Abstract

The RIG-I-like receptors (RLRs) play a major role in sensing RNA virus infection to initiate and modulate antiviral immunity. They interact with particular viral RNAs, most of them being still unknown. To decipher the viral RNA signature on RLRs during viral infection, we tagged RLRs (RIG-I, MDA5, LGP2) and applied tagged protein affinity purification followed by next-generation sequencing (NGS) of associated RNA molecules. Two viruses with negative- and positive-sense RNA genome were used: measles (MV) and chikungunya (CHIKV). NGS analysis revealed that distinct regions of MV genome were specifically recognized by distinct RLRs: RIG-I recognized defective interfering genomes, whereas MDA5 and LGP2 specifically bound MV nucleoprotein-coding region. During CHIKV infection, RIG-I associated specifically to the 3' untranslated region of viral genome. This study provides the first comparative view of the viral RNA ligands for RIG-I, MDA5 and LGP2 in the presence of infection.

Article and author information

Author details

  1. Raul Y Sanchez David

    Unité de Génomique Virale et Vaccination, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Chantal Combredet

    Unité de Génomique Virale et Vaccination, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Odile Sismeiro

    Transcriptome and Epigenome, BioMics Pole, Center for Innovation and Technological Research, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Marie-Agnès Dillies

    Transcriptome and Epigenome, BioMics Pole, Center for Innovation and Technological Research, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Bernd Jagla

    Transcriptome and Epigenome, BioMics Pole, Center for Innovation and Technological Research, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Jean-Yves Coppée

    Transcriptome and Epigenome, BioMics Pole, Center for Innovation and Technological Research, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Marie Mura

    Unité de Génomique Virale et Vaccination, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  8. Mathilde Guerbois Galla

    University of Texas Medical Branch, Galveston, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Philippe Despres

    Technology platform CYROI, University of Reunion Island, Saint-Clotilde, France
    Competing interests
    The authors declare that no competing interests exist.
  10. Frédéric Tangy

    Unité de Génomique Virale et Vaccination, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  11. Anastassia V Komarova

    Unité de Génomique Virale et Vaccination, Institut Pasteur, Paris, France
    For correspondence
    stasy@pasteur.fr
    Competing interests
    The authors declare that no competing interests exist.

Copyright

© 2016, Sanchez David 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

  • 4,417
    views
  • 1,070
    downloads
  • 79
    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. Raul Y Sanchez David
  2. Chantal Combredet
  3. Odile Sismeiro
  4. Marie-Agnès Dillies
  5. Bernd Jagla
  6. Jean-Yves Coppée
  7. Marie Mura
  8. Mathilde Guerbois Galla
  9. Philippe Despres
  10. Frédéric Tangy
  11. Anastassia V Komarova
(2016)
Comparative analysis of viral RNA signatures on different RIG-I-like receptors
eLife 5:e11275.
https://doi.org/10.7554/eLife.11275

Share this article

https://doi.org/10.7554/eLife.11275

Further reading

    1. Immunology and Inflammation
    Hong Yu, Hiroshi Nishio ... Drew Pardoll
    Research Article

    The adaptive T cell response is accompanied by continuous rewiring of the T cell’s electric and metabolic state. Ion channels and nutrient transporters integrate bioelectric and biochemical signals from the environment, setting cellular electric and metabolic states. Divergent electric and metabolic states contribute to T cell immunity or tolerance. Here, we report in mice that neuritin (Nrn1) contributes to tolerance development by modulating regulatory and effector T cell function. Nrn1 expression in regulatory T cells promotes its expansion and suppression function, while expression in the T effector cell dampens its inflammatory response. Nrn1 deficiency in mice causes dysregulation of ion channel and nutrient transporter expression in Treg and effector T cells, resulting in divergent metabolic outcomes and impacting autoimmune disease progression and recovery. These findings identify a novel immune function of the neurotrophic factor Nrn1 in regulating the T cell metabolic state in a cell context-dependent manner and modulating the outcome of an immune response.

    1. Immunology and Inflammation
    Takashi Watanabe, Hikaru Hata ... Hidehiro Fukuyama
    Research Article

    Antibodies are powerful tools for the therapy and diagnosis of various diseases. In addition to conventional hybridoma-based screening, recombinant antibody-based screening has become a common choice; however, its application is hampered by two factors: (1) screening starts after Ig gene cloning and recombinant antibody production only, and (2) the antibody is composed of paired chains, heavy and light, commonly expressed by two independent expression vectors. Here, we introduce a method for the rapid screening of recombinant monoclonal antibodies by establishing a Golden Gate-based dual-expression vector and in-vivo expression of membrane-bound antibodies. Using this system, we demonstrate the rapid isolation of influenza cross-reactive antibodies with high affinity from immunized mice within 7 days. This system is particularly useful for isolating therapeutic or diagnostic antibodies, for example during foreseen pandemics.