Biology subjects

Benavente, E. D.

Publications and source records attributed to Benavente, E. D..

4 recordsLinked to original sources

bioRxiv2023

Human primary plaque cell cultures to study mechanisms of atherosclerosis

Plaque smooth muscle cells are critical players in the initiation and advancement of atherosclerotic disease. They produce extracellular matrix (ECM) components, which play a role in lesion progression and stabilization. Despite clear phenotypic differences between plaque smooth muscle cells and vascular smooth muscle cells (VSMCs), VSMCs are still widely used as a model system in atherosclerotic research. Here we present a conditioned outgrowth method to isolate plaque smooth muscle cells. We obtained plaque cells from 27 donors (24 carotid and 3 femoral endarterectomies). We show that these cells keep their proliferative capacity for eight passages, are transcriptionally stable, retain donor-specific gene expression programs, and express extracellular matrix proteins (FN1, COL1A1, DCN) and smooth muscle cell markers (ACTA2, MYH11, CNN1). Single-cell transcriptomics of plaque tissue and cultured cells reveals that cultured plaque cells closely resemble the myofibroblast fraction of plaque smooth muscle cells. Chromatin immunoprecipitation sequencing (ChIP-seq) shows the presence of histone H3 lysine 4 dimethylation (H3K4me2) at the MYH11 promoter, pointing to their smooth muscle cell origin. Finally, we demonstrated that plaque cells can be efficiently transduced (>97%) and are capable to take up oxidized LDL (oxLDL) and undergo calcification. In conclusion, we present a method to isolate and culture primary human plaque cells that retain plaque myofibroblast-like cells phenotypical and functional capabilities - making them a suitable in vitro model for studying selected mechanisms of atherosclerosis.

cell biology↗

bioRxiv2023

Female gene networks are expressed in myofibroblast-like smooth muscle cells in vulnerable atherosclerotic plaques.

Women presenting with coronary artery disease (CAD) more often present with fibrous atherosclerotic plaques, which are currently understudied. Phenotypically modulated smooth muscle cells (SMCs) contribute to atherosclerosis in women. How these phenotypically modulated SMCs shape female versus male plaques is unknown. Here, we show sex-stratified gene regulatory networks (GRNs) from human carotid atherosclerotic tissue. Prioritization of these networks identified two main SMC GRNs in late-stage atherosclerosis. Single-cell RNA-sequencing mapped these GRNs to two SMC phenotypes: a phenotypically modulated myofibroblast-like SMC network and a contractile SMC network. The myofibroblast-like GRN was mostly expressed in plaques that were vulnerable in females. Finally, mice orthologs of the female myofibroblast-like genes showed retained expression in advanced plaques from female mice but were downregulated in male mice during atherosclerosis progression. Female atherosclerosis is driven by GRNs that promote a fibrous vulnerable plaque rich in myofibroblast-like SMCs.

bioinformatics↗

bioRxiv2022

Genetic regulation of human aortic smooth muscle cell gene expression and splicing predict causal coronary artery disease genes

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies (GWAS) have identified over 175 loci associated with CAD. The majority of these loci are in non-coding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we hypothesized that a subset of the CAD GWAS risk loci are associated with the regulation of transcription in distinct SMC phenotypes. Here, we measured gene expression in SMCs isolated from the ascending aortas of 151 ethnically diverse heart transplant donors in quiescent or proliferative conditions and calculated the association of their expression and splicing with [~]6.3 million imputed single nucleotide polymorphism (SNP) markers across the genome. We identified 4,910 expression and 4,412 splice quantitative trait loci (sQTL) that represent regions of the genome associated with transcript abundance and splicing. 3,660 of the eQTLs had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 of the eQTLs were SMC- and sex-specific, respectively. To identify the effector transcript(s) regulated by CAD GWAS loci, we used four distinct colocalization approaches and identified 84 eQTL and 164 sQTLs that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. Two CAD loci colocalized with a SMC sex-specific eQTL (AL160313.1 and TERF2IP) and another locus colocalized with SMC-specific eQTL (ALKBH8). Also, 27% and 37% of the sQTLs were unique to quiescent or proliferative SMCs, respectively. The most significantly associated CAD locus, 9p21, was an sQTL for the long non-coding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. Collectively, these results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

genetics↗

bioRxiv2021

Getting close to nature - Plasmodium knowlesi reference genome sequences from contemporary clinical isolates

Plasmodium knowlesi, a malaria parasite of old-world macaque monkeys, is used extensively to model Plasmodium biology. Recently P. knowlesi was found in the human population of Southeast Asia, particularly Malaysia. P. knowlesi causes un-complicated to severe and fatal malaria in the human host with features in common with the more prevalent and virulent malaria caused by Plasmodium falciparum. As such P. knowlesi presents a unique opportunity to inform an experimental model for malaria with clinical data from same-species human infections. Experimental lines of P. knowlesi represent well characterised genetically static parasites and to maximise their utility as a backdrop for understanding malaria pathophysiology, genetically diverse contemporary clinical isolates, essentially wild-type, require comparable characterization. The Oxford Nanopore PCR-free long-read sequencing platform was used to sequence P. knowlesi parasites from archived clinical samples. The sequencing platform and assembly pipeline was designed to facilitate capturing data on important multiple gene families, including the P. knowlesi schizont-infected cell agglutination (SICA) var genes and the Knowlesi-Interspersed Repeats (KIR) genes. The SICAvar and KIR gene families code for antigenically variant proteins that have been difficult to resolve and characterise. Analyses presented here suggest that the family members have arisen through a process of gene duplication, selection pressure and variation. Highly evolving genes tend to be located proximal to genetic elements that drive change rather than regions that support core gene conservation. For example, the virulence-associated P. falciparum erythrocyte membrane protein (PfEMP1) gene family members are restricted to relatively unstable sub-telomeric regions. In contrast the SICAvar and KIR genes are located throughout the genome but as the study presented here shows, they occupy otherwise gene-sparse chromosomal locations. The novel methods presented here offer the malaria research community new tools to generate comprehensive genome sequence data from small clinical samples and renewed insight into these complex real-world parasites. Author summaryMalaria is a potentially severe disease caused by parasite species within genus Plasmodium. Even though the number of cases is in decline there were over 200 million reported cases of malaria in 2019 that resulted in >400,000 deaths. Despite huge research efforts we still do not understand precisely how malaria makes some individuals very ill and by extension how to successfully augment and manage severe disease. Here we developed a novel method to generate comprehensive robust genome sequences from the malaria parasite Plasmodium knowlesi collected from clinical samples. We propose to use the method and initial data generated here to begin to build a resource to identify disease associated genetic traits of P. knowlesi taken from patients samples. In addition to the methodology, what further sets this work apart is the unique opportunity to utilize same-species experimental P. knowlesi parasites to discover a potential role for particular parasite traits in the differential disease progression we observe in patients with P. knowlesi malaria. While we developed the methods to study severe malaria, they are affordable and accessible, and offer the wider malaria research community the means to add context and insight into real-world malaria parasites.

genomics↗