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This correlated multimodality imaging (CMI) approach includes well-established technologies such as Positron Emission Tomography (microPET), Autoradiography, Magnetic Resonance Imaging (microMRI) and Computed Tomography (microCT), and imaging approaches that are more novel in the biomedical setting, such as X-Ray Fluorescence Spectroscopy (microXRF) and High Resolution Episcopic Microscopy (HREM). Although the current pipelines are focused on mural lesions, they would also be beneficial in preclinical and clinical investigations of vascular diseases in general.Correlative microscopy experiments require the co-registration of the image data acquired by different micro-analytical techniques. Major challenges are the potentially very different fields-of-view and resolutions as well as the multi-modality of the data. To provide microscopists with an easy-to-use software for two-dimensional image co-registration we have developed Correlia, an open source software based on ImageJa/Fiji,b which is fully tailored for the registration of multi-modal microscopy data. It can handle data-sets of in principle arbitrary extent and uses classical approaches, i.e., rigid registration tools or B-spline based deformation models for the correction of both, global and local misalignments, such that a fast registration output is provided. Here we describe some of the basics of Correlia focusing on its application firstly, registration workflows are outlined on artificial data. In the second part these recipes are applied to register correlative data acquired on an algal biofilm and a soil sample.In recent years new methodologies and workflow pipelines for acquiring correlated fluorescence microscopy and volume electron microscopy datasets have been extensively described and made accessible to users of different levels. Post-acquisition image processing, and particularly correlation of the optical and electron data in a single integrated three-dimensional framework can be key for extracting valuable information, especially when imaging large sample volumes such as whole cells or tissues. These tasks remain challenging and are often rate-limiting to most users. Here we provide a step-by-step guide to image processing and manual correlation using ImageJ and Amira software of a confocal microscopy stack and a focused ion beam/scanning electron microscopy (FIB/SEM) tomogram acquired using a correlative pipeline. These previously published datasets capture a highly transient invasion event by the bacterium Shigella flexneri infecting an epithelial cell grown in culture, and are made available here in their pre-processed form for readers who wish to gain hands-on experience in image processing and correlation using existing data. In this guide we describe a simple protocol for correlation based on internal sample features clearly visible by both fluorescence and electron microscopy, which is normally sufficient when correlating standard fluorescence microscopy stacks with FIB/SEM data. While the guide describes the treatment of specific datasets, it is applicable to a wide variety of samples and different microscopy approaches that require basic correlation and visualization of two or more datasets in a single integrated framework.Correlative light and electron microscopy (CLEM) entails a group of multimodal imaging techniques that are combined to pinpoint to the location of fluorescently labeled molecules in the context of their ultrastructural cellular environment. Here we describe a detailed workflow for STORM-CLEM, in which STochastic Optical Reconstruction Microscopy (STORM), an optical super-resolution technique, is correlated with transmission electron microscopy (TEM). ARS853 purchase This protocol has the advantage that both imaging modalities have resolution at the nanoscale, bringing higher synergies on the information obtained. The sample is prepared according to the Tokuyasu method followed by click-chemistry labeling and STORM imaging. Then, after heavy metal staining, electron microscopy imaging is performed followed by correlation of the two images. The case study presented here is on intracellular pathogens, but the protocol is versatile and could potentially be applied to many types of samples.In situ cryo-electron tomography of cryo-focused ion beam (cryo-FIB) milled cells enables the study of cellular organelles in unperturbed conditions and close to the molecular resolution. However, due to the crowdedness of the cellular environment, the identification of individual macromolecular complexes either on organelles or inside the cytosol in cryo-electron tomograms is challenging. Cryo-correlative light and electron microscopy (cryo-CLEM) employs a fluorescently labeled feature of interest imaged by cryo-light microscopy that is correlated to cryo-electron microscopy maps of cryo-FIB milled lamellae using correlation markers discernable by both imaging methods. Here, we provide a protocol for a post-correlation on-lamella cryo-CLEM approach for localization of fluorescently labeled organelles of interest in cryo-lamellae after cryo-FIB milling and tomography of adherent plunge frozen cells.The combination of super-resolution fluorescence microscopy and electron microscopy at ambient temperatures has become an established technique and a broad variety of modalities are now available to the cell biology community. In contrast, correlative cryogenic super-resolution fluorescence and electron microscopy (super-resolution cryo-CLEM) is just emerging. Aside from technical challenges, one of the major issues is the risk of devitrification of the specimen caused by the laser intensities required for super-resolution imaging. Cryo-SOFI (cryogenic super-resolution optical fluctuation imaging) allows the reconstruction of super-resolution images at particularly low laser intensities. It is fully compatible with the standard sample preparation for cryogenic electron microscopy (cryo-EM) and fairly easy to implement in any standard cryogenic fluorescence microscope.Rapidly changing features in an intact biological sample are challenging to efficiently trap and image by conventional electron microscopy (EM). For example, the model organism C. elegans is widely used to study embryonic development and differentiation, yet the fast kinetics of cell division makes the targeting of specific developmental stages for ultrastructural study difficult. We set out to image the condensed metaphase chromosomes of an early embryo in the intact worm in 3-D. To achieve this, one must capture this transient structure, then locate and subsequently image the corresponding volume by EM in the appropriate context of the organism, all while minimizing a variety of artifacts. In this methodological advance, we report on the high-pressure freezing of spatially constrained whole C. elegans hermaphrodites in a combination of cryoprotectants to identify embryonic cells in metaphase by in situ cryo-fluorescence microscopy. The screened worms were then freeze substituted, resin embedded and further prepared such that the targeted cells were successfully located and imaged by focused ion beam scanning electron microscopy (FIB-SEM).