Entry by multiple picornaviruses is dependent on a pathway that includes TNK2, WASL and NCK1

  1. Hongbing Jiang  Is a corresponding author
  2. Christian Leung
  3. Stephen Tahan
  4. David Wang  Is a corresponding author
  1. Washington University in St Louis, United States

Abstract

Comprehensive knowledge of the host factors required for picornavirus infection would facilitate antiviral development. Here we demonstrate roles for three human genes, TNK2, WASL, and NCK1, in infection by multiple picornaviruses. CRISPR deletion of TNK2, WASL or NCK1 reduced encephalomyocarditis virus (EMCV), coxsackievirus B3 (CVB3), poliovirus and enterovirus D68 infection, and chemical inhibitors of TNK2 and WASL decreased EMCV infection. Reduced EMCV lethality was observed in mice lacking TNK2. TNK2, WASL and NCK1 were important in early stages of the viral lifecycle, and genetic epistasis analysis demonstrated that the three genes function in a common pathway. Mechanistically, reduced internalization of EMCV was observed in TNK2 deficient cells demonstrating that TNK2 functions in EMCV entry. Domain analysis of WASL demonstrated that its actin nucleation activity was necessary to facilitate viral infection. Together, these data support a model wherein TNK2, WASL, and NCK1 comprise a pathway important for multiple picornaviruses.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files were provided.

Article and author information

Author details

  1. Hongbing Jiang

    Department of Molecular Microbiology, Pathology and Immunology, Washington University in St Louis, St Louis, United States
    For correspondence
    hongbingjiang@wustl.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Christian Leung

    Department of Molecular Microbiology, Pathology and Immunology, Washington University in St Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Stephen Tahan

    Department of Molecular Microbiology, Pathology and Immunology, Washington University in St Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. David Wang

    Department of Molecular Microbiology, Pathology and Immunology, Washington University in St Louis, St Louis, United States
    For correspondence
    davewang@wustl.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0827-196X

Funding

National Institutes of Health (R01 AI134967)

  • David Wang

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

Ethics

Animal experimentation: Animal experiments were conducted under the supervision of Department of Comparative Medicine at Washington University in St. Louis. All animal protocols were approved by the Washington University Institutional Animal Care and Use Committee (Protocol #20170194 and #20180289).

Copyright

© 2019, Jiang 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

  • 1,913
    views
  • 311
    downloads
  • 18
    citations

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

Download links

Share this article

https://doi.org/10.7554/eLife.50276

Further reading

    1. Evolutionary Biology
    2. Microbiology and Infectious Disease
    Zach Hensel
    Short Report

    Accurate estimation of the effects of mutations on SARS-CoV-2 viral fitness can inform public-health responses such as vaccine development and predicting the impact of a new variant; it can also illuminate biological mechanisms including those underlying the emergence of variants of concern. Recently, Lan et al. reported a model of SARS-CoV-2 secondary structure and its underlying dimethyl sulfate reactivity data (Lan et al., 2022). I investigated whether base reactivities and secondary structure models derived from them can explain some variability in the frequency of observing different nucleotide substitutions across millions of patient sequences in the SARS-CoV-2 phylogenetic tree. Nucleotide basepairing was compared to the estimated ‘mutational fitness’ of substitutions, a measurement of the difference between a substitution’s observed and expected frequency that is correlated with other estimates of viral fitness (Bloom and Neher, 2023). This comparison revealed that secondary structure is often predictive of substitution frequency, with significant decreases in substitution frequencies at basepaired positions. Focusing on the mutational fitness of C→U, the most common type of substitution, I describe C→U substitutions at basepaired positions that characterize major SARS-CoV-2 variants; such mutations may have a greater impact on fitness than appreciated when considering substitution frequency alone.

    1. Microbiology and Infectious Disease
    Michi Miura, Naho Kiuchi ... Mineki Saito
    Research Article

    Influenza A virus transcribes viral mRNAs from the eight segmented viral genome when it infects. The kinetics of viral transcription, nuclear export of viral transcripts, and their potential variation between the eight segments are poorly characterised. Here, we introduce a statistical framework for estimating the nuclear export rate of each segment from a snapshot of in situ mRNA localisation. This exploits the cell-to-cell variation at a single time point observed by an imaging-based in situ transcriptome assay. Using our model, we revealed the variation in the mRNA nuclear export rate of the eight viral segments. Notably, the two influenza viral antigens hemagglutinin and neuraminidase were the slowest segments in the nuclear export, suggesting the possibility that influenza A virus uses the nuclear retention of viral transcripts to delay the expression of antigenic molecules. Our framework presented in this study can be widely used for investigating the nuclear retention of nascent transcripts produced in a transcription burst.