Institute of Physical Chemistry and Abbe Center of Photonics, University of Jena, Jena, Thuringia, Germany.
Leibniz Institute of Photonic Technology, Jena, Thuringia, Germany.
PLoS One. 2023 Mar 9;18(3):e0282803. doi: 10.1371/journal.pone.0282803. eCollection 2023.
Correlative light and electron microscopy is a powerful tool to study the internal structure of cells. It combines the mutual benefit of correlating light (LM) and electron (EM) microscopy information. The EM images only contain contrast information. Therefore, some of the detailed structures cannot be specified from these images alone, especially when different cell organelle are contacted. However, the classical approach of overlaying LM onto EM images to assign functional to structural information is hampered by the large discrepancy in structural detail visible in the LM images. This paper aims at investigating an optimized approach which we call EM-guided deconvolution. This applies to living cells structures before fixation as well as previously fixed sample. It attempts to automatically assign fluorescence-labeled structures to structural details visible in the EM image to bridge the gaps in both resolution and specificity between the two imaging modes. We tested our approach on simulations, correlative data of multi-color beads and previously published data of biological samples.
共聚焦显微镜和电子显微镜是研究细胞内部结构的有力工具。它结合了共聚焦(LM)和电子(EM)显微镜信息的相互益处。EM 图像仅包含对比度信息。因此,仅从这些图像无法单独指定一些详细结构,特别是当不同的细胞细胞器接触时。然而,将 LM 叠加在 EM 图像上来将功能分配给结构信息的经典方法受到 LM 图像中可见的结构细节差异的阻碍。本文旨在研究一种优化的方法,我们称之为 EM 引导去卷积。它适用于固定前和固定后的活细胞结构。它试图自动将荧光标记的结构分配给 EM 图像中可见的结构细节,以弥合两种成像模式在分辨率和特异性方面的差距。我们在模拟、多色珠的相关数据以及以前发表的生物样本数据上测试了我们的方法。