Artifacts in computational optical-sectioning microscopy

Evaluating the resolution of conventional optical microscopes through point spread function measurement

In the imaging process of conventional optical microscopy, the primary factor hindering microscope resolution is the energy diffusion of incident light, most directly described by the point spread function (PSF). Therefore, accurate calculation and measurement of PSF are essential for evaluating and enhancing imaging resolution. Currently, there are various methods to obtain PSFs, each with different advantages and disadvantages suitable for different scenarios. To provide a comprehensive analysis of PSF-obtaining methods, this study classifies them into four categories based on different acquisition principles and analyzes their advantages and disadvantages, starting from the propagation property of light in optical physics. Finally, two PSF-obtaining methods are proposed based on mathematical modeling and deep learning, demonstrating their effectiveness through experimental results. This study compares and analyzes these results, highlighting the practical applications of image deblurring.

Regularization of dielectric tensor tomography

Dielectric tensor tomography reconstructs the three-dimensional dielectric tensors of microscopic objects and provides information about the crystalline structure orientations and principal refractive indices. Because dielectric tensor tomography is based on transmission measurement, it suffers from the missing cone problem, which causes poor axial resolution, underestimation of the refractive index, and halo artifacts. In this study, we study the application of total variation and positive semi-definiteness regularization to three-dimensional tensor distributions. In particular, we demonstrate the reduction of artifacts when applied to dielectric tensor tomography.

Global deblurring for continuous out-of-focus images using a depth-varying diffusion model

The phenomenon of continuous out-of-focus imaging often occurs in high-magnification optical microscopy when observing large-scale targets. Lacking of accurate depth-varying point spread functions (DVPSFs) for blurred regions at different depths, it is difficult to locally reconstruct the clear images of these blurred regions using traditional deblurring methods, making it unreasonable to globally observe the optical features of large-scale targets in high-magnification optical microscopy. This paper proposes a global deblurring method for continuous out-of-focus images of large-scale sphere samples. In this study, first we analyze the energy diffusion characteristics of the optical imaging process, integrating the relationship between high-frequency energy parameters, optical range distance, and depth of field, and we propose a three-dimensional continuous energy diffusion model for optical imaging. Next, we propose an adaptive weight depth calculation method for a continuously changing surface based on the depth varying diffusion model by introducing the sample surface curvature variation and light direction. Finally, we propose a universal method for deblurring continuous out-of-focus images of large-scale sphere samples for the purpose of observing the global optical features in high-magnification optical microscopy. Moreover, we use dynamic microspheres of different sizes to verify the effectiveness of our proposed method. The results prove that our proposed method can accurately calculate the depth of the sample surface and the energy diffusion parameters at each depth, and it can achieve the image deblurring of a continuously changing surface and the global deblurring of multiple samples in a wide field of view.

Modeling Point Spread Function in Fluorescence Microscopy With a Sparse Gaussian Mixture: Tradeoff Between Accuracy and Efficiency

Deblurring is a fundamental inverse problem in bioimaging. It requires modeling the point spread function (PSF), which captures the optical distortions entailed by the image formation process. The PSF limits the spatial resolution attainable for a given microscope. However, recent applications require a higher resolution and have prompted the development of super-resolution techniques to achieve sub-pixel accuracy. This requirement restricts the class of suitable PSF models to analog ones. In addition, deblurring is computationally intensive, hence further requiring computationally efficient models. A custom candidate fitting both the requirements is the Gaussian model. However, this model cannot capture the rich tail structures found in both the theoretical and empirical PSFs. In this paper, we aim at improving the reconstruction accuracy beyond the Gaussian model, while preserving its computational efficiency. We introduce a new class of analog PSF models based on the Gaussian mixtures. The number of Gaussian kernels controls both the modeling accuracy and the computational efficiency of the model: the lower the number of kernels, the lower the accuracy and the higher the efficiency. To explore the accuracy-efficiency tradeoff, we propose a variational formulation of the PSF calibration problem, where a convex sparsity-inducing penalty on the number of Gaussian kernels allows trading accuracy for efficiency. We derive an efficient algorithm based on a fully split formulation of alternating split Bregman. We assess our framework on synthetic and real data, and demonstrate a better reconstruction accuracy in both geometry and photometry in point source localization-a fundamental inverse problem in fluorescence microscopy.

Single-image structured illumination using Hilbert transform demodulation

Structured illumination microscopy (SIM) achieves sectioning at depth by removing undesired light from out-of-focus planes within a specimen. However, it generally requires at least three modulated images with discrete phase shifts of 0, 120, and 240 deg to produce sectioning. Using a Hilbert transform demodulation, it is possible to produce both sectioning and depth information relative to a reference plane (i.e., a coverslip) using only a single image. The specimen is modulated at a known frequency, and the unmodulated portion of the image is estimated. These two components are used to provide a high-quality sectioned image containing both axial and lateral information of an object. The sectioning resolution with a single image is on par with that of a control three-image SIM. We are also able to show that when used with three images of discrete phase, this method produces better contrast within a turbid media than the traditional SIM technique. Because the traditional SIM requires alignment of three different phases, small differences in optical path length can introduce strong artifacts. Using the single-image technique removes this dependency, greatly improving sectioning in turbid media. Multiple targets with various depths and opaqueness are considered, including human skin in vivo, demonstrating a quick and useful way to provide noninvasive sectioning in real time.

Depth-variant deconvolution of 3D widefield fluorescence microscopy using the penalized maximum likelihood estimation method

We investigated the deconvolution of 3D widefield fluorescence microscopy using the penalized maximum likelihood estimation method and the depth-variant point spread function (DV-PSF). We build the DV-PSF by fitting a parameterized theoretical PSF model to an experimental microbead image. On the basis of the constructed DV-PSF, we restore the 3D widefield microscopy by minimizing an objective function consisting of a negative Poisson likelihood function and a total variation regularization function. In simulations and experiments, the proposed method showed better performance than existing methods.

Methods for imaging thick specimens: confocal microscopy, deconvolution, and structured illumination

When a thick specimen is viewed through a conventional microscope, one sees the sum of a sharp image of an in-focus region plus blurred images of all of the out-of-focus regions. High background, scattering, and aberrations are all problems when viewing thick specimens. Several methods are available to deal with these problems in living samples. These methods can be grouped into three classes: primarily optical (e.g., confocal microscopy, multiphoton microscopy), primarily computational (e.g., deconvolution techniques), and mixed (e.g., structured illumination) approaches. This article describes these techniques, which make it possible to see details within thick specimens (e.g., the interiors of cells within living tissue) by optical sectioning, without the artifacts associated with physically sectioning the specimen.

Point-spread function engineering to reduce the impact of spherical aberration on 3D computational fluorescence microscopy imaging

Wavefront encoding (WFE) with different cubic phase mask designs was investigated in engineering 3D point-spread functions (PSF) to reduce their sensitivity to depth-induced spherical aberration (SA) which affects computational complexity in 3D microscopy imaging. The sensitivity of WFE-PSFs to defocus and to SA was evaluated as a function of phase mask parameters using mean-square-error metrics to facilitate the selection of mask designs for extended-depth-of-field (EDOF) microscopy and for computational optical sectioning microscopy (COSM). Further studies on pupil phase contribution and simulated WFE-microscope images evaluated the engineered PSFs and demonstrated SA insensitivity over sample depths of 30 μm. Despite its low sensitivity to SA, the successful WFE design for COSM maintains a high sensitivity to defocus as it is desired for optical sectioning.

