Characterization of the COPD alveolar niche using single-cell RNA sequencing

Abstract

Chronic obstructive pulmonary disease (COPD) is a leading cause of death worldwide, however our understanding of cell specific mechanisms underlying COPD pathobiology remains incomplete. Here, we analyze single-cell RNA sequencing profiles of explanted lung tissue from subjects with advanced COPD or control lungs, and we validate findings using single-cell RNA sequencing of lungs from mice exposed to 10 months of cigarette smoke, RNA sequencing of isolated human alveolar epithelial cells, functional in vitro models, and in situ hybridization and immunostaining of human lung tissue samples. We identify a subpopulation of alveolar epithelial type II cells with transcriptional evidence for aberrant cellular metabolism and reduced cellular stress tolerance in COPD. Using transcriptomic network analyses, we predict capillary endothelial cells are inflamed in COPD, particularly through increased CXCL-motif chemokine signaling. Finally, we detect a high-metallothionein expressing macrophage subpopulation enriched in advanced COPD. Collectively, these findings highlight cell-specific mechanisms involved in the pathobiology of advanced COPD.

Altered Heterogeneity of Ageing Lung Endothelium is a Hallmark of Idiopathic Pulmonary Fibrosis

“…Quantitative analysis of the cell numbers for each of 25 clusters in age-matched groups revealed IPF-associated changes in ageing human lungs in both cohorts (Figure 1 E). This reflects differences in location of tissue samples collected for scRNAseq analysis (Table 1) and matches reported in non-age matching studies contribution of different cell types to the total human lung cell population and alterations in IPF lung (20, 21, 24-26, 33, 34) Supplementary Table 2). Our data also uncovered changes in proportions of ageing human lung BEC and LEC populations between cohorts and conditions (Figure 1 E, Supplementary Table 3).…”

“…When applied to 12 ageing human lung BEC subpopulations, the dot plot expression analysis of markers of lung EC sub-types proposed in other transcriptional studies in human and murine tissues (35)(36)(37)(38)(39)(40) identified few distinct matches (Supplementary Figure 7). Further exploration of identities of 12 sub-populations by using these markers alongside those proposed for specific EC sub-clusters in HLCA and IPF cell atlas studies (20,21,(23)(24)(25), when coupled with module scoring (Figure 2 F) and cell cycle (Supplementary Figure 8) analyses, confirmed these matches, whilst 4 sub-clusters remained unannotated (Figure 2 F; Supplementary Figure 7). Altogether, these findings (Figure 2; Supplementary Figure 7) suggest that our study de-convoluted ageing human lung BEC population, providing advanced resolution of its heterogeneity at a transcriptional level, increasing the number of EC sub-clusters (20,21) and revealing previously underappreciated extend of diversity of ageing blood endothelium in human lung.…”

“…Furthermore, the lung has two distinct blood vascular circulatory networks – (bronchial and pulmonary; (18)) and three main networks of lymphatic vessels -in pulmonary tissue (peribronchial and perivascular - running parallel to the major airways and respiratory bronchioles, and existing in close proximity to the intralobular arterioles and small veins, or associated with alveoli) and in subpleural space (draining lymph from the surface of the organ) (19). The precise contribution of these specialised networks and the vessel subtypes and EC subpopulations that comprise them, to the pathophysiology and progression of IPF, or other CLDs, remain insufficiently characterised, except few individual studies (20, 21).…”

“…distal lung parenchyma (26), longitudinal sections (24) or multiple lobes (27). The most recent study generated cell atlases of the COPD lung for both human and murine tissues, comparative to physiologically ageing controls, identifying 6 subpopulations of EC (20). However, to date no comparison of lung endothelium has been performed between elderly IPF patients and age-matched healthy individuals.…”

Computation and visualization of cell–cell signaling topologies in single-cell systems data using Connectome

“…Here we describe a computational package in R called Connectome which facilitates each of these tasks . Connectome has been used to explore native signaling in human lung 9 and to identify aberrant signaling in pulmonary arterial hypertension (PAH) 10 , chronic obstructive pulmonary disease (COPD) 11 , and COVID-19 12 .…”