Protein visualization and manipulation in Drosophila through the use of epitope tags recognized by nanobodies

Abstract

Expansion of the available repertoire of reagents for visualization and manipulation of proteins will help understand their function. Short epitope tags linked to proteins of interest and recognized by existing binders such as nanobodies facilitate protein studies by obviating the need to isolate new antibodies directed against them. Nanobodies have several advantages over conventional antibodies, as they can be expressed and used as tools for visualization and manipulation of proteins in vivo. Here, we characterize two short (<15 aa) NanoTag epitopes, 127D01 and VHH05, and their corresponding high-affinity nanobodies. We demonstrate their use in Drosophila for in vivo protein detection and re-localization, direct and indirect immunofluorescence, immunoblotting, and immunoprecipitation. We further show that CRISPR-mediated gene targeting provides a straightforward approach to tagging endogenous proteins with the NanoTags. Single copies of the NanoTags, regardless of their location, suffice for detection. This versatile and validated toolbox of tags and nanobodies will serve as a resource for a wide array of applications, including functional studies in Drosophila and beyond.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file.

Article and author information

Author details

  1. Jun Xu

    Department of Genetics, Harvard Medical School, Boston, United States
    For correspondence
    Jun_Xu@hms.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Ah-Ram Kim

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9597-6759
  3. Ross W Cheloha

    Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Fabian A Fischer

    Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Joshua Shing Shun Li

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Yuan Feng

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Emily Stoneburner

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Richard Binari

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Stephanie E Mohr

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9639-7708
  10. Jonathan Zirin

    Department of Genetics, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Hidde L Ploegh

    Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Norbert Perrimon

    Department of Genetics, Harvard Medical School, Boston, United States
    For correspondence
    perrimon@genetics.med.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7542-472X

Funding

National Institute of General Medical Sciences (GM132087)

  • Norbert Perrimon

National Research Foundation of Korea (2021R1A6A3A14039622)

  • Ah-Ram Kim

Croucher Foundation

  • Joshua Shing Shun Li

Howard Hughes Medical Institute

  • Norbert Perrimon

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

Copyright

© 2022, Xu 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.

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  1. Jun Xu
  2. Ah-Ram Kim
  3. Ross W Cheloha
  4. Fabian A Fischer
  5. Joshua Shing Shun Li
  6. Yuan Feng
  7. Emily Stoneburner
  8. Richard Binari
  9. Stephanie E Mohr
  10. Jonathan Zirin
  11. Hidde L Ploegh
  12. Norbert Perrimon
(2022)
Protein visualization and manipulation in Drosophila through the use of epitope tags recognized by nanobodies
eLife 11:e74326.
https://doi.org/10.7554/eLife.74326

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https://doi.org/10.7554/eLife.74326

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