| Literature DB >> 34476818 |
Christopher J Guerin1, Saskia Lippens1.
Abstract
Correlative light and electron microscopy is a valuable tool to image samples across resolution scales and link data on structure and function. While studies using this technique have been available since the 1960s, recent developments have enabled applying these workflows to large volumes of cells and tissues. Much of the development in this area has been facilitated through the collaborative efforts of microscopists and commercial companies to bring the methods, hardware and image processing technologies needed into laboratories and core imaging facilities. This is a prime example of how what was once a niche area can be brought into the mainstream of microscopy by the efforts of imaging pioneers who push the boundaries of possibility.Entities:
Keywords: correlative light and electron microscopy; correlative volume electron microscopy; electron microscopy; volume electron microscopy
Year: 2021 PMID: 34476818 PMCID: PMC9291772 DOI: 10.1111/jmi.13056
Source DB: PubMed Journal: J Microsc ISSN: 0022-2720 Impact factor: 1.952
FIGURE 1Possible workflows for vCLEM. A number of light microscopic imaging techniques can be incorporated into a vCLEM experiment with the aim of identifying particular structures of interest usually by fluorescently staining a protein or structure of interest. Intermediate imaging steps using X‐Ray microscopy or micro CT can further assist in identifying a region of interest (ROI) to be targeted in the electron microscope. Typical vEM methods used would be in chamber sectioning either with a diamond knife (SBF‐SEM) or a focused ion beam (FIB‐SEM) or external sectioning of a resin block followed by serial imaging (AT) of the resulting sections. Supplemental imaging techniques such as EDX or mass spectrometry can be used to provide elemental or protein signatures. Finally, the LM and vEM images and any associated data are compiled in the registered sections and visualisation is carried out via computer modelling of the data stack