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Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

ABSTRACT: BACKGROUND: Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture. METHODS: Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale in silico image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM). RESULTS: We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates. CONCLUSION: The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes.

SUBMITTER: Flaberg E

PROVIDER: S-EPMC2515298 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

Flaberg Emilie E Sabelström Per P Strandh Christer C Szekely Laszlo L

BMC medical imaging 20080716

<h4>Background</h4>Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture.<h4>Methods</h4>Using the combination of microlens enhanced Nipkow ...[more]

PMID: 18627634

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Project description:BACKGROUND:Phosphorylated histone H2AX, also known as ?H2AX, forms ?m-sized nuclear foci at the sites of DNA double-strand breaks (DSBs) induced by ionizing radiation and other agents. Due to their specificity and sensitivity, ?H2AX immunoassays have become the gold standard for studying DSB induction and repair. One of these assays relies on the immunofluorescent staining of ?H2AX followed by microscopic imaging and foci counting. During the last years, semi- and fully automated image analysis, capable of fast detection and quantification of ?H2AX foci in large datasets of fluorescence images, are gradually replacing the traditional method of manual foci counting. A major drawback of the non-commercial software for foci counting (available so far) is that they are restricted to 2D-image data. In practice, these algorithms are useful for counting the foci located close to the midsection plane of the nucleus, while the out-of-plane foci are neglected. RESULTS:To overcome the limitations of 2D foci counting, we present a freely available ImageJ-based plugin (FocAn) for automated 3D analysis of ?H2AX foci in z-image stacks acquired by confocal fluorescence microscopy. The image-stack processing algorithm implemented in FocAn is capable of automatic 3D recognition of individual cell nuclei and ?H2AX foci, as well as evaluation of the total foci number per cell nucleus. The FocAn algorithm consists of two parts: nucleus identification and foci detection, each employing specific sequences of auto local thresholding in combination with watershed segmentation techniques. We validated the FocAn algorithm using fluorescence-labeled ?H2AX in two glioblastoma cell lines, irradiated with 2?Gy and given up to 24?h post-irradiation for repair. We found that the data obtained with FocAn agreed well with those obtained with an already available software (FoCo) and manual counting. Moreover, FocAn was capable of identifying overlapping foci in 3D space, which ensured accurate foci counting even at high DSB density of up to ~?200 DSB/nucleus. CONCLUSIONS:FocAn is freely available an open-source 3D foci analyzer. The user-friendly algorithm FocAn requires little supervision and can automatically count the amount of DNA-DSBs, i.e. fluorescence-labeled ?H2AX foci, in 3D image stacks acquired by laser-scanning microscopes without additional nuclei staining.

Dataset Information

Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

Publications

Extended Field Laser Confocal Microscopy (EFLCM): combining automated Gigapixel image capture with in silico virtual microscopy.

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