Single-cell RNA sequencing reveals novel cell differentiation dynamics during human airway epithelium regeneration
By
Sandra Ruiz Garcia,
Marie Deprez,
Kevin Lebrigand,
Agnès Paquet,
Amélie Cavard,
Marie-Jeanne Arguel,
Virginie Magnone,
Ignacio Caballero,
Sylvie Leroy,
Charles-Hugo Marquette,
Brice Marcet,
Pascal Barbry,
Laure-Emmanuelle Zaragosi
Posted 24 Oct 2018
bioRxiv DOI: 10.1101/451807
(published DOI: 10.1242/dev.177428)
Background: It is usually considered that the upper airway epithelium is composed of multiciliated, goblet, secretory and basal cells, which collectively constitute an efficient first line of defense against inhalation of noxious substances. Upon injury, regeneration of this epithelium through proliferation and differentiation can restore a proper mucociliary function. However, in chronic airway diseases, the injured epithelium frequently displays defective repair leading to tissue remodeling, characterized by a loss of multiciliated cells and mucus hyper-secretion. Delineating drivers of differentiation dynamics and cell fate in the human airway epithelium is important to preserve homeostasis. Results: We have used single cell transcriptomics to characterize the sequence of cellular and molecular processes taking place during human airway epithelium regeneration. We have characterized airway subpopulations with high resolution and lineage inference algorithms have unraveled cell trajectories from basal to luminal cells, providing markers for specific cell populations, such as deuterosomal cells, i.e. precursors of multiciliated cells. We report that goblet cells, like secretory cells, can act as precursors of multiciliated cells. Our study provides a repertoire of molecules involved in key steps of the regeneration process, either keratins or components of the Notch, Wnt or BMP/TGFbeta signaling pathways. Our findings were confirmed in independent experiments performed on fresh human and pig airway samples, and on mouse tracheal epithelial cells. Conclusions: Our single-cell RNA-seq study provides novel insights about airway epithelium differentiation dynamics, clarifies cell trajectories between secretory, goblet and multiciliated cells, identifies novel cell subpopulations, and maps the activation and repression of key signaling pathways.
Download data
- Downloaded 2,826 times
- Download rankings, all-time:
- Site-wide: 4,193
- In cell biology: 83
- Year to date:
- Site-wide: 9,550
- Since beginning of last month:
- Site-wide: 8,585
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!