Live imaging reveals the cellular events downstream of SARM1 activation

  1. Kwang Woo Ko
  2. Laura Devault
  3. Yo Sasaki
  4. Jeffrey Milbrandt  Is a corresponding author
  5. Aaron DiAntonio  Is a corresponding author
  1. Washington University School of Medicine, United States

Abstract

SARM1 is an inducible NAD+ hydrolase that triggers axon loss and neuronal cell death in the injured and diseased nervous system. While SARM1 activation and enzyme function are well defined, the cellular events downstream of SARM1 activity but prior to axonal demise are much less well understood. Defects in calcium, mitochondria, ATP, and membrane homeostasis occur in injured axons, but the relationships among these events have been difficult to disentangle because prior studies analyzed large collections of axons in which cellular events occur asynchronously. Here we used live imaging of mouse sensory neurons with single axon resolution to investigate the cellular events downstream of SARM1 activity. Our studies support a model in which SARM1 NADase activity leads to an ordered sequence of events from loss of cellular ATP, to defects in mitochondrial movement and depolarization, followed by calcium influx, externalization of phosphatidylserine, and loss of membrane permeability prior to catastrophic axonal self-destruction.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Kwang Woo Ko

    Washington University School of Medicine, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Laura Devault

    Washington University School of Medicine, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Yo Sasaki

    Washington University School of Medicine, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0024-0031
  4. Jeffrey Milbrandt

    Washington University School of Medicine, St Louis, United States
    For correspondence
    jmilbrandt@wustl.edu
    Competing interests
    The authors declare that no competing interests exist.
  5. Aaron DiAntonio

    Washington University School of Medicine, St Louis, United States
    For correspondence
    diantonio@wustl.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7262-0968

Funding

National Institutes of Health (R01CA219866)

  • Jeffrey Milbrandt
  • Aaron DiAntonio

National Institutes of Health (RO1NS087632)

  • Jeffrey Milbrandt
  • Aaron DiAntonio

National Institutes of Health (RF1-AG013730)

  • Jeffrey Milbrandt

National Institutes of Health (F32NS117784)

  • Laura Devault

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

Reviewing Editor

  1. Graeme W Davis, University of California, San Francisco, United States

Version history

  1. Received: June 10, 2021
  2. Preprint posted: June 15, 2021 (view preprint)
  3. Accepted: November 12, 2021
  4. Accepted Manuscript published: November 15, 2021 (version 1)
  5. Version of Record published: November 24, 2021 (version 2)

Copyright

© 2021, Ko 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

  • 2,014
    Page views
  • 414
    Downloads
  • 31
    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. Kwang Woo Ko
  2. Laura Devault
  3. Yo Sasaki
  4. Jeffrey Milbrandt
  5. Aaron DiAntonio
(2021)
Live imaging reveals the cellular events downstream of SARM1 activation
eLife 10:e71148.
https://doi.org/10.7554/eLife.71148

Share this article

https://doi.org/10.7554/eLife.71148

Further reading

    1. Neuroscience
    Kiwamu Kudo, Kamalini G Ranasinghe ... Srikantan S Nagarajan
    Research Article

    Alzheimer’s disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

    1. Medicine
    2. Neuroscience
    Luisa Fassi, Shachar Hochman ... Roi Cohen Kadosh
    Research Article

    In recent years, there has been debate about the effectiveness of treatments from different fields, such as neurostimulation, neurofeedback, brain training, and pharmacotherapy. This debate has been fuelled by contradictory and nuanced experimental findings. Notably, the effectiveness of a given treatment is commonly evaluated by comparing the effect of the active treatment versus the placebo on human health and/or behaviour. However, this approach neglects the individual’s subjective experience of the type of treatment she or he received in establishing treatment efficacy. Here, we show that individual differences in subjective treatment - the thought of receiving the active or placebo condition during an experiment - can explain variability in outcomes better than the actual treatment. We analysed four independent datasets (N = 387 participants), including clinical patients and healthy adults from different age groups who were exposed to different neurostimulation treatments (transcranial magnetic stimulation: Studies 1 and 2; transcranial direct current stimulation: Studies 3 and 4). Our findings show that the inclusion of subjective treatment can provide a better model fit either alone or in interaction with objective treatment (defined as the condition to which participants are assigned in the experiment). These results demonstrate the significant contribution of subjective experience in explaining the variability of clinical, cognitive, and behavioural outcomes. We advocate for existing and future studies in clinical and non-clinical research to start accounting for participants’ subjective beliefs and their interplay with objective treatment when assessing the efficacy of treatments. This approach will be crucial in providing a more accurate estimation of the treatment effect and its source, allowing the development of effective and reproducible interventions.