, straightforward analysis to characterize the distribution of aggregate sizes in a reversible aggregation system at equilibrium is presented. The method, an extension of fluorescence correlation spectroscopy (FCS), is based on measurements of higher order moments of spontaneous fluctuations of fluorescence intensity emitted from a defined open region of the sample. These fluctuations indicate fluctuations of the numbers of the fluorescent molecules in the observation region. Shot noise resulting from the random character of fluorescence emission and from the photoelectric detection system is modeled as a Poisson distribution and is subtracted from the measured photon count fluctuation moments to yield the desired fluorescence fluctuation moments. This analysis can also be used to estimate the fraction of immobile fluorophores in FCS measurements.     

Imaging fluorescence correlation spectroscopy: nonuniform IgE distributions on planar membranes.

Fluorescence correlation spectroscopy is useful for detecting and characterizing molecular clusters that are smaller than or approximately equal to optical resolution in size. Here, we report the development of an approach in which the pixel-to-pixel fluorescence fluctuations from a single fluorescence image are spatially autocorrelated. In these measurements, tetramethylrhodamine-labeled, anti-trinitrophenyl IgE antibodies were specifically bound to substrate-supported planar membranes composed of trinitrophenyl-aminocaproyldipalmitoylphosphatidylethanolamine and dipalmitoylphosphatidylcholine. The antibody-coated membranes were illuminated with the evanescent field from a totally internally reflected laser beam, and the fluorescence arising from the IgE-coated membranes was recorded with a cooled CCD camera. The image was corrected for the elliptical Gaussian shape of the evanescent illumination after background subtraction. The spatial autocorrelation functions of the resulting images generated two useful parameters: the extrapolated initial values, which were related to the average cluster intensity and density; and the correlation distances, which were related to the average cluster size. These parameters varied with the IgE density, and unlabeled polyclonal anti-IgE enhanced the nonuniform IgE distributions. The autocorrelation functions calculated from images of planar membranes containing fluorescently labeled lipids rather than bound, labeled IgE demonstrated that the spatial nonuniformities were prominent only in the presence of IgE. Fluorescent beads were used to demonstrate the principles and the methods.     

Application of imaging tools to plant cell culture: Relationship between plant cell aggregation and flavonoid production

Summary Image analysis tools were developed to measure biomass concentration, aggregate size and distribution, and pigmentation from anthocyanin-producing cell suspension cultures of ohelo (Vaccinium pahalae). The ex situ imaging system could image cell aggregates from 30 μm to 2 mm in diameter. The image analysis algorithm was based on extracted geometric features and morphological methods for biomass volume estimates, and hue, saturation, and intensity color characteristics for pigmentation estimates. Detailed information available from sampled cell culture images was validated by comparison to standard destructive manual measurements. Image analysis measurements revealed that pigment accumulation was negatively correlated with aggregate size. Although a substantial proportion of small aggregates remained colorless, the highly-pigmented small aggregates, 18 to 238 μm in breadth, contributed over 70% of the culture anthocyanin production (mg L⁻¹), despite their minor contribution to the overall biomass. The relative frequency of pigmented aggregates was higher in large-size aggregate classes; however, the pigmented sectors were mostly confined to only the periphery of the aggregates. As a result, large aggregate classes had only a minor contribution to overall culture anthocyanin yield.     

Fast and flexible processing of large FRET image stacks using the FRET-IBRA toolkit

Ratiometric time-lapse FRET analysis requires a robust and accurate processing pipeline to eliminate bias in intensity measurements on fluorescent images before further quantitative analysis can be conducted. This level of robustness can only be achieved by supplementing automated tools with built-in flexibility for manual ad-hoc adjustments. FRET-IBRA is a modular and fully parallelized configuration file-based tool written in Python. It simplifies the FRET processing pipeline to achieve accurate, registered, and unified ratio image stacks. The flexibility of this tool to handle discontinuous image frame sequences with tailored configuration parameters further streamlines the processing of outliers and time-varying effects in the original microscopy images. FRET-IBRA offers cluster-based channel background subtraction, photobleaching correction, and ratio image construction in an all-in-one solution without the need for multiple applications, image format conversions, and/or plug-ins. The package accepts a variety of input formats and outputs TIFF image stacks along with performance measures to detect both the quality and failure of the background subtraction algorithm on a per frame basis. Furthermore, FRET-IBRA outputs images with superior signal-to-noise ratio and accuracy in comparison to existing background subtraction solutions, whilst maintaining a fast runtime. We have used the FRET-IBRA package extensively to quantify the spatial distribution of calcium ions during pollen tube growth under mechanical constraints. Benchmarks against existing tools clearly demonstrate the need for FRET-IBRA in extracting reliable insights from FRET microscopy images of dynamic physiological processes at high spatial and temporal resolution. The source code for Linux and Mac operating systems is released under the BSD license and, along with installation instructions, test images, example configuration files, and a step-by-step tutorial, is freely available at github.com/gmunglani/fret-ibra.     

Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images

Background

Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This technique, however, has a number of drawbacks such as the limited number of available fluorescent channels in microscopes, overlapping excitation and emission spectra of the stains, and phototoxicity.

Methodology

We here present and validate a method to automatically detect cell population outlines directly from bright field images. By imaging samples with several focus levels forming a bright field -stack, and by measuring the intensity variations of this stack over the -dimension, we construct a new two dimensional projection image of increased contrast. With additional information for locations of each cell, such as stained nuclei, this bright field projection image can be used instead of whole cell fluorescence to locate borders of individual cells, separating touching cells, and enabling single cell analysis. Using the popular CellProfiler freeware cell image analysis software mainly targeted for fluorescence microscopy, we validate our method by automatically segmenting low contrast and rather complex shaped murine macrophage cells.

Significance

The proposed approach frees up a fluorescence channel, which can be used for subcellular studies. It also facilitates cell shape measurement in experiments where whole cell fluorescent staining is either not available, or is dependent on a particular experimental condition. We show that whole cell area detection results using our projected bright field images match closely to the standard approach where cell areas are localized using fluorescence, and conclude that the high contrast bright field projection image can directly replace one fluorescent channel in whole cell quantification. Matlab code for calculating the projections can be downloaded from the supplementary site: http://sites.google.com/site/brightfieldorstaining     

The nuclear membrane determines the timing of DNA replication in Xenopus egg extracts

We have exploited a property of chicken erythrocyte nuclei to analyze the regulation of DNA replication in a cell-free system from Xenopus eggs. Many individual demembranated nuclei added to the extract often became enclosed within a common nuclear membrane. Nuclei within such a "multinuclear aggregate" lacked individual membranes but shared the perimeter membrane of the aggregate. Individual nuclei that were excluded from the aggregates initiated DNA synthesis at different times over a 10-12-h period, as judged by incorporation of biotinylated dUTP into discrete replication foci at early times, followed by uniformly intense incorporation at later times. Replication forks were clustered in spots, rings, and horseshoe-shaped structures similar to those described in cultured cells. In contrast to the asynchronous replication seen between individual nuclei, replication within multinuclear aggregates was synchronous. There was a uniform distribution and similar fluorescent intensity of the replication foci throughout all the nuclei enclosed within the same membrane. However, different multinuclear aggregates replicated out of synchrony with each other indicating that each membrane-bound aggregate acts as an individual unit of replication. These data indicate that the nuclear membrane defines the unit of DNA replication and determines the timing of DNA synthesis in egg extract resulting in highly coordinated triggering of DNA replication on the DNA it encloses.     

Cellometer image cytometry as a complementary tool to flow cytometry for verifying gated cell populations

Traditionally, many cell-based assays that analyze cell populations and functionalities have been performed using flow cytometry. However, flow cytometers remain relatively expensive and require highly trained operators for routine maintenance and data analysis. Recently, an image cytometry system has been developed by Nexcelom Bioscience (Lawrence, MA, USA) for automated cell concentration and viability measurement using bright-field and fluorescent imaging methods. Image cytometry is analogous to flow cytometry in that gating operations can be performed on the cell population based on size and fluorescent intensity. In addition, the image cytometer is capable of capturing bright-field and fluorescent images, allowing for the measurement of cellular size and fluorescence intensity data. In this study, we labeled a population of cells with an enzymatic vitality stain (calcein-AM) and a cell viability dye (propidium iodide) and compared the data generated by flow and image cytometry. We report that measuring vitality and viability using the image cytometer is as effective as flow cytometric assays and allows for visual confirmation of the sample to exclude cellular debris. Image cytometry offers a direct method for performing fluorescent cell-based assays but also may be used as a complementary tool to flow cytometers for aiding the analysis of more complex samples.     

