To-date serial block-face scanning electron microscopy (SBF-SEM) dominates as the premier technique for generating three-dimensional (3-D) data of resin-embedded biological samples at an unprecedented resolution and depth volume. Given the relative infancy of the technique, limited literature is currently available regarding the applicability of SBF-SEM for the ultrastructural investigation of tissues that are inherently low in contrast, including hepatic tissue. Such tissues, relative to neural tissue – which has been extensively investigated by means of SBF-SEM – require dedicated SBF-SEM specimen preparation protocols combined with optimised imaging conditions in order to collect large-volume 3-D image data, at appropriate resolution which is devoid of imaging artefacts that are inherent to SEM investigations of uncoated samples.
Therefore, in this study, we provide a comprehensive and rigorous appraisal of different tissue preparation protocols for the large-volume exploration of hepatic architecture at an unparalleled XY and Z resolution. In so doing, we qualitatively and quantitatively validate the use of a novel and time-saving SBF-SEM tissue preparation protocol, which involves the concomitant application of heavy metal fixatives, stains and mordanting agents for the subsequent imaging of contrast-rich SBF-SEM data, 3-D reconstruction and modelling of the hepatic architecture. We further extrapolate large-volume morphometric data relating to key tissue features of the murine liver, including hepatocytes, the hepatic sinusoids and bile canaliculi network (Fig. 1).
Furthermore, we combine our validated SBF-SEM specimen preparation protocol with a correlative light and electron microscopy approach, to combine the respective advantages of confocal scanning laser microscopy and SBF-SEM in order to selectively picture particular subcellular hepatic details in a novel manner. We propose that this correlated multidimensional light and electron imaging approach will allow the study of different liver diseases under relevant experimental tissue models.
Figures:
Figure 1. (A) Reconstructed 3D volume consisting of 610 consecutive images (section thickness = 78 nm). X = 62.24 µm Y = 63.80 µm Z = 47.58 µm. Total volume = 188,935.99 µm3. Binned voxel size = 78 nm3. (B) Two adjacent hepatocytes (gold (mononucleate) and (blue (binucleate)) surrounded by the bile canaliculi (green), which are formed via the apposing plasma membranes of bordering hepatocytes. (C) Model view of the bile canalicular network (green). (D) Model view of the hepatic sinusoids (red). (E) Merged model view of B and C. (F) Merged model view of B, C and D. Magnification = 986×. Scale bar = 20 µm.
To cite this abstract:
Gerald Shami, Delfine Cheng, Minh Huynh, Celien Vreuls, Eddie Wisse, Filip Braet; 3-D EM exploration of the hepatic microarchitecture – lessons learned for large-volume in situ serial sectioning. The 16th European Microscopy Congress, Lyon, France. https://emc-proceedings.com/abstract/3-d-em-exploration-of-the-hepatic-microarchitecture-lessons-learned-for-large-volume-in-situ-serial-sectioning/. Accessed: November 30, 2020« Back to The 16th European Microscopy Congress 2016
EMC Abstracts - https://emc-proceedings.com/abstract/3-d-em-exploration-of-the-hepatic-microarchitecture-lessons-learned-for-large-volume-in-situ-serial-sectioning/