Realistic 3D coherent transfer function inverse filtering of complex fields

We present a novel technique for three-dimensional (3D) image processing of complex fields. It consists in inverting the coherent image formation by filtering the complex spectrum with a realistic 3D coherent transfer function (CTF) of a high-NA digital holographic microscope. By combining scattering theory and signal processing, the method is demonstrated to yield the reconstruction of a scattering object field. Experimental reconstructions in phase and amplitude are presented under non-design imaging conditions. The suggested technique is best suited for an implementation in high-resolution diffraction tomography based on sample or illumination rotation.

Blind deconvolution for thin-layered confocal imaging

We propose an alternate minimization algorithm for estimating the point-spread function (PSF) of a confocal laser scanning microscope and the specimen fluorescence distribution. A three-dimensional separable Gaussian model is used to restrict the PSF solution space and a constraint on the specimen is used so as to favor the stabilization and convergence of the algorithm. The results obtained from the simulation show that the PSF can be estimated to a high degree of accuracy, and those on real data show better deconvolution as compared to a full theoretical PSF model.

Effect of aberration on height calibration in three-dimensional localization-based microscopy and particle tracking

Many single-particle tracking and localization-based superresolution imaging techniques use the width of a single lateral fluorescence image to estimate a molecule's axial position. This determination is often done by use of a calibration data set derived from a source adhered to a glass-water interface. However, for sources deeper in solution, aberrations will change the relationship between the image width and the axial position. We analyzed the depth-varying point spread function of a high numerical aperture objective near an index of refraction mismatch at the water-glass interface using an optical trap. In addition to the well-known focal shift, spherical aberrations cause up to 30% relative systematic error in axial position estimation. This effect is nonuniform in depth, and we find that, although molecules below the focal plane are correctly localized, molecules deeper than the focal plane are found to be lower than their actual positions.

High-resolution solid modeling of biological samples imaged with 3D fluorescence microscopy

Optical-sectioning, digital fluorescence microscopy provides images representing temporally- and spatially-resolved molecular-scale details of the substructures of living cells. To render such images into solid models for further computational analyses, we have developed an integrated system of image acquisition, processing, and rendering, which includes a new empirical technique to correct for axial distortions inherent in fluorescence microscopy due to refractive index mismatches between microscope objective immersion medium, coverslip glass, and water. This system takes advantage of the capabilities of ultra-high numerical aperture objectives (e.g. total internal reflection fluorescence microscopy) and enables faithful three-dimensional rendering of living cells into solid models amenable to further computational analysis. An example of solid modeling of bovine aortic endothelial cells and their nuclei is presented. Since many cellular level events are temporally and spatially confined, such integrated image acquisition, processing, rendering, and computational analysis, will enable, in silico, the generation of new computational models for cell mechanics and signaling.

Optical sectioning microscopy

Confocal scanning microscopy, a form of optical sectioning microscopy, has radically transformed optical imaging in biology. These devices provide a powerful means to eliminate from images the background caused by out-of-focus light and scatter. Confocal techniques can also improve the resolution of a light microscope image beyond what is achievable with widefield fluorescence microscopy. The quality of the images obtained, however, depends on the user's familiarity with the optical and fluorescence concepts that underlie this approach. We describe the core concepts of confocal microscopes and important variables that adversely affect confocal images. We also discuss data-processing methods for confocal microscopy and computational optical sectioning techniques that can perform optical sectioning without a confocal microscope.

Noise suppression of point spread functions and its influence on deconvolution of three-dimensional fluorescence microscopy image sets

The point spread function (PSF) is of central importance in the image restoration of three-dimensional image sets acquired by an epifluorescent microscope. Even though it is well known that an experimental PSF is typically more accurate than a theoretical one, the noise content of the experimental PSF is often an obstacle to its use in deconvolution algorithms. In this paper we apply a recently introduced noise suppression method to achieve an effective noise reduction in experimental PSFs. We show with both simulated and experimental three-dimensional image sets that a PSF that is smoothed with this method leads to a significant improvement in the performance of deconvolution algorithms, such as the regularized least-squares algorithm and the accelerated Richardson-Lucy algorithm.

Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy

We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maximization (EM) formalism by using a new approximate model for depth-varying image formation for optical sectioning microscopy. This new strata-based model incorporates spherical aberration that worsens as the microscope is focused deeper under the cover slip and is the result of the refractive-index mismatch between the immersion medium and the mounting medium of the specimen. Images of a specimen with known geometry and refractive index show that the model captures the main features of the image. We analyze the performance of the depth-variant EM algorithm with simulations, which show that the algorithm can compensate for image degradation changing with depth.

Three-dimensional capillary geometry in gut tissue

Accurate characterization of capillary geometry is of the utmost importance for physiological tissue studies such as oxygen transport. We show that 3D microscopy can be used to measure tissue capillary geometry both in normal and disease states. We imaged fluorescently labeled gut mucosa capillary beds of three control rats and three rats 4 hours after i.p. injection of 9 mg/kg endotoxin. We used serial optical sectioning microscopy coupled with deconvolution to reconstruct 3D capillary geometry. Theoretical point spread functions accounting for depth into the specimen resulted in better reconstructions than experimentally measured point spread functions. We next derived the distribution of the shortest distances to the nearest capillary from all extravascular tissue voxels. In normal rats the shortest-distance distributions were remarkably constant despite widely varying capillary geometry. Furthermore, the mean of the shortest-distance distributions increased significantly for endotoxemic rats (4.8+/-0.4 microm) compared to controls (4.3+/-0.3 microm, P<0.05). Hence, serial sectioning microscopy provides an accurate venue for measuring physiologically relevant 3D capillary structure.

Structure of silica in matt water-based lacquer

A model for the structure of silica matting agent in water-based lacquers is presented. It is assumed that, during film formation, the air that lies between the silica particles in the dry powder is replaced by polymer. At a critical concentration this leads to a silica structure similar to that of the dry powder. We assume the bulk volume occupied by the dry silica powder (silica and air) equals the dried lacquer film (polymer, silica, and residual air). Since the silica structure in the dry powder percolates, the silica in the dried lacquer is tested for percolation. Experimentally, a percolation threshold is found close to the critical concentration predicted by the model. Two further silica structures are also seen under different conditions. At low silica concentrations, the silica particles are suspended in the lacquer matrix and isolated. Above the percolation threshold, where the bulk volume of the dry silica exceeds that of the film, the silica structure can undergo collapse. This is caused by volume reduction in the lacquer as water evaporates. The lacquer is imaged with confocal laser scanning microscopy, to produce three-dimensional images of the bulk of the 50-microm film. Resolution is enhanced with image reconstruction via deconvolution. Computational image analysis is then used to investigate the structure quantitatively.

Validation of image processing tools for 3-D fluorescence microscopy

3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented.

Artefacts in restored images due to intensity loss in three-dimensional fluorescence microscopy

Computational algorithms for three-dimensional deconvolution have proven successful in reducing blurring and improving the resolution of fluorescence microscopic images. However, discrepancies between the imaging conditions and the models on which such deconvolution algorithms are based may lead to artefacts and/or distortions in the images restored by application of the algorithms. In this paper, artefacts associated with a decrease of fluorescence intensity with time or slice in three-dimensional wide-field images are demonstrated using simulated images. Loss of intensity, whether due to photobleaching or other factors, leads to artefacts in the form of bands or stripes in the restored images. An empirical method for correcting the intensity losses in wide-field images has been implemented and used to correct biological images. This method is based on fitting a decreasing function to the slice intensity curve computed by summing all pixel values in each slice. The fitted curve is then used for the calculation of correction factors for each slice.