Resolving heterogeneity on the single molecular level with the photon-counting histogram

The diffusion of fluorescent particles through a small, illuminated observation volume gives rise to intensity fluctuations caused by particle number fluctuations in the open observation volume and the inhomogeneous excitation-beam profile. The intensity distribution of these fluorescence fluctuations is experimentally captured by the photon-counting histogram (PCH). We recently introduced the theory of the PCH for diffusing particles (Chen et al., Biophys. J., 77:553-567), where we showed that we can uniquely describe the distribution of photon counts with only two parameters for each species: the molecular brightness of the particle and the average number of particles within the observation volume. The PCH is sensitive to the molecular brightness and thus offers the possibility to separate a mixture of fluorescent species into its constituents, based on a difference in their molecular brightness alone. This analysis is complementary to the autocorrelation function, traditionally used in fluorescence fluctuation spectroscopy, which separates a mixture of species by a difference in their diffusion coefficient. The PCH of each individual species is convoluted successively to yield the PCH of the mixture. Successful resolution of the histogram into its components is largely a matter of the signal statistics. Here, we discuss the case of two species in detail and show that a concentration for each species exists, where the signal statistics is optimal. We also discuss the influence of the absolute molecular brightness and the brightness contrast between two species on the resolvability of two species. A binary dye mixture serves as a model system to demonstrate that the molecular brightness and the concentration of each species can be resolved experimentally from a single or from several histograms. We extend our study to biomolecules, where we label proteins with a fluorescent dye and show that a brightness ratio of two can be resolved. The ability to resolve a brightness ratio of two is very important for biological applications.     

Spatial-temporal studies of membrane dynamics: scanning fluorescence correlation spectroscopy (SFCS)

Giant unilamellar vesicles (GUVs) have been widely used as a model membrane system to study membrane organization, dynamics, and protein-membrane interactions. Most recent studies have relied on imaging methods, which require good contrast for image resolution. Multiple sequential image processing only detects slow components of membrane dynamics. We have developed a new fluorescence correlation spectroscopy (FCS) technique, termed scanning FCS (i.e., SFCS), which performs multiple FCS measurements simultaneously by rapidly directing the excitation laser beam in a uniform (circular) scan across the bilayer of the GUVs in a repetitive fashion. The scan rate is fast compared to the diffusion of the membrane proteins and even small molecules in the GUVs. Scanning FCS outputs a "carpet" of timed fluorescence intensity fluctuations at specific points along the scan. In this study, GUVs were assembled from rat kidney brush border membranes, which included the integral membrane proteins. Scanning FCS measurements on GUVs allowed for a straightforward detection of spatial-temporal interactions between the protein and the membrane based on the diffusion rate of the protein. To test for protein incorporation into the bilayers of the GUVs, antibodies against one specific membrane protein (NaPi II cotransporter) were labeled with ALEXA-488. Fluorescence images of the GUVs in the presence of the labeled antibody showed marginal fluorescence enhancement on the GUV membrane bilayers (poor image contrast and resolution). With the application of scanning FCS, the binding of the antibody to the GUVs was detected directly from the analysis of diffusion rates of the fluorescent antibody. The diffusion coefficient of the antibody bound to NaPi II in the GUVs was approximately 200-fold smaller than that in solution. Scanning FCS provided a simple, quantitative, yet highly sensitive method to study protein-membrane interactions.     

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.     

Molecular insights into cell toxicity of a novel familial amyloidogenic variant of β2‐microglobulin

The first genetic variant of β₂‐microglobulin (b2M) associated with a familial form of systemic amyloidosis has been recently described. The mutated protein, carrying a substitution of Asp at position 76 with an Asn (D76N b2M), exhibits a strongly enhanced amyloidogenic tendency to aggregate with respect to the wild‐type protein. In this study, we characterized the D76N b2M aggregation path and performed an unprecedented analysis of the biochemical mechanisms underlying aggregate cytotoxicity. We showed that, contrarily to what expected from other amyloid studies, early aggregates of the mutant are not the most toxic species, despite their higher surface hydrophobicity. By modulating ganglioside GM1 content in cell membrane or synthetic lipid bilayers, we confirmed the pivotal role of this lipid as aggregate recruiter favouring their cytotoxicity. We finally observed that the aggregates bind to the cell membrane inducing an alteration of its elasticity (with possible functional unbalance and cytotoxicity) in GM1‐enriched domains only, thus establishing a link between aggregate‐membrane contact and cell damage.     

Diffusional properties of methanogenic granular sludge: 1H NMR characterization

The diffusive properties of anaerobic methanogenic and sulfidogenic aggregates present in wastewater treatment bioreactors were studied using diffusion analysis by relaxation time-separated pulsed-field gradient nuclear magnetic resonance (NMR) spectroscopy and NMR imaging. NMR spectroscopy measurements were performed at 22 degrees C with 10 ml of granular sludge at a magnetic field strength of 0.5 T (20 MHz resonance frequency for protons). Self-diffusion coefficients of H(2)O in the investigated series of mesophilic aggregates were found to be 51 to 78% lower than the self-diffusion coefficient of free water. Interestingly, self-diffusion coefficients of H(2)O were independent of the aggregate size for the size fractions investigated. Diffusional transport occurred faster in aggregates growing under nutrient-rich conditions (e.g., the bottom of a reactor) or at high (55 degrees C) temperatures than in aggregates cultivated in nutrient-poor conditions or at low (10 degrees C) temperatures. Exposure of aggregates to 2.5% glutaraldehyde or heat (70 or 90 degrees C for 30 min) modified the diffusional transport up to 20%. In contrast, deactivation of aggregates by HgCl(2) did not affect the H(2)O self-diffusion coefficient in aggregates. Analysis of NMR images of a single aggregate shows that methanogenic aggregates possess a spin-spin relaxation time and self-diffusion coefficient distribution, which are due to both physical (porosity) and chemical (metal sulfide precipitates) factors.     

