Transcriptional networks specifying homeostatic and inflammatory programs of gene expression in human aortic endothelial cells.

Endothelial cells (ECs) are critical determinants of vascular homeostasis and inflammation, but transcriptional mechanisms specifying their identities and functional states remain poorly understood. Here, we report a genome-wide assessment of regulatory landscapes of primary human aortic endothelial cells (HAECs) under basal and activated conditions, enabling inference of transcription factor networks that direct homeostatic and pro-inflammatory programs. We demonstrate that 43% of detected enhancers are EC-specific and contain SNPs associated to cardiovascular disease and hypertension. We provide evidence that AP1, ETS, and GATA transcription factors play key roles in HAEC transcription by co-binding enhancers associated with EC-specific genes. We further demonstrate that exposure of HAECs to oxidized phospholipids or pro-inflammatory cytokines results in signal-specific alterations in enhancer landscapes and associate with coordinated binding of CEBPD, IRF1, and NFκB. Collectively, these findings identify cis-regulatory elements and corresponding trans-acting factors that contribute to EC identity and their specific responses to pro-inflammatory stimuli

Single-Cell Epigenomics and Functional Fine-Mapping of Atherosclerosis GWAS Loci

Rationale: Genome-wide association studies have identified hundreds of loci associated with coronary artery disease (CAD). Many of these loci are enriched in cisregulatory elements but not linked to cardiometabolic risk factors nor to candidate causal genes, complicating their functional interpretation. Objective: Single-nucleus chromatin accessibility profiling of the human atherosclerotic lesions was used to investigate cell type-specific patterns of cisregulatory elements, to understand transcription factors establishing cell identity, and to interpret CAD-relevant, noncoding genetic variation. Methods and Results: We used single-nucleus ATAC-seq (assay for transposase-accessible chromatin with sequencing) to generate DNA accessibility maps in >7000 cells derived from human atherosclerotic lesions. We identified 5 major lesional cell types including endothelial cells, smooth muscle cells, monocyte/macrophages, natural killer/T cells, and B cells and further investigated subtype characteristics of macrophages and smooth muscle cells transitioning into fibromyocytes. We demonstrated that CAD-associated genetic variants are particularly enriched in endothelial and smooth muscle cell-specific open chromatin. Using single-cell coaccessibility and cis-expression quantitative trait loci information, we prioritized putative target genes and candidate regulatory elements for approximate to 30% of all known CAD loci. Finally, we performed genome-wide experimental fine-mapping of the CAD variants identified in genome-wide association studies using epigenetic quantitative trait loci analysis in primary human aortic endothelial cells and self-transcribing active regulatory region sequencing (STARR-Seq) massively parallel reporter assay in smooth muscle cells. This analysis identified potential causal single-nucleotide polymorphisms (SNPs) and the associated target gene for over 30 CAD loci. We present several examples where the chromatin accessibility and gene expression could be assigned to one cell type predicting the cell type of action for CAD loci. Conclusions: These findings highlight the potential of applying single-nucleus ATAC-seq to human tissues in revealing relative contributions of distinct cell types to diseases and in identifying genes likely to be influenced by noncoding genome-wide association study variants.</p

scDemultiplex: An iterative beta-binomial model-based method for accurate demultiplexing with hashtag oligos

Single-cell sequencing have been widely used to characterize cellular heterogeneity. Sample multiplexing where multiple samples are pooled together for single-cell experiments, attracts wide attention due to its benefits of increasing capacity, reducing costs, and minimizing batch effects. To analyze multiplexed data, the first crucial step is to demultiplex, the process of assigning cells to individual samples. Inaccurate demultiplexing will create false cell types and result in misleading characterization. We propose scDemultiplex, which models hashtag oligo (HTO) counts with beta-binomial distribution and uses an iterative strategy for further refinement. Compared with seven existing demultiplexing approaches, scDemultiplex achieved great performance in both high-quality and low-quality data. Additionally, scDemultiplex can be combined with other approaches to improve their performance

Transcriptional networks specifying homeostatic and inflammatory programs of gene expression in human aortic endothelial cells.

Endothelial cells (ECs) are critical determinants of vascular homeostasis and inflammation, but transcriptional mechanisms specifying their identities and functional states remain poorly understood. Here, we report a genome-wide assessment of regulatory landscapes of primary human aortic endothelial cells (HAECs) under basal and activated conditions, enabling inference of transcription factor networks that direct homeostatic and pro-inflammatory programs. We demonstrate that 43% of detected enhancers are EC-specific and contain SNPs associated to cardiovascular disease and hypertension. We provide evidence that AP1, ETS, and GATA transcription factors play key roles in HAEC transcription by co-binding enhancers associated with EC-specific genes. We further demonstrate that exposure of HAECs to oxidized phospholipids or pro-inflammatory cytokines results in signal-specific alterations in enhancer landscapes and associate with coordinated binding of CEBPD, IRF1, and NFκB. Collectively, these findings identify cis-regulatory elements and corresponding trans-acting factors that contribute to EC identity and their specific responses to pro-inflammatory stimuli

Transcriptional synergy in human aortic endothelial cells is vulnerable to combination p300/CBP and BET bromodomain inhibition

