Reconstructing neural circuits using multiresolution correlated light and electron microscopy

Karl Friedrichsen, Pratyush Ramakrishna, Jen Chun Hsiang, Katia Valkova, Daniel Kerschensteiner, Josh L. Morgan

Research output: Contribution to journalArticlepeer-review

Abstract

Correlated light and electron microscopy (CLEM) can be used to combine functional and molecular characterizations of neurons with detailed anatomical maps of their synaptic organization. Here we describe a multiresolution approach to CLEM (mrCLEM) that efficiently targets electron microscopy (EM) imaging to optically characterized cells while maintaining optimal tissue preparation for high-throughput EM reconstruction. This approach hinges on the ease with which arrays of sections collected on a solid substrate can be repeatedly imaged at different scales using scanning electron microscopy. We match this multiresolution EM imaging with multiresolution confocal mapping of the aldehyde-fixed tissue. Features visible in lower resolution EM correspond well to features visible in densely labeled optical maps of fixed tissue. Iterative feature matching, starting with gross anatomical correspondences and ending with subcellular structure, can then be used to target high-resolution EM image acquisition and annotation to cells of interest. To demonstrate this technique and range of images used to link live optical imaging to EM reconstructions, we provide a walkthrough of a mouse retinal light to EM experiment as well as some examples from mouse brain slices.

Original languageEnglish
Article number753496
JournalFrontiers in Neural Circuits
Volume16
DOIs
StatePublished - Oct 21 2022

Keywords

  • confocal 3D microscopy
  • connectomics
  • correlated light and electron microscopy (CLEM)
  • electron microscopy
  • neural circuit
  • synapse
  • tissue mapping

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