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.     

Multi-Image Colocalization and Its Statistical Significance

Accurately localizing molecules within the cell is one of main tasks of modern biology, and colocalization analysis is one of its principal and most often used tools. Despite this popularity, interpretation is often uncertain because colocalization between two or more images is rarely analyzed to determine whether the observed values could have occurred by chance. To address this, we have developed a robust methodology, based on Monte Carlo randomization, to measure the statistical significance of a colocalization. The method works with voxel-based, intensity-based, object-based, and nearest-neighbor metrics. We extend all of these to measure colocalization in images with three colors. We also introduce three new metrics; blob colocalization, where the blob consists of a local maximum surrounded by a three-dimensional group of voxels; cluster diameter, to measure the clustering of fluorophores in three or more images; and the intercluster distance to measure the distance between these clusters. The robustness of these metrics was tested by varying the image thresholds over a broad range, which produced no change in the statistical significance of the colocalizations. A comparison of blob colocalization with voxel and Manders colocalization metrics shows that the different measures produce consistent results with similar values for significance and nonsignificance. Using our methodology, we are able to determine not only whether the labeled molecules colocalize with a probability greater than chance, but also whether they are sequestrated into different compartments. The program, written in C++, is freely available as source, as well as in a Linux version.     

Coordinate-based colocalization analysis of single-molecule localization microscopy data

Colocalization of differently labeled biomolecules is a valuable tool in fluorescence microscopy and can provide information on biomolecular interactions. With the advent of super-resolution microscopy, colocalization analysis is getting closer to molecular resolution, bridging the gap to other technologies such as fluorescence resonance energy transfer. Among these novel microscopic techniques, single-molecule localization-based super-resolution methods offer the advantage of providing single-molecule coordinates that, rather than intensity information, can be used for colocalization analysis. This requires adapting the existing mathematical algorithms for localization microscopy data. Here, we introduce an algorithm for coordinate-based colocalization analysis which is suited for single-molecule super-resolution data. In addition, we present an experimental configuration for simultaneous dual-color imaging together with a robust approach to correct for optical aberrations with an accuracy of a few nanometers. We demonstrate the potential of our approach for cellular structures and for two proteins binding actin filaments.     

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.     

Bioinformatic and image analyses of the cellular localization of the apoptotic proteins endonuclease G,AIF, and AMID during apoptosis in human cells

We studied the cellular localization of the apoptotic proteins endonuclease G, AIF, and AMID in silico using three prediction tools and in living cells using both single-cell colocalization image analysis and nuclear translocation analysis. We confirmed the mitochondrial localization of endonuclease G and AIF by prediction analysis and by single-cell colocalization image analysis. We found the AMID protein to be cytoplasmic, most probably incorporated into the cytoplasmic side of the membranes of various organelles. The highest concentration of AMID was observed associated with the Golgi. Colocalization of AMID with lysosomes was also indirectly confirmed by analysis of AMID-rich vesicle velocity using manual tracking analysis. Bioinformatic analysis also detected nuclear localization signals in endonuclease G and AIF, but not in AMID. A novel analysis of time-lapse fluorescence image data during staurosporine-induced apoptosis revealed nuclear translocation only for endonuclease G and AIF.     

Decoding the entry of two novel cell-penetrating peptides in HeLa cells: lipid raft-mediated endocytosis and endosomal escape

Cellular entry of peptide, protein, and nucleic acid biopharmaceuticals is severely impeded by the cell membrane. Linkage or assembly of such agents and cell-penetrating peptides (CPP) with the ability to cross cellular membranes has opened a new horizon in biomedical research. Nevertheless, the uptake mechanisms of most CPP have been controversially discussed and are poorly understood. We present data on two recently developed oligocationic CPP, the sweet arrow peptide SAP, a gamma-zein-related sequence, and a branched human calcitonin derived peptide, hCT(9-32)-br, carrying a simian virus derived nuclear localization sequence in the side chain. Uptake in HeLa cells and intracellular trafficking of N-terminally carboxyfluorescein labeled peptides was studied by confocal laser scanning microscopy and flow cytometry using biochemical markers in combination with quenching and colocalization approaches. Both peptides were readily internalized by HeLa cells through interaction with the extracellular matrix followed by lipid raft-mediated endocytosis as confirmed by reduced uptake at lower temperature, in the presence of endocytosis inhibitors and through cholesterol depletion by methyl-beta-cyclodextrin, supported by colocalization with markers for clathrin-independent pathways. In contrast to the oligocationic SAP and hCT(9-32)-br, interaction with the extracellular matrix, however, was no prerequisite for the observed lipid raft-mediated uptake of the weakly cationic, unbranched hCT(9-32). Transient involvement of endosomes in intracellular trafficking of SAP and hCT(9-32)-br prior to endosomal escape of both peptides was revealed by colocalization and pulse-chase studies of the peptides with the early endosome antigen 1. The results bear potential for CPP as tools for intracellular drug delivery.     

Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples

Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest Points registration method. Results for fixed and live experimental data shows the association method to perform comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for live cells.     

Autophagosome-lysosome fusion depends on the pH in acidic compartments in CHO cells

Autophagy is the bulk degradation of cytoplasmic constituents in response to starvation and other environmental or intracellular cues. During this process, most of the cytoplasm is sequestered into autophagosomes, which then fuse with lysosomes where the degradation of the sequestered material proceeds. We investigated the relationship between autophagosome-lysosome fusion and the pH in acidic compartments by visualizing the fusion process using fluorescence in CHO cells. In this experiment, mitochondria were labeled with GFP by transfecting CHO cells with the presequence of ornithine transcarbamylase, and lysosomes were labeled with Texas Red Dextran; any fusion was identified by the colocalization of mitochondria (in autophagosomes) and lysosomes using fluorescence microscopy. When CHO cells were treated with rapamycin or starvation medium to induce autophagy, the colocalization of fluorescence was observed. Whereas when they were treated with 3-MA, an inhibitor of autophagy, the colocalization disappeared. We conclude that the colocalization reflects the fusion of autophagosomes and lysosomes. Moreover, when the CHO cells were treated with drugs that increase the pH of acidic compartments, the colocalization disappeared. This suggests that the autophagosome-lysosome fusion is inhibited by increasing pH in acidic compartments independently of V-ATPase activity in CHO cells.     

SpatTrack: An Imaging Toolbox for Analysis of Vesicle Motility and Distribution in Living Cells

The endocytic pathway is a complex network of highly dynamic organelles, which has been traditionally studied by quantitative fluorescence microscopy. The data generated by this method can be overwhelming and its analysis, even for the skilled microscopist, is tedious and error‐prone. We developed SpatTrack, an open source, platform‐independent program collecting a variety of methods for analysis of vesicle dynamics and distribution in living cells. SpatTrack performs 2D particle tracking, trajectory analysis and fitting of diffusion models to the calculated mean square displacement. It allows for spatial analysis of detected vesicle patterns including calculation of the radial distribution function and particle‐based colocalization. Importantly, all analysis tools are supported by Monte Carlo simulations of synthetic images. This allows the user to assess the reliability of the analysis and to study alternative scenarios. We demonstrate the functionality of SpatTrack by performing a detailed imaging study of internalized fluorescence‐tagged Niemann Pick C2 (NPC2) protein in human disease fibroblasts. Using SpatTrack, we show that NPC2 rescued the cholesterol‐storage phenotype from a subpopulation of late endosomes/lysosomes (LE/LYSs). This was paralleled by repositioning and active transport of NPC2‐containing vesicles to the cell surface. The potential of SpatTrack for other applications in intracellular transport studies will be discussed.      

Imaging molecular interactions in living cells

Hormones integrate the activities of their target cells through receptor-modulated cascades of protein interactions that ultimately lead to changes in cellular function. Understanding how the cell assembles these signaling protein complexes is critically important to unraveling disease processes, and to the design of therapeutic strategies. Recent advances in live-cell imaging technologies, combined with the use of genetically encoded fluorescent proteins, now allow the assembly of these signaling protein complexes to be tracked within the organized microenvironment of the living cell. Here, we review some of the recent developments in the application of imaging techniques to measure the dynamic behavior, colocalization, and spatial relationships between proteins in living cells. Where possible, we discuss the application of these different approaches in the context of hormone regulation of nuclear receptor localization, mobility, and interactions in different subcellular compartments. We discuss measurements that define the spatial relationships and dynamics between proteins in living cells including fluorescence colocalization, fluorescence recovery after photobleaching, fluorescence correlation spectroscopy, fluorescence resonance energy transfer microscopy, and fluorescence lifetime imaging microscopy. These live-cell imaging tools provide an important complement to biochemical and structural biology studies, extending the analysis of protein-protein interactions, protein conformational changes, and the behavior of signaling molecules to their natural environment within the intact cell.     

The CryoCapsule: Simplifying Correlative Light to Electron Microscopy

Correlating complementary multiple scale images of the same object is a straightforward means to decipher biological processes. Light microscopy and electron microscopy are the most commonly used imaging techniques, yet despite their complementarity, the experimental procedures available to correlate them are technically complex. We designed and manufactured a new device adapted to many biological specimens, the CryoCapsule, that simplifies the multiple sample preparation steps, which at present separate live cell fluorescence imaging from contextual high‐resolution electron microscopy, thus opening new strategies for full correlative light to electron microscopy. We tested the biological application of this highly optimized tool on three different specimens: the in vitro Xenopus laevis mitotic spindle, melanoma cells over‐expressing YFP‐langerin sequestered in organized membranous subcellular organelles and a pigmented melanocytic cell in which the endosomal system was labeled with internalized fluorescent transferrin.      

