Early detection of cerebrovascular pathology and protective antiviral immunity by MRI

  1. Li Liu  Is a corresponding author
  2. Steve Dodd
  3. Ryan D Hunt
  4. Nikorn Pothayee
  5. Tatjana Atanasijevic
  6. Nadia Bouraoud
  7. Dragan Maric
  8. E Ashley Moseman
  9. Selamawit Gossa
  10. Dorian B McGavern
  11. Alan P Koretsky  Is a corresponding author
  1. National Institute of Neurological Disorders and Stroke, United States
  2. Duke University School of Medicine, United States

Abstract

Central nervous system (CNS) infections are a major cause of human morbidity and mortality worldwide. Even patients that survive CNS infections can have lasting neurological dysfunction resulting from immune and pathogen induced pathology. Developing approaches to noninvasively track pathology and immunity in the infected CNS is crucial for patient management and development of new therapeutics. Here, we develop novel MRI-based approaches to monitor virus-specific CD8+ T cells and their relationship to cerebrovascular pathology in the living brain. We studied a relevant murine model in which a neurotropic virus (vesicular stomatitis virus) was introduced intranasally and then entered the brain via olfactory sensory neurons - a route exploited by many pathogens in humans. Using T2*-weighted high-resolution MRI, we identified small cerebral microbleeds as an early form of pathology associated with viral entry into the brain. Mechanistically, these microbleeds occurred in the absence of peripheral immune cells and were associated with infection of vascular endothelial cells. We monitored the adaptive response to this infection by developing methods to iron label and track individual virus specific CD8+ T cells by MRI. Transferred antiviral T cells were detected in the brain within a day of infection and were able to reduce cerebral microbleeds. These data demonstrate the utility of MRI in detecting the earliest pathological events in the virally infected CNS as well as the therapeutic potential of antiviral T cells in mitigating this pathology.

Data availability

The source data of this study wilb be available in Dryad (https://doi.org/10.5061/dryad.79cnp5hwp)

The following data sets were generated

Article and author information

Author details

  1. Li Liu

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    For correspondence
    li.liu3@nih.gov
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2493-3086
  2. Steve Dodd

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Ryan D Hunt

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Nikorn Pothayee

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Tatjana Atanasijevic

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Nadia Bouraoud

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Dragan Maric

    Flow and Imaging Cytometry Core Facility, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. E Ashley Moseman

    Department of Immunology, Duke University School of Medicine, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Selamawit Gossa

    Viral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Dorian B McGavern

    Viral Immunology and Intravital Imaging Section, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Alan P Koretsky

    Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, United States
    For correspondence
    koretskya@ninds.nih.gov
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8085-4756

Funding

the National Institute of Health

  • Alan P Koretsky

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

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 715
    views
  • 112
    downloads
  • 6
    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. Li Liu
  2. Steve Dodd
  3. Ryan D Hunt
  4. Nikorn Pothayee
  5. Tatjana Atanasijevic
  6. Nadia Bouraoud
  7. Dragan Maric
  8. E Ashley Moseman
  9. Selamawit Gossa
  10. Dorian B McGavern
  11. Alan P Koretsky
(2022)
Early detection of cerebrovascular pathology and protective antiviral immunity by MRI
eLife 11:e74462.
https://doi.org/10.7554/eLife.74462

Share this article

https://doi.org/10.7554/eLife.74462

Further reading

    1. Neuroscience
    Célian Bimbard, Flóra Takács ... Philip Coen
    Tools and Resources

    Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the ‘Apollo Implant’, an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a ‘payload’ module which is attached to the probe and is recoverable, and a ‘docking’ module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

    1. Neuroscience
    Ana Fló, Lucas Benjamin ... Ghislaine Dehaene-Lambertz
    Research Article

    Interest in statistical learning in developmental studies stems from the observation that 8-month-olds were able to extract words from a monotone speech stream solely using the transition probabilities (TP) between syllables (Saffran et al., 1996). A simple mechanism was thus part of the human infant’s toolbox for discovering regularities in language. Since this seminal study, observations on statistical learning capabilities have multiplied across domains and species, challenging the hypothesis of a dedicated mechanism for language acquisition. Here, we leverage the two dimensions conveyed by speech –speaker identity and phonemes– to examine (1) whether neonates can compute TPs on one dimension despite irrelevant variation on the other and (2) whether the linguistic dimension enjoys an advantage over the voice dimension. In two experiments, we exposed neonates to artificial speech streams constructed by concatenating syllables while recording EEG. The sequence had a statistical structure based either on the phonetic content, while the voices varied randomly (Experiment 1) or on voices with random phonetic content (Experiment 2). After familiarisation, neonates heard isolated duplets adhering, or not, to the structure they were familiarised with. In both experiments, we observed neural entrainment at the frequency of the regularity and distinct Event-Related Potentials (ERP) to correct and incorrect duplets, highlighting the universality of statistical learning mechanisms and suggesting it operates on virtually any dimension the input is factorised. However, only linguistic duplets elicited a specific ERP component, potentially an N400 precursor, suggesting a lexical stage triggered by phonetic regularities already at birth. These results show that, from birth, multiple input regularities can be processed in parallel and feed different higher-order networks.