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In this article, we characterize the lateral field distortions in a low numerical aperture and large field-of-view (FOV) fluorescence imaging system. To this end, we study a commercial fluorescence MACROscope setup, which is a zooming microscope. The versatility of this system lies in its ability to image at different zoom ranges, so that sample preparations can be examined in three-dimensions, at cellular, organ and whole body levels. Yet, we found that the imaging system's optics are optimized only for high magnifications where the observed FOV is small. When we studied the point-spread function (PSF) by using fluorescent polystyrene beads as "guide-stars", we noticed that the PSF is spatially varying due to field distortions. This variation was found to be laterally symmetrical and the distortions were found to increase with the distance from the center of the FOV. In this communication, we investigate the idea of using the field at the back focal plane of an optical system for characterizing distortions. As this field is unknown, we develop a theoretical framework to retrieve the amplitude and phase of the field at the back focal pupil plane, from the empirical bead images. By using the retrieved amplitude, we can understand and characterize the underlying cause of these distortions. We also propose a few approaches, before acquisition, to either avoid it or correct it at the optical design level., (© 2012 Optical Society of America)

In this work, we propose a novel method for the regularization of blind deconvolution algorithms. The proposed method employs example-based machine learning techniques for modeling the space of point spread functions. During an iterative blind deconvolution process, a prior term attracts the point spread function estimates to the learned point spread function space. We demonstrate the usage of this regularizer within a Bayesian blind deconvolution framework and also integrate into the latter a method for noise reduction, thus creating a complete blind deconvolution method. The application of the proposed algorithm is demonstrated on synthetic and real-world three-dimensional images acquired by a wide-field fluorescence microscope, where the need for blind deconvolution algorithms is indispensable, yielding excellent results.

Live fluorescence microscopy has the unique capability to probe dynamic processes, linking molecular components and their localization with function. A key goal of microscopy is to increase spatial and temporal resolution while simultaneously permitting identification of multiple specific components. We demonstrate a new microscope platform, OMX, that enables subsecond, multicolor four-dimensional data acquisition and also provides access to subdiffraction structured illumination imaging. Using this platform to image chromosome movement during a complete yeast cell cycle at one 3D image stack per second reveals an unexpected degree of photosensitivity of fluorophore-containing cells. To avoid perturbation of cell division, excitation levels had to be attenuated between 100 and 10,000× below the level normally used for imaging. We show that an image denoising algorithm that exploits redundancy in the image sequence over space and time allows recovery of biological information from the low light level noisy images while maintaining full cell viability with no fading.

Live imaging in cell biology requires three-dimensional data acquisition with the best resolution and signal-to-noise ratio possible. Depth aberrations are a major source of image degradation in three-dimensional microscopy, causing a significant loss of resolution and intensity deep into the sample. These aberrations occur because of the mismatch between the sample refractive index and the immersion medium index. We have built a wide-field fluorescence microscope that incorporates a large-throw deformable mirror to simultaneously focus and correct for depth aberration in three-dimensional imaging. Imaging fluorescent beads in water and glycerol with an oil immersion lens we demonstrate a corrected point spread function and a 2-fold improvement in signal intensity. We apply this new microscope to imaging biological samples, and show sharper images and improved deconvolution.

Background: Cellular processes occur within dynamic and multi-molecular compartments whose characterization requires analysis at high spatio-temporal resolution. Notable examples for such complexes are cell-matrix adhesion sites, consisting of numerous cytoskeletal and signaling proteins. These adhesions are highly variable in their morphology, dynamics, and apparent function, yet their molecular diversity is poorly defined., Methodology/principal Findings: We present here a compositional imaging approach for the analysis and display of multi-component compositions. This methodology is based on microscopy-acquired multicolor data, multi-dimensional clustering of pixels according to their composition similarity and display of the cellular distribution of these composition clusters. We apply this approach for resolving the molecular complexes associated with focal-adhesions, and the time-dependent effects of Rho-kinase inhibition. We show here compositional variations between adhesion sites, as well as ordered variations along the axis of individual focal-adhesions. The multicolor clustering approach also reveals distinct sensitivities of different focal-adhesion-associated complexes to Rho-kinase inhibition., Conclusions/significance: Multicolor compositional imaging resolves "molecular signatures" characteristic to focal-adhesions and related structures, as well as sub-domains within these adhesion sites. This analysis enhances the spatial information with additional "contents-resolved" dimensions. We propose that compositional imaging can serve as a powerful tool for studying complex multi-molecular assemblies in cells and for mapping their distribution at sub-micron resolution.

