Testing independence between two random sets for the analysis of colocalization in bioimaging

Colocalization aims at characterizing spatial associations between two fluorescently tagged biomolecules by quantifying the co-occurrence and correlation between the two channels acquired in fluorescence microscopy. Colocalization is presented either as the degree of overlap between the two channels or the overlays of the red and green images, with areas of yellow indicating colocalization of the molecules. This problem remains an open issue in diffraction-limited microscopy and raises new challenges with the emergence of superresolution imaging, a microscopic technique awarded by the 2014 Nobel prize in chemistry. We propose GcoPS, for Geo-coPositioning System, an original method that exploits the random sets structure of the tagged molecules to provide an explicit testing procedure. Our simulation study shows that GcoPS unequivocally outperforms the best competitive methods in adverse situations (noise, irregularly shaped fluorescent patterns, and different optical resolutions). GcoPS is also much faster, a decisive advantage to face the huge amount of data in superresolution imaging. We demonstrate the performances of GcoPS on two biological real data sets, obtained by conventional diffraction-limited microscopy technique and by superresolution technique, respectively.     

High-Density 3D Single Molecular Analysis Based on Compressed Sensing

Single molecule fitting-based superresolution microscopy achieves sub-diffraction-limit image resolution but suffers from a need for long acquisition times to gather enough molecules. Several methods have recently been developed that analyze high molecule density images but most are only applicable to two dimensions. In this study, we implemented a high-density superresolution localization algorithm based on compressed sensing and a biplane approach that provides three-dimensional information about molecules, achieving super-resolution imaging at higher molecule densities than those achieved using the conventional single molecule fitting method.     

High-Density 3D Single Molecular Analysis Based on Compressed Sensing

Single molecule fitting-based superresolution microscopy achieves sub-diffraction-limit image resolution but suffers from a need for long acquisition times to gather enough molecules. Several methods have recently been developed that analyze high molecule density images but most are only applicable to two dimensions. In this study, we implemented a high-density superresolution localization algorithm based on compressed sensing and a biplane approach that provides three-dimensional information about molecules, achieving super-resolution imaging at higher molecule densities than those achieved using the conventional single molecule fitting method.     

Extended-Depth 3D Super-Resolution Imaging Using Probe-Refresh STORM

Single-molecule localization microscopy methods for super-resolution fluorescence microscopy such as STORM (stochastic optical reconstruction microscopy) are generally limited to thin three-dimensional (3D) sections (≤600 nm) because of photobleaching of molecules outside the focal plane. Although multiple focal planes may be imaged before photobleaching by focusing progressively deeper within the sample, image quality is compromised in this approach because the total number of measurable localizations is divided between detection planes. Here, we solve this problem on fixed samples by developing an imaging method that we call probe-refresh STORM (prSTORM), which allows bleached fluorophores to be straightforwardly replaced with nonbleached fluorophores. We accomplish this by immunostaining the sample with DNA-conjugated antibodies and then reading out their distribution using fluorescently-labeled DNA-reporter oligonucleotides that can be fully replaced in successive rounds of imaging. We demonstrate that prSTORM can acquire 3D images over extended depths without sacrificing the density of localizations at any given plane. We also show that prSTORM can be adapted to obtain high-quality, 3D multichannel images with extended depth that would be challenging or impossible to achieve using established probe methods.     

Two-color STED microscopy of living synapses using a single laser-beam pair

The advent of superresolution microscopy has opened up new research opportunities into dynamic processes at the nanoscale inside living biological specimens. This is particularly true for synapses, which are very small, highly dynamic, and embedded in brain tissue. Stimulated emission depletion (STED) microscopy, a recently developed laser-scanning technique, has been shown to be well suited for imaging living synapses in brain slices using yellow fluorescent protein as a single label. However, it would be highly desirable to be able to image presynaptic boutons and postsynaptic spines, which together form synapses, using two different fluorophores. As STED microscopy uses separate laser beams for fluorescence excitation and quenching, incorporation of multicolor imaging for STED is more difficult than for conventional light microscopy. Although two-color schemes exist for STED microscopy, these approaches have several drawbacks due to their complexity, cost, and incompatibility with common labeling strategies and fluorophores. Therefore, we set out to develop a straightforward method for two-color STED microscopy that permits the use of popular green-yellow fluorescent labels such as green fluorescent protein, yellow fluorescent protein, Alexa Fluor 488, and calcein green. Our new (to our knowledge) method is based on a single-excitation/STED laser-beam pair to simultaneously excite and quench pairs of these fluorophores, whose signals can be separated by spectral detection and linear unmixing. We illustrate the potential of this approach by two-color superresolution time-lapse imaging of axonal boutons and dendritic spines in living organotypic brain slices.     

Ultra-high resolution imaging by fluorescence photoactivation localization microscopy

Biological structures span many orders of magnitude in size, but far-field visible light microscopy suffers from limited resolution. A new method for fluorescence imaging has been developed that can obtain spatial distributions of large numbers of fluorescent molecules on length scales shorter than the classical diffraction limit. Fluorescence photoactivation localization microscopy (FPALM) analyzes thousands of single fluorophores per acquisition, localizing small numbers of them at a time, at low excitation intensity. To control the number of visible fluorophores in the field of view and ensure that optically active molecules are separated by much more than the width of the point spread function, photoactivatable fluorescent molecules are used, in this case the photoactivatable green fluorescent protein (PA-GFP). For these photoactivatable molecules, the activation rate is controlled by the activation illumination intensity; nonfluorescent inactive molecules are activated by a high-frequency (405-nm) laser and are then fluorescent when excited at a lower frequency. The fluorescence is imaged by a CCD camera, and then the molecules are either reversibly inactivated or irreversibly photobleached to remove them from the field of view. The rate of photobleaching is controlled by the intensity of the laser used to excite the fluorescence, in this case an Ar+ ion laser. Because only a small number of molecules are visible at a given time, their positions can be determined precisely; with only approximately 100 detected photons per molecule, the localization precision can be as much as 10-fold better than the resolution, depending on background levels. Heterogeneities on length scales of the order of tens of nanometers are observed by FPALM of PA-GFP on glass. FPALM images are compared with images of the same molecules by widefield fluorescence. FPALM images of PA-GFP on a terraced sapphire crystal surface were compared with atomic force microscopy and show that the full width at half-maximum of features approximately 86 +/- 4 nm is significantly better than the expected diffraction-limited optical resolution. The number of fluorescent molecules and their brightness distribution have also been determined using FPALM. This new method suggests a means to address a significant number of biological questions that had previously been limited by microscope resolution.     

Direct stochastic optical reconstruction microscopy with standard fluorescent probes

Direct stochastic optical reconstruction microscopy (dSTORM) uses conventional fluorescent probes such as labeled antibodies or chemical tags for subdiffraction resolution fluorescence imaging with a lateral resolution of ～20 nm. In contrast to photoactivated localization microscopy (PALM) with photoactivatable fluorescent proteins, dSTORM experiments start with bright fluorescent samples in which the fluorophores have to be transferred to a stable and reversible OFF state. The OFF state has a lifetime in the range of 100 milliseconds to several seconds after irradiation with light intensities low enough to ensure minimal photodestruction. Either spontaneously or photoinduced on irradiation with a second laser wavelength, a sparse subset of fluorophores is reactivated and their positions are precisely determined. Repetitive activation, localization and deactivation allow a temporal separation of spatially unresolved structures in a reconstructed image. Here we present a step-by-step protocol for dSTORM imaging in fixed and living cells on a wide-field fluorescence microscope, with standard fluorescent probes focusing especially on the photoinduced fine adjustment of the ratio of fluorophores residing in the ON and OFF states. Furthermore, we discuss labeling strategies, acquisition parameters, and temporal and spatial resolution. The ultimate step of data acquisition and data processing can be performed in seconds to minutes.     

Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins.     

Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)

We have developed a high-resolution fluorescence microscopy method based on high-accuracy localization of photoswitchable fluorophores. In each imaging cycle, only a fraction of the fluorophores were turned on, allowing their positions to be determined with nanometer accuracy. The fluorophore positions obtained from a series of imaging cycles were used to reconstruct the overall image. We demonstrated an imaging resolution of 20 nm. This technique can, in principle, reach molecular-scale resolution.     

Lucky Imaging: Improved Localization Accuracy for Single Molecule Imaging

We apply the astronomical data-analysis technique, Lucky imaging, to improve resolution in single molecule fluorescence microscopy. We show that by selectively discarding data points from individual single-molecule trajectories, imaging resolution can be improved by a factor of 1.6 for individual fluorophores and up to 5.6 for more complex images. The method is illustrated using images of fluorescent dye molecules and quantum dots, and the in vivo imaging of fluorescently labeled linker for activation of T cells.     

Detecting and quantifying colocalization of cell surface molecules by single particle fluorescence imaging

Single particle fluorescence imaging (SPFI) uses the high sensitivity of fluorescence to visualize individual molecules that have been selectively labeled with small fluorescent particles. The positions of particles are determined by fitting the intensity profile of their images to a 2-D Gaussian function. We have exploited the positional information obtained from SPFI to develop a method for detecting colocalization of cell surface molecules. This involves labeling two different molecules with different colored fluorophores and determining their positions separately by dual wavelength imaging. The images are analyzed to quantify the overlap of the particle images and hence determine the extent of colocalization of the labeled molecules. Simulated images and experiments with a model system are used to investigate the extent to which colocalization occurs from chance proximity of randomly distributed molecules. A method of correcting for positional shifts that result from chromatic aberration is presented. The technique provides quantification of the extent of colocalization and can detect whether colocalized molecules occur singly or in clusters. We have obtained preliminary data for colocalization of molecules on intact cells. Cells often exhibit particulate autofluorescence that can interfere with the measurements; a method for overcoming this problem by triple wavelength imaging is described.     

Sequential Superresolution Imaging of Multiple Targets Using a Single Fluorophore

Fluorescence superresolution (SR) microscopy, or fluorescence nanoscopy, provides nanometer scale detail of cellular structures and allows for imaging of biological processes at the molecular level. Specific SR imaging methods, such as localization-based imaging, rely on stochastic transitions between on (fluorescent) and off (dark) states of fluorophores. Imaging multiple cellular structures using multi-color imaging is complicated and limited by the differing properties of various organic dyes including their fluorescent state duty cycle, photons per switching event, number of fluorescent cycles before irreversible photobleaching, and overall sensitivity to buffer conditions. In addition, multiple color imaging requires consideration of multiple optical paths or chromatic aberration that can lead to differential aberrations that are important at the nanometer scale. Here, we report a method for sequential labeling and imaging that allows for SR imaging of multiple targets using a single fluorophore with negligible cross-talk between images. Using brightfield image correlation to register and overlay multiple image acquisitions with ~10 nm overlay precision in the x-y imaging plane, we have exploited the optimal properties of AlexaFluor647 for dSTORM to image four distinct cellular proteins. We also visualize the changes in co-localization of the epidermal growth factor (EGF) receptor and clathrin upon EGF addition that are consistent with clathrin-mediated endocytosis. These results are the first to demonstrate sequential SR (s-SR) imaging using direct stochastic reconstruction microscopy (dSTORM), and this method for sequential imaging can be applied to any superresolution technique.     

Achieving Molecular Selectivity in Imaging Using Multiphoton Raman Spectroscopy Techniques

In the case of most optical imaging methods, contrast is generated either by physical properties of the sample (Differential Image Contrast, Phase Contrast), or by fluorescent labels that are localized to a particular protein or organelle. Standard Raman and infrared methods for obtaining images are based upon the intrinsic vibrational properties of molecules, and thus obviate the need for attached fluorophores. Unfortunately, they have significant limitations for live-cell imaging. However, an active Raman method, called Coherent Anti-Stokes Raman Scattering (CARS), is well suited for microscopy, and provides a new means for imaging specific molecules. Vibrational imaging techniques, such as CARS, avoid problems associated with photobleaching and photo-induced toxicity often associated with the use of fluorescent labels with live cells. Because the laser configuration needed to implement CARS technology is similar to that used in other multiphoton microscopy methods, such as two-photon fluorescence and harmonic generation, it is possible to combine imaging modalities, thus generating simultaneous CARS and fluorescence images. A particularly powerful aspect of CARS microscopy is its ability to selectively image deuterated compounds, thus allowing the visualization of molecules, such as lipids, that are chemically indistinguishable from the native species.     

Fluorescence lifetime imaging microscopy (flimscopy). Methodology development and application to studies of endosome fusion in single cells.

A new method of fluorescence microscopy for cell imaging has been developed that takes advantage of the spatial variations of fluorescence lifetimes in single cells as a source of image contrast, and thus it is named "fluorescence lifetime imaging microscopy (flimscopy)". Since time-resolved fluorescence measurements are sensitive to molecular dynamics and interactions, flimscopy allows the molecular information to be visualized in single cells. In flimscopy measurements, several (nanosecond) time-resolved fluorescence images of a sample are obtained at various delay times after pulsed laser excitation of the microscope's entire field of view. Lifetimes are calculated pixel-by-pixel from these time-resolved images, and the spatial variations of the lifetimes are then displayed in a pseudocolor format (flimscopy image). The total data acquisition time needed to obtain a flimscopy image with the diffraction-limited spatial resolution (approximately 250 nm) is decreased to just approximately 30 s for approximately 300 fluorescent molecules/micron2. This was achieved by developing a high-frequency (400 kHz) nanosecond-gating (9 ns full width at half height)-signal accumulation system. This technique allows the extent of resonance energy transfer to be visualized in single living cells, and is free from the errors due to variations in path length, light scattering, and the number of fluorophores that necessitate complex corrections in steady-state microfluorometry and fluorescence ratio imaging microscopy. Flimscopy was applied here to observe the extent of fusion of individual endosomes in single cells. Results revealed the occurrence of extensive fusion between primary endocytic vesicles and/or sorting endosomes, thereby raising the possibility that the biogenesis of sorting endosomes involves multiple fusions of primary endocytic vesicles.     

Efficient super‐resolution volumetric imaging by radial fluctuation Bayesian analysis light‐sheet microscopy

Various computational super‐resolution methods are available based on the analysis of fluorescence fluctuation behind acquired frames. However, dilemmas often exist in the balance of fluorophore characteristics, computation cost, and achievable resolution. Here we present an approach that uses a super‐resolution radial fluctuations (SRRF) image to guide the Bayesian analysis of fluorophore blinking and bleaching (3B) events, allowing greatly accelerated localization of overlapping fluorophores with high accuracy. This radial fluctuation Bayesian analysis (RFBA) approach is also extended to three dimensions for the first time and combined with light‐sheet fluorescence microscopy, to achieve super‐resolution volumetric imaging of thick samples densely labeled with common fluorophores. For example, a 700‐nm thin Bessel plane illumination is developed to optically section the Drosophila brain, providing a high‐contrast 3D image of rhythmic neurons. RFBA analyzes 30 serial volumes to reconstruct a super‐resolved 3D image at 4‐times higher resolutions (~70 and 170 nm), and precisely resolve the axon terminals. The computation is over 2‐orders faster than conventional 3B analysis microscopy. The capability of RFBA is also verified through dual‐color imaging of cell nucleus in live Drosophila brain. The spatial co‐localization patterns of the nuclear envelope and DNA in a neuron deep inside the brain can be precisely extracted by our approach.     

