Characterization of Endothelial to Mesenchymal Transition in Air Pollution Mediated Atherosclerosis: Insights from Trajectory Inference and Functional Analyses in Single cell RNA Sequencing Data
Authors: Edwards-Glenn Jonnelle , Vergara-Martel Armando , Cara Elaine Ann , Rengasamy Palanivel , Rajagopalan Sanjay , Dazard Jean-Eudes 
Published: May 2024

Background: Air pollution is the world’s leading environmental risk factor for atherosclerotic cardiovascular disease (ASCVD). Regressive transcriptional reprogramming and transition of cells to primordial states has been identified as a driver of atherosclerosis. Endothelial cell to mesenchymal cell transition (EndoMT) whereby an endothelial cell transforms to a mesenchymal-like cellular phenotype is one such mechanism. However its relevance to air pollution exposure remains uncharacterized. Methods: Male ApoE−/− mice were inhalationally exposed to concentrated particulate matter <2.5μ component (PM2.5) or filtered air (FA, controls) using a Versatile Aerosol Concentration Enrichment System (VACES, 5–6 h/day, 5 d/week for 36 weeks, n = 7/group. PM2.5 concentrations were 70-80 μg/m3 or ~10X ambient levels. Following euthanasia, single-cell RNA-sequencing of aortic cells was performed using the 10-X platform (CA). For all subsequent analyses, aortic cell samples were integrated. Unsupervised clustering (k-NN) and low-dimensional space visualization (UMAP) were performed with a supervised graph method (Minimum Spanning Tree and Principal Curves) to infer and visualize trajectory analysis of novel cell lineages (branching and cell ordering in pseudotime/pseudospace). Functional analyses were carried out by statistical enrichment analysis using Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) against databases of Gene Ontologies (GO), Biological Pathways, putative regulatory motifs, proteins, or disease annotations to find over-representation of terms and functions. Pseudotime distribution assessed along exposure groups and cell-types lineages were statistically compared using GLM models. Differential Expression Analysis within lineages and between groups were tested by GLM and GAM models and FDR correction, followed by functional analyses. Results: Comparison of the pseudotime lineage with lineage root node at the endothelial cells revealed a similarity between observed endothelial (EC) to vascular smooth muscle (VSMC) cell transition with the differential transition noted with PM2.5 from FA. This overlap suggests a potential exaggeration of EC to VSMC transition in response to PM2.5 exposure. Differential gene expression profiling upon PM2.5-exposure in EC revealed significant changes in GO terms related to cell differentiation, cell migration, and regulation of cell population proliferation. Specific genes with variable patterns of expression (4481) were identified along the EC to VSMC lineage. KEGG pathway analysis along the lineage revealed enriched pathways including PI3K/Akt signaling pathway, MAPK signaling pathway, and Rap1 signaling pathway which are all implicated in the development and progression of atherosclerosis. Conclusion: Single-cell analysis reveals that chronic exposure to PM2.5 results in the exaggeration of EC to VSMC transition consistent with the EndoMT paradigm that may help explain the acceleration of ASCVD in response to air pollution exposure. Additional analysis of cell specific pathways may provide improved understanding of mechanisms progression of atherosclerosis in response to environmental exposures.

NIH: 1R35ES031702-01, R01 HL155450, 3R35ES031702-02S1; Burroughs Wellcome Fund: 1060485.

This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.