Genomic and scRNA-seq Analyses Reveal SMC Phenotypic Diversity as Key Determinants of Atherosclerotic Plaque Composition

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Falcao Alencar, Gabriel, Biochemistry and Molecular Genetics - School of Medicine, University of Virginia
Owens, Gary, MD-MPHY Mole Phys & Biophysics, University of Virginia
Bekiranov, Stefan, MD-BIOC Biochem/Mole Genetics, University of Virginia

Atherosclerosis is a disease of chronic inflammation and the leading cause of morbidity and mortality worldwide. Despite decades of research, our understanding of the mechanisms regulating plaque stability remains poor. Until recently, smooth muscle cells (SMCs) were thought to play an athero-protective role in lesion pathogenesis. However, rigorous lineage tracing has shown a significant portion (>80%) of SMC-derived cells within an advanced atherosclerotic lesion did not express detectable SMC markers in an ApoE KO mouse model. Furthermore, SMC-specific conditional KO of Klf4 resulted in a reduction of several indices of plaque instability and SMC-derived macrophage-like cells. In contrast, conditional KO of Oct4 in SMCs presented a reduction of SMCs and increase of Lgals3+ cells within lesions, as well as the increase of several indices of plaque instability. Taken together, SMCs can have a beneficial or detrimental effect in lesion pathogenesis.
Studies within this dissertation are focused on understanding the potential mechanisms by which SMCs can have opposing phenotypes in disease. To address this question, we used genomic approaches (bulk RNA-seq, ChIP-seq, and scRNA-seq) in combination with several SMC-lineage tracing mouse models, including a newly developed dual-lineage tracing system. We hypothesize that combinatorial Oct4 or Klf4 ChIP-seq and RNA-seq analysis of advanced atherosclerotic lesions from our SMC-Klf4 and SMC-Oct4 mice provide a unique opportunity to identify genes that play a critical role in regulating beneficial or detrimental changes in SMC phenotype. We have shown that bulk RNA-seq of SMCKLF4-Δ/Δ vs SMCKLF4-WT/WT and SMCOCT4-Δ/Δ vs SMCOCT4-WT/WT showed opposite regulation of several pathways, suggesting a “genomic” phenotype. One of the most surprising results in our analysis was the fact that more than 1/3 of all CAD GWAS loci are possible SMCKlf4 and SMCOct4 target genes based on our ChIP-seq. In addition, we also demonstrate that both Klf4 and Oct4 are significantly upregulated in atherosclerotic lesions of human patients.
In addition, using scRNA-seq, we also showed that there is a calcifying phenotype that is Klf4 dependent. Moreover, we developed a novel SMC-Dual Lineage tracing mouse aiming to study the function of SMCs that activate Lgals3. Surprisingly, Lgals3 activation occurs in a more plastic state than previously thought, and these cells acquire several different phenotypes, including the calcifying phenotype. Further, the Lgals3 activation occurs, at least in part, in the fibrous cap. The combination of this mouse model, and its enabling visualization of cellular transition and their location, with scRNA-seq gives us an incredible potential to understand SMCs transitions within atherosclerotic lesions.
Taken together, we conclude that: First, SMC phenotypic transitions can be predominantly beneficial or detrimental; Second, the cross-comparison analysis showed a remarkable correlation between late stage disease models in mouse and humans; Third, more than 1/3 of GWAS CAD appear to be, at least in part, impacting SMC function and are either Klf4 and/or Oct4 potential targets; Fourth, Klf4 appears to modulate more than one phenotypic transition in SMCs; Fifth, SMCs transitions within the cap are more dynamic than originally thought. We hypothesize that detrimental reprograming of SMC and other ECM producing cells can destabilize atherosclerotic lesions. Improving our understanding of SMC gene regulation and biology is a key challenge and a potential source of novel therapeutic approaches focused on stabilization of lesions.

PHD (Doctor of Philosophy)
Smooth Muscle Cells, Klf4, Oct4, ChIP-seq, RNA-seq, Atherosclerosis, scRNA-seq
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