Abstract

This data article contains complementary figure and movies (Supplementary Movies 1–3) related to the research article entitled, “Effective synaptome analysis of itch-mediating neurons in the spinal cord: a novel immunohistochemical methodology using high-voltage electron microscopy” [7]. It is important to show the synaptic connections at the ultrastructural level to understand the neural circuit, which requires the three-dimensional (3-D) analyses in the electron microscopy. Here, we applied a new sample preparation method, a high-contrast en bloc staining according to the protocol of the National Center for Microscopy and Imaging Research (NCMIR), University of California, San Diego, CA, USA to high-voltage electron microscopy (HVEM) tomography in order to examine the 3-D chemical neuroanatomy of the rat spinal cord. Pre-embedding immunoelectron microscopy was used in this study. HVEM has an excellent potential to directly visualize the ultrastructures in semi-thin sections (~5 μm thick), and we have successfully visualized many itch-mediating synaptic connections and neural networks in the spinal cord using “HVEM tomography”. Moreover, the methodology used in this study is simple and can be applied in multiple ways. This is an important contribution to ultrastructural investigations of the central nervous system in the present post-genomic age.

Highlights

  • Images were processed with IMOD, UCSF Chimera and the AMIRA software packages

  • Using high-voltage electron microscopy (HVEM) tomography, we demonstrated a previously uncharacterized itch-mediating neural network

  • HVEM images are obtained from semi-thin sections, which are contrasted with the heavy metal staining (A) or the National Center for Microscopy and Imaging Research (NCMIR) method (B)

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Summary

Introduction

Images were processed with IMOD, UCSF Chimera and the AMIRA software packages. Immunostained semi-thin sections were observed with HVEM by tilting the specimen from À 60.01 to þ 60.01, continuously. Animations and ultrastructural analyses were performed with UCSF Chimera software and manually segmented using the AMIRA

Results
Conclusion
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