Enhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets

The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, repr...

Full description

Saved in:

Bibliographic Details
Published in:	Atherosclerosis Vol. 340; pp. 12 - 22
Main Authors:	Ma, Wei Feng, Hodonsky, Chani J., Turner, Adam W., Wong, Doris, Song, Yipei, Mosquera, Jose Verdezoto, Ligay, Alexandra V., Slenders, Lotte, Gancayco, Christina, Pan, Huize, Barrientos, Nelson B., Mai, David, Alencar, Gabriel F., Owsiany, Katherine, Owens, Gary K., Reilly, Muredach P., Li, Mingyao, Pasterkamp, Gerard, Mokry, Michal, van der Laan, Sander W., Khomtchouk, Bohdan B., Miller, Clint L.
Format:	Journal Article
Language:	English
Published:	Ireland Elsevier B.V 01-01-2022
Subjects:	Atherosclerosis Cardioinformatics Coronary Artery Disease - drug therapy Coronary Artery Disease - genetics Drug Discovery Gene Expression Profiling Humans Pharmaceutical Preparations Pipeline PlaqView Precision Medicine RNA-Seq scRNA Sequence Analysis, RNA Single-Cell Analysis Software Web Application Workflow Atherosclerosis scRNA PlaqView Web Application Cardioinformatics Drug Discovery Pipeline Precision Medicine
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets. Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets. We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge. This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation. [Display omitted] •Automated cell annotation and pseudotemporal analyses reveal expression changes in de-differentiated smooth muscle cells (SMC).•Ligand-receptor profiling reveals potential drug targets that modulate SMC and fibroblast signaling during atherosclerosis.•Reproducible workflow allows for detailed evaluation of scRNA-seq datasets with minimal coding and eliminates potential bias.•PlaqView web application allows for interactive analysis of scRNA-seq datasets and facilitates data sharing and reanalysis.
Bibliography:	Authors’ contributions WFM designed and performed the statistical analysis. CJH, AWT, AVL, BBK, DW and YS refined the methodology and edited the manuscript. JVM, DM, and GFA helped with scripting. AVL, BBK, LS, HZP, NBB, and KO helped with data acquisition and refinement of PlaqView, and edited the manuscript. GKO, MPR, MYL, BBK, GP, MM, and SWvL provided critical feedback on the manuscript. MYL provided statistical review and edited the manuscript. CG provided deployment and application scripting support, and edited the manuscript. CLM and SWvL conceived the project. CLM and BBK refined the project and edited the manuscript.
ISSN:	0021-9150 1879-1484
DOI:	10.1016/j.atherosclerosis.2021.11.025