Cytoprotection by a naturally occurring variant of ATP5G1 in Arctic ground squirrel neural progenitor cells

  1. Neel S Singhal
  2. Meirong Bai
  3. Evan M Lee
  4. Shuo Luo
  5. Kayleigh R Cook
  6. Dengke K Ma  Is a corresponding author
  1. University of California, San Francisco, United States

Abstract

Many organisms in nature have evolved mechanisms to tolerate severe hypoxia or ischemia, including the hibernation-capable Arctic ground squirrel (AGS). Although hypoxic or ischemia tolerance in AGS involves physiological adaptations, little is known about the critical cellular mechanisms underlying intrinsic AGS cell resilience to metabolic stress. Through cell survival-based cDNA expression screens in neural progenitor cells, we identify a genetic variant of AGS Atp5g1 that confers cell resilience to metabolic stress. Atp5g1 encodes a subunit of the mitochondrial ATP synthase. Ectopic expression in mouse cells and CRISPR/Cas9 base editing of endogenous AGS loci revealed causal roles of one AGS-specific amino acid substitution in mediating cytoprotection by AGS ATP5G1. AGS ATP5G1 promotes metabolic stress resilience by modulating mitochondrial morphological change and metabolic functions. Our results identify a naturally occurring variant of ATP5G1 from a mammalian hibernator that critically contributes to intrinsic cytoprotection against metabolic stress.

Data availability

Data has been made available on Dryad (doi:10.7272/Q6MW2FCP) and code as been made available on GitHub (https://github.com/evanmlee/MaLab_spec_subs).

The following data sets were generated
    1. Neel Singhal
    2. Dengke Ma
    (2020) Data for
    Dryad Digital Repository, doi:10.7272/Q6MW2FCP.

Article and author information

Author details

  1. Neel S Singhal

    Neurology, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1605-4444
  2. Meirong Bai

    Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5919-7464
  3. Evan M Lee

    Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Shuo Luo

    Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Kayleigh R Cook

    Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Dengke K Ma

    Physiology, University of California, San Francisco, San Francisco, United States
    For correspondence
    Dengke.Ma@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5619-7485

Funding

National Institute of General Medical Sciences (R01)

  • Dengke K Ma

Pew Charitable Trusts (Pew Scholar Award)

  • Dengke K Ma

David and Lucile Packard Foundation (Fellowship)

  • Dengke K Ma

Innovative Genomics Institute (Curci Scholar Award)

  • Dengke K Ma

American Heart Association (Fellowship Grant)

  • Neel S Singhal

American Heart Association (Fellowship Grant)

  • Meirong Bai

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

Reviewing Editor

  1. Agnieszka Chacinska, University of Warsaw, Poland

Publication history

  1. Received: January 29, 2020
  2. Accepted: October 8, 2020
  3. Accepted Manuscript published: October 14, 2020 (version 1)
  4. Version of Record published: November 17, 2020 (version 2)

Copyright

© 2020, Singhal 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

  • 1,630
    Page views
  • 221
    Downloads
  • 6
    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. Neel S Singhal
  2. Meirong Bai
  3. Evan M Lee
  4. Shuo Luo
  5. Kayleigh R Cook
  6. Dengke K Ma
(2020)
Cytoprotection by a naturally occurring variant of ATP5G1 in Arctic ground squirrel neural progenitor cells
eLife 9:e55578.
https://doi.org/10.7554/eLife.55578

Further reading

    1. Cell Biology
    Willa Wen-You Yim et al.
    Tools and Resources Updated

    Monitoring autophagic flux is necessary for most autophagy studies. The autophagic flux assays currently available for mammalian cells are generally complicated and do not yield highly quantitative results. Yeast autophagic flux is routinely monitored with the green fluorescence protein (GFP)-based processing assay, whereby the amount of GFP proteolytically released from GFP-containing reporters (e.g. GFP-Atg8), detected by immunoblotting, reflects autophagic flux. However, this simple and effective assay is typically inapplicable to mammalian cells because GFP is efficiently degraded in lysosomes while the more proteolytically resistant red fluorescent protein (RFP) accumulates in lysosomes under basal conditions. Here, we report a HaloTag (Halo)-based reporter processing assay to monitor mammalian autophagic flux. We found that Halo is sensitive to lysosomal proteolysis but becomes resistant upon ligand binding. When delivered into lysosomes by autophagy, pulse-labeled Halo-based reporters (e.g. Halo-LC3 and Halo-GFP) are proteolytically processed to generate Haloligand when delivered into lysosomes by autophagy. Hence, the amount of free Haloligand detected by immunoblotting or in-gel fluorescence imaging reflects autophagic flux. We demonstrate the applications of this assay by monitoring the autophagy pathways, macroautophagy, selective autophagy, and even bulk nonselective autophagy. With the Halo-based processing assay, mammalian autophagic flux and lysosome-mediated degradation can be monitored easily and precisely.

    1. Cell Biology
    2. Computational and Systems Biology
    Théo Aspert et al.
    Tools and Resources

    Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays.