Biology subjects

Whalen, M. B.

Publications and source records attributed to Whalen, M. B..

3 recordsLinked to original sources

bioRxiv2023

Multiomics of human aortic endothelial cells reveals cell subtypes with heterogeneous responses to canonical endothelial-to-mesenchymal perturbations

ObjectiveEndothelial cells (ECs), macrophages, and vascular smooth muscle cells (VSMCs) are major cell types in atherosclerosis progression, and heterogeneity in EC sub-phenotypes are becoming increasingly appreciated. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Approach and ResultsTo create an in vitro dataset to study human EC heterogeneity, multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs). To model pro-inflammatory and activating environments characteristic of the atherosclerotic microenvironment in vitro, HAECs from at least three donors were exposed to three distinct perturbations with their respective controls: transforming growth factor beta-2 (TGFB2), interleukin-1 beta (IL1B), and siRNA-mediated knock-down of the endothelial transcription factor ERG (siERG). To form a comprehensive in vivo/ex vivo dataset of human atherosclerotic cell types, meta-analysis of single cell transcriptomes across 17 human arterial specimens was performed. Two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and in vivo cell profiles. HAEC cultures were reproducibly populated by 4 major clusters with distinct pathway enrichment profiles: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Exposure to siERG, IL1B or TGFB2 elicited mostly distinct transcriptional and accessible chromatin responses. EC1 and EC2, the most canonically healthy EC populations, were affected predominantly by siERG; the activated cluster EC3 was most responsive to IL1B; and the mesenchymal population EC4 was most affected by TGFB2. Quantitative comparisons between in vitro and in vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated SNPs from GWAS, suggesting these cell phenotypes harbor CAD-modulating mechanisms. ConclusionPrimary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here, which have been reported by others to be involved in the pathogenesis of atherosclerosis as well as induce endothelial-to-mesenchymal transition (EndMT), only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and in vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

genomics↗

bioRxiv2021

Functional non-coding SNPs in human endothelial cells fine-map vascular trait associations

Functional consequences of genetic variation in the non-coding human genome are difficult to ascertain despite demonstrated associations to common, complex disease traits. To elucidate properties of functional non-coding SNPs with effects in human endothelial cells (EC), we utilized molecular Quantitative Trait Locus (molQTL) analysis for transcription factor binding, chromatin accessibility, and H3K27 acetylation to nominate a set of likely functional non-coding SNPs. Together with information from genome-wide association studies for vascular disease traits, we tested the ability of 34,344 variants to perturb enhancer function in ECs using the highly multiplexed STARR-seq assay. Of these, 5,592 variants validated, whose enriched attributes included: 1) mutations to TF binding motifs for ETS or AP1 that are regulators of EC state, 2) location in accessible and H3K27ac-marked EC chromatin, and 3) molQTLs associations whereby alleles associate with differences in chromatin accessibility and TF binding across genetically diverse ECs. Next, using pro-inflammatory IL1B as an activator of cell state, we observed robust evidence (>50%) of context-specific SNP effects, underscoring the prevalence of non-coding gene-by-environment (GxE) effects. Lastly, using these cumulative data, we fine-mapped vascular disease loci and highlight evidence suggesting mechanisms by which non-coding SNPs at two loci affect risk for Pulse Pressure/Large Artery Stroke, and Abdominal Aortic Aneurysm through respective effects on transcriptional regulation of POU4F1 and LDAH. Together, we highlight the attributes and context dependence of functional non-coding SNPs, and provide new mechanisms underlying vascular disease risk.

genetics↗

bioRxiv2018

A genetic variant at coronary artery disease and ischemic stroke locus 1p32.2 regulates endothelial responses to hemodynamics

Biomechanical cues dynamically control major cellular processes but whether genetic variants actively participate in mechano-sensing mechanisms remains unexplored. Vascular homeostasis is tightly regulated by hemodynamics. Exposure to disturbed blood flow at arterial sites of branching and bifurcation causes constitutive activation of vascular endothelium contributing to atherosclerosis, the major cause of coronary artery disease (CAD) and ischemic stroke (IS). Conversely, unidirectional flow promotes quiescent endothelium. Genome-wide association studies have identified chromosome 1p32.2 as one of the most strongly associated loci with CAD/IS; however, the causal mechanism related to this locus remains unknown. Employing statistical analyses, ATAC-seq, and H3K27ac/H3K4me2 ChIP-Seq in human aortic endothelium (HAEC), our results demonstrate that rs17114036, a common noncoding polymorphism at the 1p32.2, is located in an endothelial enhancer dynamically regulated by hemodynamics. CRISPR/Cas9-based genome editing shows that rs17114036-containing region promotes endothelial quiescence under unidirectional flow by regulating phospholipid phosphatase 3 (PLPP3). Chromatin accessibility quantitative trait locus mapping using HAECs from 56 donors, allelic imbalance assay from 7 donors, and luciferase assays further demonstrate that CAD/IS protective allele at rs17114036 in PLPP3 intron 5 confers an increased endothelial enhancer activity. ChIPPCR and luciferase assays show that CAD/IS protective allele at rs17114036 creates a binding site for transcription factor Kruppel-like factor 2, which increases the enhancer activity under unidirectional flow. These results demonstrate for the first time that a human single-nucleotide polymorphism contributes to critical endothelial mechanotransduction mechanisms and suggest that human haplotypes and related cisregulatory elements provide a previously unappreciated layer of regulatory control in cellular mechano-sensing mechanisms.\n\nSignificance StatementBiomechanical stimuli control major cellular functions and play critical roles in the pathogenesis of diverse human diseases. Although recent studies have implicated genetic variation in regulating key biological processes, whether human genetic variants contribute to the cellular mechano-sensing mechanisms remains unclear. This study provides the first line of evidence supporting an underappreciated role of genetic predisposition in cellular mechanotransduction mechanisms. Employing epigenomic profiling, genome-editing, and latest human genetics approaches, our data demonstrate that rs17114036, a common noncoding polymorphism implicated in coronary artery disease and ischemic stroke by genome-wide association studies, dynamically regulates endothelial responses to blood flow (hemodynamics) related to atherosclerosis via regulation of an intronic enhancer. The results provide new molecular insights linking disease-associated genetic variants to cellular mechanobiology.

genomics↗