Summary: Combinatorial signaling by proinflammatory cytokines synergizes to exacerbate toxicity to cells and tissue injury during acute infections. To explore synergism at the gene-regulatory level, we investigated the dynamics of transcription and chromatin signaling in response to dual cytokines by integrating nascent RNA imaging mass spectrometry, RNA sequencing, amplification-independent mRNA quantification, assay for transposase-accessible chromatin using sequencing (ATAC-seq), and transcription factor profiling. Costimulation with interferon-gamma (IFNγ) and tumor necrosis factor alpha (TNFα) synergistically induced a small subset of genes, including the chemokines CXCL9, -10, and -11. Gene induction coincided with increased chromatin accessibility at non-coding regions enriched for p65 and STAT1 binding sites. To discover coactivator dependencies, we conducted a targeted chemogenomic screen of transcriptional inhibitors followed by modeling of inhibitor dose-response curves. These results identified high efficacy of either p300/CREB-binding protein (CBP) or bromodomain and extra-terminal (BET) bromodomain inhibitors to disrupt induction of synergy genes. Combination p300/CBP and BET bromodomain inhibition at half-maximal inhibitory concentrations (subIC50) synergistically abrogated IFNγ/TNFα-induced chemokine gene and protein levels

Systematic analysis of naturally occurring insertions and deletions that alter transcription factor spacing identifies tolerant and sensitive transcription factor pairs

Regulation of gene expression requires the combinatorial binding of sequence-specific transcription factors (TFs) at promoters and enhancers. Prior studies showed that alterations in the spacing between TF binding sites can influence promoter and enhancer activity. However, the relative importance of TF spacing alterations resulting from naturally occurring insertions and deletions (InDels) has not been systematically analyzed. To address this question, we first characterized the genome-wide spacing relationships of 73 TFs in human K562 cells as determined by ChIP-seq. We found a dominant pattern of a relaxed range of spacing between collaborative factors, including 45 TFs exclusively exhibiting relaxed spacing with their binding partners. Next, we exploited millions of InDels provided by genetically diverse mouse strains and human individuals to investigate the effects of altered spacing on TF binding and local histone acetylation. These analyses suggested that spacing alterations resulting from naturally occurring InDels are generally tolerated in comparison to genetic variants directly affecting TF binding sites. To experimentally validate this prediction, we introduced synthetic spacing alterations between PU.1 and C/EBPβ binding sites at six endogenous genomic loci in a macrophage cell line. Remarkably, collaborative binding of PU.1 and C/EBPβ at these locations tolerated changes in spacing ranging from 5-bp increase to >30-bp decrease. Collectively, these findings have implications for understanding mechanisms underlying enhancer selection and for the interpretation of non-coding genetic variation

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 mechanosensing 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 (GWAS) have identified chromosome 1p32.2 as strongly associated with CAD/IS; however, the causal mechanism related to this locus remains unknown. Using statistical analyses, assay of transposase accessible chromatin with whole-genome sequencing (ATAC-seq), H3K27ac/H3K4me2 ChIP with whole-genome sequencing (ChIP-seq), and CRISPR interference in human aortic endothelial cells (HAECs), our results demonstrate that rs17114036, a common noncoding polymorphism at 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 shear stress by regulating phospholipid phosphatase 3 (PLPP3). Chromatin accessibility quantitative trait locus (caQTL) mapping using HAECs from 56 donors, allelic imbalance assay from 7 donors, and luciferase assays demonstrate that CAD/IS-protective allele at rs17114036 in PLPP3 intron 5 confers increased endothelial enhancer activity. ChIP-PCR and luciferase assays show that CAD/IS-protective allele at rs17114036 creates a binding site for transcription factor Krüppel-like factor 2 (KLF2), which increases the enhancer activity under unidirectional flow. These results demonstrate that a human SNP contributes to critical endothelial mechanotransduction mechanisms and suggest that human haplotypes and related cis-regulatory elements provide a previously unappreciated layer of regulatory control in cellular mechanosensing mechanisms

Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks.

Acknowledgements: A.S.P. is supported by the AHA (20SFRN35120123). J.M.R. is supported by the National Institutes of Health (NIH) (K23HL150327). R.V.S. is supported by grants from the American Heart Association (AHA) and NIH. M.N. is supported by NIH (R01HL156975, R01HL131029) and by a Career Investment Award from the Department of Medicine, Boston University School of Medicine. R.E.G. and M.A.S. were funded by R01NR019628. T.T., K.A.W., and L.F. are supported by the National Institute on Aging’s Intramural Research Program. P.R. is supported by the John S. LaDue Memorial Fellowship at Harvard Medical School. Q.S.W. is supported by the NIH (R01HL140074). M.Y.M. was supported by the NIH (K23HL171855). B.C. is supported by an Early Career Investigator Grant from the American Lung Association. The BLSA study was funded by the National Institute on Aging’s Intramural Research Program. Proteomics in CARDIA were funded by a grant to R.K. (R01HL122477). CARDIA is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (75N92023D00002 and 75N92023D00005), Northwestern University (75N92023D00004), University of Minnesota (75N92023D00006) and Kaiser Foundation Research Institute (75N92023D00003). This manuscript has been reviewed by CARDIA for scientific content. Exercise testing in CARDIA was funded by a grant to S.S. and B. Sternfeld (R01HL078972). The Fenland Study is funded by the UK Medical Research Council, with proteomic assessment funded by Somalogic; Investigators T.G., N.J.W. and S.B. received support from the UK Medical Research Council (MC_UU_00006/1, MC_UU_00006/4) as well as the National Institute for Health and Care Research Cambridge Biomedical Research Centre (IS-BRC-1215-20014). The HERITAGE study was supported by several grants from the NHLBI (R01HL45670, R01HL47317, R01HL47321, R01HL47323 and R01HL47327).Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48-0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable