Subcellular proteomics of dopamine neurons in the mouse brain

  1. Benjamin D Hobson
  2. Se Joon Choi
  3. Eugene V Mosharov
  4. Rajesh K Soni
  5. David Sulzer  Is a corresponding author
  6. Peter Sims  Is a corresponding author
  1. Columbia University Medical Center, United States

Abstract

Dopaminergic neurons modulate neural circuits and behaviors via dopamine release from expansive, long range axonal projections. The elaborate cytoarchitecture of these neurons is embedded within complex brain tissue, making it difficult to access the neuronal proteome using conventional methods. Here, we demonstrate APEX2 proximity labeling within genetically targeted neurons in the mouse brain, enabling subcellular proteomics with cell type-specificity. By combining APEX2 biotinylation with mass spectrometry, we mapped the somatodendritic and axonal proteomes of midbrain dopaminergic neurons. Our dataset reveals the proteomic architecture underlying proteostasis, axonal metabolism, and neurotransmission in these neurons. We identify numerous proteins encoded by dopamine neuron-enriched genes in striatal dopaminergic axons, including ion channels with previously undescribed axonal localization. These proteomic datasets provide a resource for neuronal cell biology, and this approach can be readily adapted for study of other neural cell types.

Data availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (Perez-Riverol et al., 2019) partner repository with the dataset identifier PXD026229. Raw label-free quantification intensity values for proteomics data can be found in Figure 2 - source data 2. The scRNA-seq data analyzed are publicly available as GSE116470 (Saunders et al., 2018). High confidence DA neuron profiles used in this study are reported in Figure 5 - source data 3.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Benjamin D Hobson

    Depart of Systems Biology, Columbia University Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2745-5318
  2. Se Joon Choi

    New York State Psychiatric Institute, Columbia University Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Eugene V Mosharov

    New York State Psychiatric Institute, Columbia University Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Rajesh K Soni

    Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4556-4358
  5. David Sulzer

    Department of Psychiatry, Columbia University Medical Center, New York, United States
    For correspondence
    ds43@cumc.columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7632-0439
  6. Peter Sims

    Department of Systems Biology, Columbia University Medical Center, New York, United States
    For correspondence
    pas2182@columbia.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3921-4837

Funding

National Institutes of Health (F30DA047775)

  • Benjamin D Hobson

National Institutes of Health (R01NS095435)

  • David Sulzer

National Institutes of Health (R01DA007418)

  • David Sulzer

National Institutes of Health (R01MH122470)

  • David Sulzer

Michael J. Fox Foundation for Parkinson's Research (ASAP-000375)

  • David Sulzer
  • Peter Sims

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All experiments were conducted according to NIH guidelines and approved by the Institutional Animal Care and Use Committees of Columbia University and the New York State Psychiatric Institute. Protocol numbers are NYSPI #1584 (Columbia University AABI2605) and NYSPI #1551 (Columbia University AABD8564).

Reviewing Editor

  1. Andrew B West, Duke University, United States

Publication history

  1. Preprint posted: June 1, 2021 (view preprint)
  2. Received: June 2, 2021
  3. Accepted: January 30, 2022
  4. Accepted Manuscript published: January 31, 2022 (version 1)
  5. Version of Record published: February 21, 2022 (version 2)

Copyright

© 2022, Hobson 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

  • 2,779
    Page views
  • 552
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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. Benjamin D Hobson
  2. Se Joon Choi
  3. Eugene V Mosharov
  4. Rajesh K Soni
  5. David Sulzer
  6. Peter Sims
(2022)
Subcellular proteomics of dopamine neurons in the mouse brain
eLife 11:e70921.
https://doi.org/10.7554/eLife.70921

Further reading

    1. Neuroscience
    Arefeh Sherafati et al.
    Research Article Updated

    Cochlear implants are neuroprosthetic devices that can restore hearing in people with severe to profound hearing loss by electrically stimulating the auditory nerve. Because of physical limitations on the precision of this stimulation, the acoustic information delivered by a cochlear implant does not convey the same level of acoustic detail as that conveyed by normal hearing. As a result, speech understanding in listeners with cochlear implants is typically poorer and more effortful than in listeners with normal hearing. The brain networks supporting speech understanding in listeners with cochlear implants are not well understood, partly due to difficulties obtaining functional neuroimaging data in this population. In the current study, we assessed the brain regions supporting spoken word understanding in adult listeners with right unilateral cochlear implants (n=20) and matched controls (n=18) using high-density diffuse optical tomography (HD-DOT), a quiet and non-invasive imaging modality with spatial resolution comparable to that of functional MRI. We found that while listening to spoken words in quiet, listeners with cochlear implants showed greater activity in the left prefrontal cortex than listeners with normal hearing, specifically in a region engaged in a separate spatial working memory task. These results suggest that listeners with cochlear implants require greater cognitive processing during speech understanding than listeners with normal hearing, supported by compensatory recruitment of the left prefrontal cortex.

    1. Neuroscience
    Mohammad Ali Salehinejad et al.
    Research Article Updated

    Sleep strongly affects synaptic strength, making it critical for cognition, especially learning and memory formation. Whether and how sleep deprivation modulates human brain physiology and cognition is not well understood. Here we examined how overnight sleep deprivation vs overnight sufficient sleep affects (a) cortical excitability, measured by transcranial magnetic stimulation, (b) inducibility of long-term potentiation (LTP)- and long-term depression (LTD)-like plasticity via transcranial direct current stimulation (tDCS), and (c) learning, memory, and attention. The results suggest that sleep deprivation upscales cortical excitability due to enhanced glutamate-related cortical facilitation and decreases and/or reverses GABAergic cortical inhibition. Furthermore, tDCS-induced LTP-like plasticity (anodal) abolishes while the inhibitory LTD-like plasticity (cathodal) converts to excitatory LTP-like plasticity under sleep deprivation. This is associated with increased EEG theta oscillations due to sleep pressure. Finally, we show that learning and memory formation, behavioral counterparts of plasticity, and working memory and attention, which rely on cortical excitability, are impaired during sleep deprivation. Our data indicate that upscaled brain excitability and altered plasticity, due to sleep deprivation, are associated with impaired cognitive performance. Besides showing how brain physiology and cognition undergo changes (from neurophysiology to higher-order cognition) under sleep pressure, the findings have implications for variability and optimal application of noninvasive brain stimulation.