(942.1) A Transcriptional Regulation Bioinformatics Pipeline to Predict Co-Regulated Genes in Vascular Smooth Muscle Cell Phenotypic Transitions During Atherosclerosis

Poster Board Number: D64

Mahima Reddy (University of Virginia School of Medicine), Vlad Serbulea (University of Virginia School of Medicine), Sohel Shamsuzzaman (University of Virginia School of Medicine), Anita Salamon (University of Virginia School of Medicine), Rupa Tripathi (University of Virginia School of Medicine), Clint Miller (University of Virginia School of Medicine), Giuseppe Mocci (Karolinska Institutet), Johan Björkegren (Icahn School of Medicine at Mount Sinai), Gary Owens (University of Virginia School of Medicine)

The rupture of vulnerable or advanced atherosclerotic lesions contributes to myocardial infarctions and strokes, the leading causes of death globally. During all stages of atherosclerosis, vascular smooth muscle cells (VSMCs) are recruited as a major source of plaque cells within lesions, where they undergo phenotypic modulation and give rise to both plaque-stabilizing and destabilizing phenotypes. Because most atherosclerosis studies test the functional role of single transcription factors, genes, and proteins in VSMCs, many aspects of how VSMC plasticity can be clinically exploited to prevent the rupture of vulnerable atherosclerotic lesions remain unclear. Systems biology approaches have emerged as a promising avenue for characterizing cellular dynamics at the organismal level, but they remain under-utilized in the field of cardiovascular medicine. This study proposes a novel systems biology pipeline that integrates experimental and computational tools with large datasets measuring the transcriptomes and epigenomes of phenotypically transitioning VSMCs. Our pipeline allows users to identify candidate transcription factors that co-regulate mouse or human gene sets controlling specific VSMC phenotypic transitions during atherosclerosis. The computational algorithms developed in this workflow integrate an array of publicly available databases, such as the Ensembl genome database and the JASPAR transcription factor database. To demonstrate the translational potential of our pipeline, we used it to test the hypothesis that the murine mesenchymal marker stem cell antigen-1 Sca1 (Ly6a) has a human ortholog, which has not been previously validated as a target in clinical therapies. To test the hypothesis that there are sets of genes co-regulated with Ly6a in human VSMCs which, when expressed in concert, promote a distinct phenotypic state marked by Ly6a in mice, we integrated genomic and ATAC-seq analyses of VSMCs to identify murine genes with human orthologs that bind Ly6a-specific transcription factors. Specifically, we predict that the transcription factors ETS1, KLF5, GATA6, and SOX10 co-regulate sets of human genes with Ly6a. While prior studies have associated these transcription factors with VSMC proliferation and phenotypic modulation, we specifically predict these Ly6a-specific transcription factor co-regulate the following human gene sets: PHACTR1, EFHC1, LAMC2 (ETS1); TTC33, RUNX1, KIAA1217 (KLF5); TMEM50A (GATA6); and ZBTB20, MYLK2 (SOX10). To validate these predictions, we will determine if these transcription factors and their co-regulated genes are expressed in single cell RNA-sequencing analyses of human carotid arteries and can be detected with immunofluorescence staining of human coronary artery sections. We will also use siRNA to target these candidate transcription factors and genes in cultured VSMCs. The results of our pipeline will help identify novel transcriptional regulatory networks in VSMCs that can be therapeutically targeted for the treatment of advanced atherosclerosis.