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.     

Accurate measurements of protein interactions in cells via improved spatial image cross-correlation spectroscopy

The sensitive detection of protein interactions in living cells is an important first step toward understanding each of the multitude of cellular processes that are regulated by such interactions. Spatial image cross-correlation spectroscopy (ICCS) is one method used to measure protein-protein interactions from the analysis of two-channel fluorescence microscopy images. In spatial ICCS, cross-correlation of fluctuations in fluorescence intensity recorded as images from two independent wavelength detection channels in a fluorescence microscope is used to determine the average number of interacting particles in the imaged region. Even in situations where the particle number density is relatively high, ICCS provides an accurate measure of molecular interactions. However, it was shown previously that the method suffers from relatively high detection limits of interacting particles (approximately 20%) and can be perturbed by heterogeneous spatial distributions of the fluorescent particles within the images. Here, we demonstrate new approaches to circumvent some of the limitations of ICCS. Spatial scrambling of pixel blocks within fluorescence images was investigated as a way of extending the detection of spatial ICCS to measure lower interaction fractions as well as colocalization within cells. We also show that 'mean-intensity-padding' of regions of interest within fluorescence images is a feasible method of applying ICCS to arbitrarily selected areas of the cell with boundaries or edge morphologies that would be impossible to analyze with conventional ICCS. Using these newly developed strategies we were able to measure the fraction of actin that interacts with alpha-actinin in the leading edge of a migrating cell.     

Quantifying Phenotypic Variation in Isogenic Caenorhabditis elegans Expressing Phsp-16.2::gfp by Clustering 2D Expression Patterns

Isogenic populations of animals still show a surprisingly large amount of phenotypic variation between individuals. Using a GFP reporter that has been shown to predict longevity and resistance to stress in isogenic populations of the nematode Caenorhabditis elegans, we examined residual variation in expression of this GFP reporter. We found that when we separated the populations into brightest 3% and dimmest 3% we also saw variation in relative expression patterns that distinguished the bright and dim worms. Using a novel image processing method which is capable of directly analyzing worm images, we found that bright worms (after normalization to remove variation between bright and dim worms) had expression patterns that correlated with other bright worms but that dim worms fell into two distinct expression patterns. We have analysed a small set of worms with confocal microscopy to validate these findings, and found that the activity loci in these clusters are caused by extremely bright intestine cells. We also found that the vast majority of the fluorescent signal for all worms came from intestinal cells as well, which may indicate that the activity of intestinal cells is responsible for the observed patterns. Phenotypic variation in C. elegans is still not well understood but our proposed novel method to analyze complex expression patterns offers a way to enable a better understanding.     

Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis.

The accurate measurement of bacterial and protistan cell biomass is necessary for understanding their population and trophic dynamics in nature. Direct measurement of fluorescently stained cells is often the method of choice. The tedium of making such measurements visually on the large numbers of cells required has prompted the use of automatic image analysis for this purpose. Accurate measurements by image analysis require an accurate, reliable method of segmenting the image, that is, distinguishing the brightly fluorescing cells from a dark background. This is commonly done by visually choosing a threshold intensity value which most closely coincides with the outline of the cells as perceived by the operator. Ideally, an automated method based on the cell image characteristics should be used. Since the optical nature of edges in images of light-emitting, microscopic fluorescent objects is different from that of images generated by transmitted or reflected light, it seemed that automatic segmentation of such images may require special considerations. We tested nine automated threshold selection methods using standard fluorescent microspheres ranging in size and fluorescence intensity and fluorochrome-stained samples of cells from cultures of cyanobacteria, flagellates, and ciliates. The methods included several variations based on the maximum intensity gradient of the sphere profile (first derivative), the minimum in the second derivative of the sphere profile, the minimum of the image histogram, and the midpoint intensity. Our results indicated that thresholds determined visually and by first-derivative methods tended to overestimate the threshold, causing an underestimation of microsphere size. The method based on the minimum of the second derivative of the profile yielded the most accurate area estimates for spheres of different sizes and brightnesses and for four of the five cell types tested. A simple model of the optical properties of fluorescing objects and the video acquisition system is described which explains how the second derivative best approximates the position of the edge.