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Guided-deconvolution for correlative light and electron microscopy.
Ma, Fengjiao; Kaufmann, Rainer; Sedzicki, Jaroslaw; Cseresnyés, Zoltán; Dehio, Christoph; Hoeppener, Stephanie; Figge, Marc Thilo; Heintzmann, Rainer.
Affiliation
  • Ma F; Institute of Physical Chemistry and Abbe Center of Photonics, University of Jena, Jena, Thuringia, Germany.
  • Kaufmann R; Leibniz Institute of Photonic Technology, Jena, Thuringia, Germany.
  • Sedzicki J; Jena Center for Soft Matter, University of Jena, Jena, Thuringia, Germany.
  • Cseresnyés Z; Centre for Structural Systems Biology, Hamburg, Germany.
  • Dehio C; Department of Physics, University of Hamburg, Hamburg, Germany.
  • Hoeppener S; Biozentrum, University of Basel, Basel, Switzerland.
  • Figge MT; Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Jena, Thuringia, Germany.
  • Heintzmann R; Biozentrum, University of Basel, Basel, Switzerland.
PLoS One ; 18(3): e0282803, 2023.
Article in En | MEDLINE | ID: mdl-36893111
ABSTRACT
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Organelles Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2023 Document type: Article Affiliation country: Alemania

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Organelles Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2023 Document type: Article Affiliation country: Alemania