Fast maximum-likelihood image-restoration algorithms for three-dimensional fluorescence microscopy

We have evaluated three constrained, iterative restoration algorithms to find a fast, reliable algorithm for maximum-likelihood estimation of fluorescence microscopic images. Two algorithms used a Gaussian approximation to Poisson statistics, with variances computed assuming Poisson noise for the images. The third method used Csiszar's information-divergence (I-divergence) discrepancy measure. Each method included a nonnegativity constraint and a penalty term for regularization; optimization was performed with a conjugate gradient method. Performance of the methods was analyzed with simulated as well as biological images and the results compared with those obtained with the expectation-maximization-maximum-likelihood (EM-ML) algorithm. The I-divergence-based algorithm converged fastest and produced images similar to those restored by EM-ML as measured by several metrics. For a noiseless simulated specimen, the number of iterations required for the EM-ML method to reach a given log-likelihood value was approximately the square of the number required for the I-divergence-based method to reach the same value.

Three-dimensional in vivo analysis of Dictyostelium mounds reveals directional sorting of prestalk cells and defines a role for the myosin II regulatory light chain in prestalk cell sorting and tip protrusion

During cell sorting in Dictyostelium, we observed that GFP-tagged prestalk cells (ecmAO-expressing cells) moved independently and directionally to form a cluster. This is consistent with a chemotaxis model for cell sorting (and not differential adhesion) in which a long-range signal attracts many of the prestalk cells to the site of cluster formation. Surprisingly, the ecmAO prestalk cluster that we observed was initially found at a random location within the mound of this Ax3 strain, defining an intermediate sorting stage not widely reported in Dictyostelium. The cluster then moved en masse to the top of the mound to produce the classic, apical pattern of ecmAO prestalk cells. Migration of the cluster was also directional, suggesting the presence of another long-range guidance cue. Once at the mound apex, the cluster continued moving upward leading to protrusion of the mound's tip. To investigate the role of the cluster in tip protrusion, we examined ecmAO prestalk-cell sorting in a myosin II regulatory light chain (RLC) null in which tips fail to form. In RLC-null mounds, ecmAO prestalk cells formed an initial cluster that began to move to the mound apex, but then arrested as a vertical column that extended from the mound's apex to its base. Mixing experiments with wild-type cells demonstrated that the RLC-null ecmAO prestalk-cell defect is cell autonomous. These observations define a specific mechanism for myosin's function in tip formation, namely a mechanical role in the upward movement of the ecmAO prestalk cluster. The wild-type data demonstrate that cell sorting can occur in two steps, suggesting that, in this Ax3 strain, spatially and temporally distinct cues may guide prestalk cells first to an initial cluster and then later to the tip.

Digital analysis of light microscope immunofluorescence: high-resolution co-localization of synaptic proteins in cultured neurons

A protocol is presented for determining the subcellular distribution of fluorescently labeled proteins in neurons using deconvolved images gathered with a wide-field microscope. The protocol includes optimal settings for the numerical algorithm used to deconvolve the images and an objective method for thresholding the deconvolved images to retain only high-intensity, specific labeling. The effectiveness of the protocol is demonstrated using a fluorescent antibody stain directed towards the alpha1 subunit of the GABA(A) receptor in cultured neurons. We also show, using an antibody against the presynaptic vesicular protein synaptophysin, that the technique can detect presumptive regions of synaptic contact between neurons. Double-labeling with the anti-alpha1 and anti-synaptophysin antibodies in a cultured neuron reveals regions of both synaptic and non-synaptic alpha1 labeling. Thus, numerical postprocessing of wide-field images can be used to efficiently locate receptor proteins in neurons in relation to functionally important structures. This confocal-like functionality is attained without the excessive bleaching and phototoxicity associated with the intense laser excitation light used in confocal techniques.

Determination of intracellular organelles implicated in daunorubicin cytoplasmic sequestration in multidrug-resistant MCF-7 cells using fluorescence microscopy image analysis

BACKGROUND

Anthracycline resistance is known to be mediated by P-glycoprotein (P-gp) or multidrug-resistance related protein (MRP) as well as intracellular sequestration of drugs.