A three-dimensional colocalization RNA interference screening platform to elucidate the alternative lengthening of telomeres pathway

A high-content colocalization RNA interference screen based on automatic three-color confocal fluorescence microscopy was developed to analyze the alternative lengthening of telomeres (ALT) pathway. Via this pathway telomerase-negative cancer cells can maintain their telomeres and with it their unlimited proliferative potential. A hallmark of ALT cells is the colocalization of promyelocytic leukemia (PML) nuclear bodies with telomeres to form ALT-associated PML nuclear bodies (APBs). In our screen, the presence of APBs was used as a marker to identify proteins required for the ALT mechanism. A cell-based assay and an automatic confocal image acquisition procedure were established. Using automatic image analysis based on 3D parametric intensity models to identify APBs, we conducted an unbiased and quantitative analysis of nine different candidate genes. A comparison with the literature and manual analysis of the gene knockdown demonstrates the reliability of our approach. It extends the available repertoire of high-content screening to studies of cellular colocalizations and allows the identification of candidate genes for the ALT mechanism that represent possible targets for cancer therapy.     

Localization of Autocrine Motility Factor Receptor to Caveolae and Clathrin-independent Internalization of Its Ligand to Smooth Endoplasmic Reticulum

Autocrine motility factor receptor (AMF-R) is a cell surface receptor that is also localized to a smooth subdomain of the endoplasmic reticulum, the AMF-R tubule. By postembedding immunoelectron microscopy, AMF-R concentrates within smooth plasmalemmal vesicles or caveolae in both NIH-3T3 fibroblasts and HeLa cells. By confocal microscopy, cell surface AMF-R labeled by the addition of anti-AMF-R antibody to viable cells at 4°C exhibits partial colocalization with caveolin, confirming the localization of cell surface AMF-R to caveolae. Labeling of cell surface AMF-R by either anti-AMF-R antibody or biotinylated AMF (bAMF) exhibits extensive colocalization and after a pulse of 1–2 h at 37°C, bAMF accumulates in densely labeled perinuclear structures as well as fainter tubular structures that colocalize with AMF-R tubules. After a subsequent 2- to 4-h chase, bAMF is localized predominantly to AMF-R tubules. Cytoplasmic acidification, blocking clathrin-mediated endocytosis, results in the essentially exclusive distribution of internalized bAMF to AMF-R tubules. By confocal microscopy, the tubular structures labeled by internalized bAMF show complete colocalization with AMF-R tubules. bAMF internalized in the presence of a 10-fold excess of unlabeled AMF labels perinuclear punctate structures, which are therefore the product of fluid phase endocytosis, but does not label AMF-R tubules, demonstrating that bAMF targeting to AMF-R tubules occurs via a receptor-mediated pathway. By electron microscopy, bAMF internalized for 10 min is located to cell surface caveolae and after 30 min is present within smooth and rough endoplasmic reticulum tubules. AMF-R is therefore internalized via a receptor-mediated clathrin-independent pathway to smooth ER. The steady state localization of AMF-R to caveolae implicates these cell surface invaginations in AMF-R endocytosis.     

Autophagosome-Lysosome Fusion Depends on the pH in Acidic Compartments in CHO Cells

Autophagy is the bulk degradation of cytoplasmic constituents in response to starvation and other environmental or intracellular cues. During this process, most of the cytoplasm is sequestered into autophagosomes, which then fuse with lysosomes where the degradation of the sequestered material proceeds. We investigated the relationship between autophagosome-lysosome fusion and the pH in acidic compartments by visualizing the fusion process using fluorescence in CHO cells. In this experiment, mitochondria were labeled with GFP by transfecting CHO cells with the presequence of ornithine transcarbamylase, and lysosomes were labeled with Texas Red Dextran; any fusion was identified by the colocalization of mitochondria (in autophagosomes) and lysosomes using fluorescence microscopy. When CHO cells were treated with rapamycin or starvation medium to induce autophagy, the colocalization of fluorescence was observed. Whereas when they were treated with 3-MA, an inhibitor of autophagy, the colocalization disappeared. We conclude that the colocalization reflects the fusion of autophagosomes and lysosomes. Moreover, when the CHO cells were treated with drugs that increase the pH of acidic compartments, the colocalization disappeared. This suggests that the autophagosome-lysosome fusion is inhibited by increasing pH in acidic compartments independently of V-ATPase activity in CHO cells.

