单细胞 RNA-seq 工作流程增强揭示了冠心病细胞串扰和候选药物靶点。
Enhanced single-cell RNA-seq workflow reveals coronary artery disease cellular cross-talk and candidate drug targets.
机构信息
Medical Scientist Training Program, University of Virginia, Charlottesville, VA, 22908, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
出版信息
Atherosclerosis. 2022 Jan;340:12-22. doi: 10.1016/j.atherosclerosis.2021.11.025. Epub 2021 Nov 26.
BACKGROUND AND AIMS
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.
METHODS
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.
RESULTS
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.
CONCLUSIONS
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.
背景与目的
动脉粥样硬化斑块的微环境非常复杂,目前还没有能够调节斑块稳定性的选择性药物。我们试图开发一种 scRNA-seq 分析工作流程,以研究这种环境并发现潜在的治疗方法。我们设计了一个用户友好、可重复的工作流程,该流程将适用于其他特定于疾病的 scRNA-seq 数据集。
方法
在这里,我们将自动细胞标记、伪时间排序、配体-受体评估和药物-基因相互作用分析纳入到一个可随时部署的工作流程中。我们应用该流水线进一步研究了 Wirka 等人之前发表的人类冠状动脉单细胞数据集。值得注意的是,我们开发了一个交互式网络应用程序,以实现对该数据集和其他心血管单细胞数据集的进一步探索和分析。
结果
我们揭示了成纤维细胞样细胞从平滑肌细胞(SMCs)的不同衍生,并展示了它们在去分化过程中基因表达的关键变化。我们通过功能表达谱分析突出了动脉粥样硬化环境中的几个关键配体-受体相互作用,并揭示了几个未来用于精准医学的药理学发展途径。此外,我们的交互式网络应用程序 PlaqView(www.plaqview.com)允许非专业科学家探索这个和其他数据集,并在没有先验编码知识的情况下比较 scRNA-seq 工具。
结论
这个公开的工作流程和应用程序将允许更系统和用户友好地分析其他疾病和发育系统中的 scRNA 数据集。我们的分析流水线提供了许多生成假说的工具,以揭示冠状动脉疾病的病因。我们还强调了几种药物在动脉粥样硬化细胞环境中的潜在作用机制。未来版本的 PlaqView 将具有更多与 scRNA-seq 和 scATAC-seq 动脉粥样硬化相关的数据集,为该领域提供关键资源,并促进数据协调和生物学解释。
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