We reasoned that for imaging tissue and cells in AT there is an unmet need to rapidly and reliably identify similar structures in regions of interest (ROIs) in consecutive sections independent of fluorescence to facilitate 3D imaging of specific structures. Additionally, the fluorescence signal of a reporter is required as the basis for navigation to specific areas of interest. Generally, software solutions for correlating images using AT are not designed for iLEMs, and therefore, integrating acquisition workflows has not been explored. However, so far, correlative AT using an iLEM system has not been widely adopted. Given that on iLEMs, typical ultrathin sections are imaged, these devices are the ideal candidate for correlative AT. Correlation is done in the plane of each section, limiting the correlation problem to 2D and reducing any inaccuracy in Z-direction to the thickness of the section and even beyond the limit of resolution of the LM in Z-direction. ILEM imaging datasets can be pre-aligned using, for example, cathodoluminescence on the nanometer scale. For AT, the use of a high-resolution iLEM that uses diffraction-limited oil immersion lenses (with a resolution of about 200 nm in the x,y range and that can even be used for super-resolution ) combined with a high-resolution SEM seems the most promising for bridging the gap between LM and EM imaging smoothly. Different realizations of iLEMs have been developed, including transmitted and scanning electron microscopes and setups dedicated towards 3D imaging. Integrated light and electron microscopes, so-called iLEMs, have been designed to overcome the problem of alignment between the two modalities for imaging in both LM and EM. However, a key challenge is the overlaying of LM and EM outputs to produce the final correlated image, as the resolution gap between LM and EM and different distortions in the two techniques prevent straightforward automation. Ĭorrelative light and electron microscopy (CLEM) combines the specificity and flexibility of light microscopy (LM) with the ultrastructural context and comprehensive information available via EM. 3D EM imaging has been achieved in a number of ways, including so-called array tomography (AT) where serial sections are imaged with an SEM. Our method facilitates tracing and reconstructing cellular structures over multiple sections, is targeted at high resolution ILEMs, and can be integrated into existing devices, both commercial and custom-built systems.Īdvances in 3D electron microscopy (EM) imaging and correlative and multimodal imaging have revolutionized life science imaging. We provide a proof of concept of our approach and the developed software tools using both Golgi neuronal impregnation staining and fluorescently labeled protein condensates in cells. With minimal user interaction, this enables autonomous and speedy acquisition of regions containing cells and cellular organelles of interest correlated across different magnifications for LM and EM modalities, providing a more efficient way to obtain 3D images. Our workflow is based on the detection of section boundaries on an initial transmitted light acquisition that serves as a reference space to compensate for changes in shape between sections, and we apply a stepwise refinement of localizations as the magnification increases from LM to EM. We use a targeted approach that allows imaging specific tissue features, like organelles, cell processes, and nuclei at different scales to enable fast, directly correlated in situ AT using an integrated light and electron microscope (iLEM-AT). Here, we report a workflow to automate navigation between regions of interest. Integrated light and electron microscopes (iLEMs) offer the possibility to provide well-correlated images and may pose an ideal solution for correlative AT. However, the correlation between modalities can be a challenge and delineating specific regions of interest in consecutive sections can be time-consuming. AT can be carried out in a correlative way, combing light and electron microscopy (LM, EM) techniques. Array tomography (AT) is a high-resolution imaging method to resolve fine details at the organelle level and has the advantage that it can provide 3D volumes to show the tissue context.
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