Addendum to:

Quantitative Monitoring of Autophagic Degradation

Akinori Kawai, Syuichi Takano, Nobuhiro Nakamura and Shoji Ohkuma

Biochem Biophys Res Commun 2006; 351:71-7     

New methods to evaluate colocalization of fluorophores in immunocytochemical preparations as exemplified by a study on A2A and D2 receptors in Chinese hamster ovary cells.

An important aspect of the image analysis of immunocytochemical preparations is the evaluation of colocalization of different molecules. The aim of the present study is to introduce image analysis methods to identify double-labeled locations exhibiting the highest association of two fluorophores and to characterize their pattern of distribution. These methods will be applied to the analysis of the cotrafficking of adenosine A2A and dopamine D2 receptors belonging to the G protein-coupled receptor family and visualized by means of fluorescence immunocytochemistry in Chinese hamster ovary cells after agonist treatment. The present procedures for colocalization have the great advantage that they are, to a large extent, insensitive to the need for a balanced staining with the two fluorophores. Thus, these procedures involve image processing, visualization, and analysis of colocalized events, using a covariance method and a multiply method and the evaluation of the identified colocalization patterns. Moreover, the covariance method offers the possibility of detecting and quantitatively characterizing anticorrelated patterns of intensities, whereas the immediate detection of colocalized clusters with a high concentration of labeling is a possibility offered by the multiply method. The present methods offer a new and sensitive approach to detecting and quantitatively characterizing strongly associated fluorescence events, such as those generated by receptor-receptor interaction, and their distribution patterns in dual-color confocal laser microscopy.     

Proteomic analysis of protein complexes

While it sometimes does not generate the publicity that biomarker discovery does, the identification of protein complexes may be the most popular use of proteomic technology. The partners a protein interacts with is a key component that describes the function of any protein. Basic research has long appreciated the importance of identifying protein interactions through techniques such as Western blotting and colocalization studies using immunofluorescence microscopy. This appreciation has carried over into the field of proteomics and brought with it the development of tools that increase the capabilities to characterize protein complexes to a far greater scale. While advances in technology have had a huge impact, sample preparation issues related to the isolation of protein complexes remains a critical factor in determining the success of these types of studies.     

On Optical Detection of Densely Labeled Synapses in Neuropil and Mapping Connectivity with Combinatorially Multiplexed Fluorescent Synaptic Markers

We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM). Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools.     

Grid computing in image analysis

Diagnostic surgical pathology or tissue–based diagnosis still remains the most reliable and specific diagnostic medical procedure. The development of whole slide scanners permits the creation of virtual slides and to work on so-called virtual microscopes. In addition to interactive work on virtual slides approaches have been reported that introduce automated virtual microscopy, which is composed of several tools focusing on quite different tasks. These include evaluation of image quality and image standardization, analysis of potential useful thresholds for object detection and identification (segmentation), dynamic segmentation procedures, adjustable magnification to optimize feature extraction, and texture analysis including image transformation and evaluation of elementary primitives. Grid technology seems to possess all features to efficiently target and control the specific tasks of image information and detection in order to obtain a detailed and accurate diagnosis. Grid technology is based upon so-called nodes that are linked together and share certain communication rules in using open standards. Their number and functionality can vary according to the needs of a specific user at a given point in time. When implementing automated virtual microscopy with Grid technology, all of the five different Grid functions have to be taken into account, namely 1) computation services, 2) data services, 3) application services, 4) information services, and 5) knowledge services. Although all mandatory tools of automated virtual microscopy can be implemented in a closed or standardized open system, Grid technology offers a new dimension to acquire, detect, classify, and distribute medical image information, and to assure quality in tissue–based diagnosis.     

New algorithm to determine true colocalization in combination with image restoration and time-lapse confocal microscopy to MAP kinases in mitochondria

The subcellular localization and physiological functions of biomolecules are closely related and thus it is crucial to precisely determine the distribution of different molecules inside the intracellular structures. This is frequently accomplished by fluorescence microscopy with well-characterized markers and posterior evaluation of the signal colocalization. Rigorous study of colocalization requires statistical analysis of the data, albeit yet no single technique has been established as a standard method. Indeed, the few methods currently available are only accurate in images with particular characteristics. Here, we introduce a new algorithm to automatically obtain the true colocalization between images that is suitable for a wide variety of biological situations. To proceed, the algorithm contemplates the individual contribution of each pixel's fluorescence intensity in a pair of images to the overall Pearsońs correlation and Manders' overlap coefficients. The accuracy and reliability of the algorithm was validated on both simulated and real images that reflected the characteristics of a range of biological samples. We used this algorithm in combination with image restoration by deconvolution and time-lapse confocal microscopy to address the localization of MEK1 in the mitochondria of different cell lines. Appraising the previously described behavior of Akt1 corroborated the reliability of the combined use of these techniques. Together, the present work provides a novel statistical approach to accurately and reliably determine the colocalization in a variety of biological images.