Applications of combined spectral lifetime microscopy for biology

Live cell imaging has been greatly advanced by the recent development of new fluorescence microscopy-based methods such as multiphoton laser-scanning microscopy, which can noninvasively image deep into live specimens and generate images of extrinsic and intrinsic signals. Of recent interest has been the development of techniques that can harness properties of fluorescence, other than intensity, such as the emission spectrum and excited state lifetime of a fluorophore. Spectra can be used to discriminate between fluorophores, and lifetime can be used to report on the microenvironment of fluorophores. We describe a novel technique-combined spectral and lifetime imaging-which combines the benefits of multiphoton microscopy, spectral discrimination, and lifetime analysis and allows for the simultaneous collection of all three dimensions of data along with spatial and temporal information.     

Quantifying and Optimizing Single-Molecule Switching Nanoscopy at High Speeds

Single-molecule switching nanoscopy overcomes the diffraction limit of light by stochastically switching single fluorescent molecules on and off, and then localizing their positions individually. Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. However, it has not been quantified whether this speed increase comes at the cost of compromised image quality. The spatial and temporal resolution depends on many factors, among which laser intensity and camera speed are the two most critical parameters. Here we quantitatively compare the image quality achieved when imaging Alexa Fluor 647-immunolabeled microtubules over an extended range of laser intensities and camera speeds using three criteria – localization precision, density of localized molecules, and resolution of reconstructed images based on Fourier Ring Correlation. We found that, with optimized parameters, single-molecule switching nanoscopy at high speeds can achieve the same image quality as imaging at conventional speeds in a 5–25 times shorter time period. Furthermore, we measured the photoswitching kinetics of Alexa Fluor 647 from single-molecule experiments, and, based on this kinetic data, we developed algorithms to simulate single-molecule switching nanoscopy images. We used this software tool to demonstrate how laser intensity and camera speed affect the density of active fluorophores and influence the achievable resolution. Our study provides guidelines for choosing appropriate laser intensities for imaging Alexa Fluor 647 at different speeds and a quantification protocol for future evaluations of other probes and imaging parameters.     

Precise Time Superresolution by Event Correlation Microscopy

Fluorescence imaging is often used to monitor dynamic cellular functions under conditions of very low light intensities to avoid photodamage to the cell and rapid photobleaching. Determination of the time of a fluorescence change relative to a rapid high time-resolution event, such as an action potential or pulse stimulation, is challenged by the low photon rate and the need to use imaging frame durations that limit the time resolution. To overcome these limitations, we developed a time superresolution method named event correlation microscopy that aligns repetitive events with respect to the high time-resolution events. We describe the algorithm of the method, its step response function, and a theoretical, computational, and experimental analysis of its precision, providing guidelines for camera exposure time settings depending on imaging signal properties and camera parameters for optimal time resolution. We also demonstrate the utility of the method to recover rapid nonstepwise kinetics by deconvolution fits. The event correlation microscopy method provides time superresolution beyond the photon rate limit and imaging frame duration with well-defined precision.     

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.     

Two‐photon laser‐scanning fluorescence microscopy applied for studies of human skin

Two‐photon laser scanning fluorescence microscopy (TPM) has been shown to be advantageous for imaging optically turbid media such as human skin. The ability of performing three‐dimensional imaging without presectioning of the samples makes the technique not only suitable for noninvasive diagnostics but also for studies of topical delivery of xenobiotics. Here, TPM is used as a method to visualize both autofluorescent and exogenous fluorophores in skin. Samples exposed to sulforhodamine B have been scanned from two directions to investigate attenuation effects. It is shown that optical effects play a major role. Thus, TPM is excellent for visualizing the localization and distribution of fluorophores in human skin, although quantification might be difficult. Furthermore, an image‐analysis algorithm has been implemented to facilitate interpretation of TPM images of autofluorescent features of nonmelanoma skin cancer obtained ex vivo. The algorithm was designed to detect cell nuclei and currently has a sensitivity and specificity of 82% and 78% to single cell nuclei. However, in order to detect multinucleated cells, the algorithm needs further development. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)