IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v560y2018i7718d10.1038_s41586-018-0394-6.html
   My bibliography  Save this article

A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte

Author

Listed:
  • Lindsey W. Plasschaert

    (Novartis Institutes for BioMedical Research
    Respiratory Diseases, Novartis Institutes for BioMedical Research)

  • Rapolas Žilionis

    (Harvard Medical School
    Vilnius University)

  • Rayman Choo-Wing

    (Novartis Institutes for BioMedical Research
    Respiratory Diseases, Novartis Institutes for BioMedical Research)

  • Virginia Savova

    (Harvard Medical School
    Precision Immunology, Immunology & Inflammation Research Therapeutic Area, Sanofi)

  • Judith Knehr

    (Novartis Institutes for BioMedical Research)

  • Guglielmo Roma

    (Novartis Institutes for BioMedical Research)

  • Allon M. Klein

    (Harvard Medical School)

  • Aron B. Jaffe

    (Novartis Institutes for BioMedical Research
    Respiratory Diseases, Novartis Institutes for BioMedical Research)

Abstract

The functions of epithelial tissues are dictated by the types, abundance and distribution of the differentiated cells they contain. Attempts to restore tissue function after damage require knowledge of how physiological tasks are distributed among cell types, and how cell states vary between homeostasis, injury–repair and disease. In the conducting airway, a heterogeneous basal cell population gives rise to specialized luminal cells that perform mucociliary clearance1. Here we perform single-cell profiling of human bronchial epithelial cells and mouse tracheal epithelial cells to obtain a comprehensive census of cell types in the conducting airway and their behaviour in homeostasis and regeneration. Our analysis reveals cell states that represent known and novel cell populations, delineates their heterogeneity and identifies distinct differentiation trajectories during homeostasis and tissue repair. Finally, we identified a novel, rare cell type that we call the ‘pulmonary ionocyte’, which co-expresses FOXI1, multiple subunits of the vacuolar-type H+-ATPase (V-ATPase) and CFTR, the gene that is mutated in cystic fibrosis. Using immunofluorescence, modulation of signalling pathways and electrophysiology, we show that Notch signalling is necessary and FOXI1 expression is sufficient to drive the production of the pulmonary ionocyte, and that the pulmonary ionocyte is a major source of CFTR activity in the conducting airway epithelium.

Suggested Citation

  • Lindsey W. Plasschaert & Rapolas Žilionis & Rayman Choo-Wing & Virginia Savova & Judith Knehr & Guglielmo Roma & Allon M. Klein & Aron B. Jaffe, 2018. "A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte," Nature, Nature, vol. 560(7718), pages 377-381, August.
  • Handle: RePEc:nat:nature:v:560:y:2018:i:7718:d:10.1038_s41586-018-0394-6
    DOI: 10.1038/s41586-018-0394-6
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-018-0394-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-018-0394-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuanyuan Chen & Reka Toth & Sara Chocarro & Dieter Weichenhan & Joschka Hey & Pavlo Lutsik & Stefan Sawall & Georgios T. Stathopoulos & Christoph Plass & Rocio Sotillo, 2022. "Club cells employ regeneration mechanisms during lung tumorigenesis," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    2. Qizhou Lian & Kui Zhang & Zhao Zhang & Fuyu Duan & Liyan Guo & Weiren Luo & Bobo Wing-Yee Mok & Abhimanyu Thakur & Xiaoshan Ke & Pedram Motallebnejad & Vlad Nicolaescu & Jonathan Chen & Chui Yan Ma & , 2022. "Differential effects of macrophage subtypes on SARS-CoV-2 infection in a human pluripotent stem cell-derived model," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Tim Flerlage & Jeremy Chase Crawford & E. Kaitlynn Allen & Danielle Severns & Shaoyuan Tan & Sherri Surman & Granger Ridout & Tanya Novak & Adrienne Randolph & Alina N. West & Paul G. Thomas, 2023. "Single cell transcriptomics identifies distinct profiles in pediatric acute respiratory distress syndrome," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    4. Yuan Guan & Annika Enejder & Meiyue Wang & Zhuoqing Fang & Lu Cui & Shih-Yu Chen & Jingxiao Wang & Yalun Tan & Manhong Wu & Xinyu Chen & Patrik K. Johansson & Issra Osman & Koshi Kunimoto & Pierre Rus, 2021. "A human multi-lineage hepatic organoid model for liver fibrosis," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    5. Leila R. Martins & Lina Sieverling & Michelle Michelhans & Chiara Schiller & Cihan Erkut & Thomas G. P. Grünewald & Sergio Triana & Stefan Fröhling & Lars Velten & Hanno Glimm & Claudia Scholl, 2024. "Single-cell division tracing and transcriptomics reveal cell types and differentiation paths in the regenerating lung," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    6. Andrew Berical & Rhianna E. Lee & Junjie Lu & Mary Lou Beermann & Jake A. Le Suer & Aditya Mithal & Dylan Thomas & Nicole Ranallo & Megan Peasley & Alex Stuffer & Katherine Bukis & Rebecca Seymour & J, 2022. "A multimodal iPSC platform for cystic fibrosis drug testing," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    7. Katarina Kulhankova & Soumba Traore & Xue Cheng & Hadrien Benk-Fortin & Stéphanie Hallée & Mario Harvey & Joannie Roberge & Frédéric Couture & Sajeev Kohli & Thomas J. Gross & David K. Meyerholz & Gar, 2023. "Shuttle peptide delivers base editor RNPs to rhesus monkey airway epithelial cells in vivo," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    8. Michael J. Geuenich & Dae-won Gong & Kieran R. Campbell, 2024. "The impacts of active and self-supervised learning on efficient annotation of single-cell expression data," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    9. Lei Xiong & Kang Tian & Yuzhe Li & Weixi Ning & Xin Gao & Qiangfeng Cliff Zhang, 2022. "Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:560:y:2018:i:7718:d:10.1038_s41586-018-0394-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.