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Published July 7, 2016 | Published + Supplemental Material
Journal Article Open

Reconstruction of genetically identified neurons imaged by serial-section electron microscopy

Abstract

Resolving patterns of synaptic connectivity in neural circuits currently requires serial section electron microscopy. However, complete circuit reconstruction is prohibitively slow and may not be necessary for many purposes such as comparing neuronal structure and connectivity among multiple animals. Here, we present an alternative strategy, targeted reconstruction of specific neuronal types. We used viral vectors to deliver peroxidase derivatives, which catalyze production of an electron-dense tracer, to genetically identified neurons, and developed a protocol that enhances the electron-density of the labeled cells and while retaining quality of the ultrastructure. The high contrast of the marked neurons enabled two innovations that dramatically speed data acquisition: targeted high-resolution reimaging of regions selected from rapidly-acquired lower resolution reconstruction, and an unsupervised segmentation algorithm. This pipeline reduces imaging and reconstruction times by at least two orders of magnitude, facilitating directed inquiry of circuit motifs.

Additional Information

© 2016 Joesch et al. This article is distributed under the terms of the Creative Commons Attribution License. Received February 04, 2016. Accepted June 27, 2016. Published July 07, 2016. We thank Alice Ting, Jeff Martell, and Stephanie Lam for advice and for providing the APX and APEX2 constructs. We also thank Chiao-Lin Chen and Norbert Perrimon for generating and providing the UAS-APEX-GFP fly and Benjamin de Bivort for support with the fly work. This work was supported by NIH grant NS76467 to M.M., J.L. and J.R.S., an HHMI Collaborative Innovation Award to J.R.S., an IARPA contract #D16PC00002 to W.J.S. and by The International Human Frontier Science Program Organization fellowship to M.J. The authors declare no conflicts of interest.

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August 20, 2023
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