Background: The cytoskeleton consists of complex arrays of fibers that play indispensable roles in cell structure and function. The cytoskeletal fibers are concertedly involved in numerous cellular processes, including cell adhesion, locomotion, intracellular transport, and cell division. The organization of the cytoskeleton was extensively studied, mainly by immunofluorescence microscopy, yet these studies were mostly qualitative, and a reliable quantitative approach for determining fiber structure and distribution is still missing., Methods: In this study we developed algorithms for filament feature extraction, based on fluorescence microscopy. These algorithms are robust against blurring by slight defocus, high background, and noise, and are applicable to both fixed, immunolabeled cells and live cells expressing fluorescently tagged cytoskeletal proteins. The implemented FiberScore program is used in order to recognize, segment, and quantify various structural parameters of the cytoskeleton, including total fiber-associated fluorescence, as well as fiber length and orientation. Furthermore, these parameters can be determined for different cytoskeletal proteins in the same sample tagged with multiple-fluorescent labels, and the results can be correlated with other cellular parameters., Results: FiberScore was used here for the quantification of simultaneous changes in microtubule and actin filaments induced by the microtubule-disrupting drug nocodazole. Actin filaments, which are reported to respond reciprocally to microtubule disruption, are found to be affected by both immediate and delayed signals., Conclusions: Analysis of the organization of fibers by the FiberScore algorithm allows quantification of the cytoskeletal signature of cells and offers reliable multiparametric functional assays for effects of drugs and other perturbations evaluated on a cell-by-cell basis., (Copyright 2003 Wiley-Liss, Inc.)

Quantitative microscopic imaging of resonance energy transfer (RET) was applied for immunological high resolution proximity mapping of several cytoskeletal components of cell adhesions. To conduct this analysis, a microscopic system was developed, consisting of a highly stable field illuminator, computer-controlled filter wheels for rapid multiple-color imaging and a sensitive, high resolution CCD camera, enabling quantitative data recording and processing. Using this system, we have investigated the spatial inter-relationships and organization of four adhesion-associated proteins, namely vinculin, talin, alpha-actinin and actin. Cultured chick lens cells were double labeled for each of the junctional molecules, using fluorescein- and rhodamine-conjugated antibodies or phalloidin. RET images were acquired with fluorescein excitation and rhodamine emission filter setting, corrected for fluorescein and rhodamine fluorescence, and normalized to the fluorescein image. The results pointed to high local densities of vinculin, talin and F-actin in focal adhesions, manifested by mean RET values of 15%, 12% and 10%, respectively. On the other hand, relatively low values (less than 1%) were observed following double immunofluorescence labeling of the same cells for alpha-actinin. Double indirect labeling for pairs of these four proteins (using fluorophore-conjugated antibodies or phalloidin) resulted in RET values of 5% or lower, except for the pair alpha-actinin and actin, which yielded significantly higher values (13-15%). These results suggest that despite their overlapping staining patterns, at the level of resolution of the light microscope, the plaque proteins vinculin and talin are not homogeneously interspersed at the molecular level but form segregated clusters. alpha-Actinin, on the other hand, does not appear to form such clusters but, rather, closely interacts with actin. We discuss here the conceptual and applicative aspects of RET measurements and the implications of the results on the subcellular molecular organization of adherens-type junctions.