Single-cell multiomic analysis of mesenchymal cells reveals molecular signatures and regulators of lung allograft fibrosis
Lu Lu, A. Patrick McLinden, Natalie M. Walker, Ragini Vittal, Yichen Wang, Fatemeh Fattahi, Stephen T. Russell, Michael P. Combs, Joshua D. Welch, Vibha N. Lama
Lu Lu, A. Patrick McLinden, Natalie M. Walker, Ragini Vittal, Yichen Wang, Fatemeh Fattahi, Stephen T. Russell, Michael P. Combs, Joshua D. Welch, Vibha N. Lama
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Research Article Genetics Pulmonology

Single-cell multiomic analysis of mesenchymal cells reveals molecular signatures and regulators of lung allograft fibrosis

Abstract

Survival after lung transplantation is limited by chronic, progressive graft failure, termed chronic lung allograft dysfunction (CLAD). Graft-resident mesenchymal cells (MCs) drive CLAD pathogenesis and exhibit stable dysregulated signaling, yet the transcriptomic and epigenomic drivers underlying this fibrogenic transformation remain elusive. We used single-cell multiomic profiling to characterize gene expression and chromatin accessibility in MCs isolated from bronchoalveolar lavage fluid of lung transplant recipients with and without CLAD, collected early after transplantation or after disease onset. MCs obtained after CLAD onset demonstrated a distinct transcriptomic signature compared with non-CLAD controls, enabling classification of disease status at the single-cell level with greater than 98% accuracy using signature genes. Chromatin accessibility analyses identified enrichment of CCAAT-enhancer-binding protein family transcription factors, specifically CEBPD, in CLAD MCs. MCs early after transplantation showed minimal accessibility differences, suggesting that CEBPD-associated regulatory changes emerge over time. Integration analyses identified 8 MC states and a CLAD-specific shift toward a fibrotic state. CEBPD, SOX4, and FOXP2 were identified as putative regulators of this state with substantial overlap in predicted targets. Targeting CEBPD reversed fibrotic phenotypes of CLAD MCs (decreased ECM expression, contractility, proliferation, and migration). Together, these data provide insights into transcriptomic and epigenomic changes in posttransplant MCs, facilitating the nomination of biomarkers and therapeutic targets.

Authors

Lu Lu, A. Patrick McLinden, Natalie M. Walker, Ragini Vittal, Yichen Wang, Fatemeh Fattahi, Stephen T. Russell, Michael P. Combs, Joshua D. Welch, Vibha N. Lama

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Figure 4

Cell state heterogeneity and cell state shifts in patient-derived MCs.

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Cell state heterogeneity and cell state shifts in patient-derived MCs. (...
(A) Uniform manifold approximation and projection (UMAP) representation of 22,918 cells derived from lung transplant recipients at the 2 time points. Each dot represents a single cell, and cells are colored by clusters. (B) Density plots of integrated MCs. Top left: Early time point (later developed CLAD). Top right: Early time point (later not developed CLAD). Bottom left: Late time point (CLAD patient–derived). Bottom right: Late time point (non–CLAD patient–derived). (C) Compositional change in fibrotic (top) and inflammatory (bottom) clusters. The bounds of the boxes represent the 25th and 75th percentiles (interquartile range, IQR); the line within each box represents the median; the whiskers extend to the minimum and maximum values within 1.5× IQR from the box bounds; individual data points beyond the whiskers are plotted as outliers. (D) Velocities fit by VeloVAE are visualized as streamlines in the UMAP plot.