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

  1. Maximilian Joesch
  2. David Mankus
  3. Masahito Yamagata
  4. Ali Shahbazi
  5. Richard Shalek
  6. Adi Suissa-Peleg
  7. Markus Meister
  8. Jeff w Lichtman
  9. Walter J Scheirer
  10. Joshua R Sanes  Is a corresponding author
  1. Harvard University, United States
  2. University of Notre Dame, United States
  3. California Institute of Technology, United States
  4. Harvard, United States

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.

Data availability

The following data sets were generated

Article and author information

Author details

  1. Maximilian Joesch

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. David Mankus

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Masahito Yamagata

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8193-2931
  4. Ali Shahbazi

    University of Notre Dame, Notre Dame, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Richard Shalek

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Adi Suissa-Peleg

    School of Engineering and Applied Sciences, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Markus Meister

    Division of Biology, California Institute of Technology, Pasadena, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2136-6506
  8. Jeff w Lichtman

    Center for Brain Science, Harvard, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Walter J Scheirer

    University of Notre Dame, Notre Dame, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Joshua R Sanes

    Center for Brain Science, Harvard University, Cambridge, United States
    For correspondence
    sanesj@mcb.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8926-8836

Ethics

Animal experimentation: Animals were used in accordance with NIH guidelines and protocols approved by Institutional Animal Use and Care Committee at Harvard University (Protocol 233 #92_19).

Copyright

© 2016, Joesch et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 7,246
    views
  • 1,709
    downloads
  • 82
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Maximilian Joesch
  2. David Mankus
  3. Masahito Yamagata
  4. Ali Shahbazi
  5. Richard Shalek
  6. Adi Suissa-Peleg
  7. Markus Meister
  8. Jeff w Lichtman
  9. Walter J Scheirer
  10. Joshua R Sanes
(2016)
Reconstruction of genetically identified neurons imaged by serial-section electron microscopy
eLife 5:e15015.
https://doi.org/10.7554/eLife.15015

Share this article

https://doi.org/10.7554/eLife.15015

Further reading

    1. Cell Biology
    2. Genetics and Genomics
    Jisun So, Olivia Strobel ... Hyun Cheol Roh
    Tools and Resources

    Single-nucleus RNA sequencing (snRNA-seq), an alternative to single-cell RNA sequencing (scRNA-seq), encounters technical challenges in obtaining high-quality nuclei and RNA, persistently hindering its applications. Here, we present a robust technique for isolating nuclei across various tissue types, remarkably enhancing snRNA-seq data quality. Employing this approach, we comprehensively characterize the depot-dependent cellular dynamics of various cell types underlying mouse adipose tissue remodeling during obesity. By integrating bulk nuclear RNA-seq from adipocyte nuclei of different sizes, we identify distinct adipocyte subpopulations categorized by size and functionality. These subpopulations follow two divergent trajectories, adaptive and pathological, with their prevalence varying by depot. Specifically, we identify a key molecular feature of dysfunctional hypertrophic adipocytes, a global shutdown in gene expression, along with elevated stress and inflammatory responses. Furthermore, our differential gene expression analysis reveals distinct contributions of adipocyte subpopulations to the overall pathophysiology of adipose tissue. Our study establishes a robust snRNA-seq method, providing novel insights into the biological processes involved in adipose tissue remodeling during obesity, with broader applicability across diverse biological systems.

    1. Cell Biology
    Inês Sequeira
    Insight

    A combination of intermittent fasting and administering Wnt3a proteins to a bone injury can rejuvenate bone repair in aged mice.