METHODS

The resistance phenotype of doxorubicin-selected MCF-7(DXR) human breast adenocarcinoma cell line was characterized by cellular and nuclear daunorubicin efflux, P-gp and MRP expression and apoptosis induction. Daunorubicin sequestration was investigated through organelle markers (lysosomes, endoplasmic reticulum and Golgi apparatus) and daunorubicin co-localization by dual-color image analysis fluorescence microscopy using high numerical aperture objective lenses to achieve the smallest field depth and the best lateral resolution. Signal to noise and specificity ratios were optimized for daunorubicin and organelle fluorescent probes labeling.

RESULTS

An original image analysis procedure was developed to investigate daunorubicin and organelles co-localization. The reliability of the image analysis was controlled through chromatic shift and intensity linearity measurement using calibrated microbeads. The main contribution (65%) of Golgi vesicles in daunorubicin sequestration was demonstrated. Although no rational relationship could be established between daunorubicin sequestration and apoptosis induction, no apoptosis was observed in MCF-7(DXR) cells.

CONCLUSIONS

In addition to P-glycoprotein mediated drug efflux and without MRP overexpression, MCF-7(DXR) daunorubicin resistance phenotype involves drug sequestration within intracellular vesicles identified as Golgi vesicles and resistance to apoptosis induction.

Three-dimensional imaging by deconvolution microscopy

Deconvolution is a computational method used to reduce out-of-focus fluorescence in three-dimensional (3D) microscope images. It can be applied in principle to any type of microscope image but has most often been used to improve images from conventional fluorescence microscopes. Compared to other forms of 3D light microscopy, like confocal microscopy, the advantage of deconvolution microscopy is that it can be accomplished at very low light levels, thus enabling multiple focal-plane imaging of light-sensitive living specimens over long time periods. Here we discuss the principles of deconvolution microscopy, describe different computational approaches for deconvolution, and discuss interpretation of deconvolved images with a particular emphasis on what artifacts may arise.

Parametric blind deconvolution: a robust method for the simultaneous estimation of image and blur

Blind-deconvolution microscopy, the simultaneous estimation of the specimen function and the point-spread function (PSF) of the microscope, is an underdetermined problem with nonunique solutions that are usually avoided by enforcing constraints on the specimen function and the PSF. We derived a maximum-likelihood-based method for blind deconvolution in which we assume a mathematical model for the PSF that depends on a small number of parameters (e.g., less than 20). The algorithm then estimates the unknown parameters together with the specimen function. The mathematical model ensures that all the constraints of the PSF are satisfied, and the maximum-likelihood approach ensures that the specimen is nonnegative. The method successfully estimates the PSF and removes out-of-focus blur. The PSF estimation is robust to aberrations in the PSF and to noise in the image.

In vivo observations of myosin II dynamics support a role in rear retraction

To investigate myosin II function in cell movement within a cell mass, we imaged green fluorescent protein-myosin heavy chain (GFP-MHC) cells moving within the tight mound of Dictyostelium discoideum. In the posterior cortex of cells undergoing rotational motion around the center of the mound, GFP-MHC cyclically formed a "C," which converted to a spot as the cell retracted its rear. Consistent with an important role for myosin in rotation, cells failed to rotate when they lacked the myosin II heavy chain (MHC-) or when they contained predominantly monomeric myosin II (3xAsp). In cells lacking the myosin II regulatory light chain (RLC-), rotation was impaired and eventually ceased. These rotational defects reflect a mechanical problem in the 3xAsp and RLC- cells, because these mutants exhibited proper rotational guidance cues. MHC- cells exhibited disorganized and erratic rotational guidance cues, suggesting a requirement for the MHC in organizing these signals. However, the MHC- cells also exhibited mechanical defects in rotation, because they still moved aberrantly when seeded into wild-type mounds with proper rotational guidance cues. The mechanical defects in rotation may be mediated by the C-to-spot, because RLC- cells exhibited a defective C-to-spot, including a slower C-to-spot transition, consistent with this mutant's slower rotational velocity.

