A Single-Cell Atlas of the Human Healthy Airways

Abstract

Rationale:The respiratory tract constitutes an elaborated line of defense based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. Methods:We have explored cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12 th division of the airway tree. Results:The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with peculiar cellular proportions in different sites of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression was stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine (PNEC) and brush cells, which are likely derived from a common population of precursor cells. We also report a population of KRT13 positive cells with a high percentage of dividing cells which are reminiscent of "hillock" cells previously described in mouse.Conclusions: Robust characterization of this unprecedented large single-cell cohort establishes an important resource for future investigations. The precise description of the continuum existing from nasal epithelium to successive divisions of lung airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing

“…To elucidate the expression pattern of the molecular targets of putative antiviral compounds from this cell-based screen, we used a previously reported dataset to analyse the transcriptional profile of these genes across cell types within the respiratory tract 31 . Critically, a majority of the mapped targets of active compounds were also expressed in relevant respiratory epithelial cells, suggesting that these may be physiologically relevant drug targets (Extended Data Figs.…”

“…3a showed significant enrichment by the GSEA analysis in the virus-infected samples compared to the control. Gene-expression analysis on human data was based on a publicly available RNA-seq dataset of nasopharyngeal swab specimens taken from patients infected with SARS-CoV-2 30 and a publicly available single-cell RNA-seq dataset consisting of profiled samples from four macro-anatomical locations of human airway epithelium in healthy living volunteers 31 (Extended Data Fig. 4).…”

“…The dataset is available on Gene Expression Omnibus (GEO) with accession number GSE153940. Extended Data Figure 4 is based on analysis of a publicly available single-cell RNA-seq dataset accessible from https://singlecell.broadinstitute.org/single_cell/study/ SCP867/hca-lungmap-covid-19-barbry-lung?scpbr=hca-covid-19-int egrated-analysis 31 . Gene-expression analysis on human data shown in Supplementary Table 2 (GSEA_Mason's paper) refers to the RNA-seq dataset in ref.…”

Single cell profiling of COVID-19 patients: an international data resource from multiple tissues

“…Epithelial cell types include AT1 ( AGER, HOPX ) and AT2 ( NAPSA , SFTB ) cells, ciliated cells ( FOXJ1, CAPS ), basal cells ( KRT5, DAPL1 ), ionocytes ( FOXI1, ASCL3 ), mucous ( MUC5AC, SCGB3A1 ) and serous ( PRR4, LYZ ) secretory cells, deuterosomal cells ( DEUP1, PLK4 ). We recovered a CD309 high SPRR3 high fraction of epithelial cells reminiscent to previously described mouse "hillock" cells ( Deprez et al, 2020 ). Three granulocyte subtypes were identified: neutrophils (based on CD16, CD66b and CD15 protein levels), basophils ( CPA3, CD123) and mast cells ( CPA3, CD117).…”

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data

“…The two most negative (blue) entries are highlighted in the Zoomed view (top right). Data are from (Deprez et al 2020), which presents a detailed single-cell atlas of the human airway from nose to the 12 th division of the airway tree. Single-cell capture was performed using the 10X Genomics Chromium device (3' V2), and data from the 35 samples for the atlas were pre-processed (Deprez et al 2020) using fastMNN (Haghverdi et al 2018) and Scanpy (Wolf et al 2018).…”