Superresolution and convergence properties of the expectation-maximization algorithm for maximum-likelihood deconvolution of incoherent images

Computational optical-sectioning microscopy with a nonconfocal microscope is fundamentally limited because the optical transfer function, the Fourier transform of the point-spread function, is exactly zero over a conic region of the spatial-frequency domain. Because of this missing cone of optical information, images are potentially artifactual. To overcome this limitation, superresolution, in the sense of band extrapolation, is necessary. I present a frequency-domain analysis of the expectation-maximization algorithm for maximum-likelihood image estimation that shows how the algorithm achieves this band extrapolation. This analysis gives the theoretical absolute bandwidth of the restored image; however, this absolute value may not be realistic in many cases. Then a second analysis is presented that assumes a Gaussian point-spread function and a specimen function and shows more realistic behavior of the algorithm and demonstrates some of its properties. Experimental results on the superresolving capability of the algorithm are also presented.

Assembly and function of the actin cytoskeleton of yeast: relationships between cables and patches

Actin in eukaryotic cells is found in different pools, with filaments being organized into a variety of supramolecular assemblies. To investigate the assembly and functional relationships between different parts of the actin cytoskeleton in one cell, we studied the morphology and dynamics of cables and patches in yeast. The fine structure of actin cables and the manner in which cables disassemble support a model in which cables are composed of a number of overlapping actin filaments. No evidence for intrinsic polarity of cables was found. To investigate to what extent different parts of the actin cytoskeleton depend on each other, we looked for relationships between cables and patches. Patches and cables were often associated, and their polarized distributions were highly correlated. Therefore, patches and cables do appear to depend on each other for assembly and function. Many cell types show rearrangements of the actin cytoskeleton, which can occur via assembly or movement of actin filaments. In our studies, dramatic changes in actin polarization did not include changes in filamentous actin. In addition, the concentration of actin patches was relatively constant as cells grew. Therefore, cells do not have bursts of activity in which new parts of the actin cytoskeleton are created.

Imaging of spheres with the confocal scanning optical microscope

The scalar theory of image formation for a strongly spherical object in ref lection confocal optical microscopy is considered. The image contrast is derived from the far-field scattering amplitude. Experimentally obtained images of the sphere are seen to be in good agreement with the theoretical prediction.

Covisualization by computational optical-sectioning microscopy of integrin and associated proteins at the cell membrane of living onion protoplasts

Using higher-resolution wide-field computational optical-sectioning fluorescence microscopy, the distribution of antigens recognized by antibodies against animal beta 1 integrin, fibronectin, and vitronectin has been visualized at the outer surface of enzymatically protoplasted onion epidermis cells and in depectinated cell wall fragments. On the protoplast all three antigens are colocalized in an array of small spots, as seen in raw images, in Gaussian filtered images, and in images restored by two different algorithms. Fibronectin and vitronectin but not beta 1 integrin antigenicities colocalize as puncta in comparably prepared and processed images of the wall fragments. Several control visualizations suggest considerable specifity of antibody recognition. Affinity purification of onion cell extract with the same anti-integrin used for visualization has yielded protein that separates in SDS-PAGE into two bands of about 105-110 and 115-125 kDa. These bands are again recognized by the visualization antibody, which was raised against the extracellular domain of chicken beta 1 integrin, and are also recognized by an antibody against the intracellular domain of chicken beta 1 integrin. Because beta 1 integrin is a key protein in numerous animal adhesion sites, it appears that the punctate distribution of this protein in the cell membranes of onion epidermis represents the adhesion sites long known to occur in cells of this tissue. Because vitronectin and fibronection are matrix proteins that bind to integrin in animals, the punctate occurrence of antigenically similar proteins both in the wall (matrix) and on enzymatically prepared protoplasts reinforces the concept that onion cells have adhesion sites with some similarity to certain kinds of adhesion sites in animals.