Dataset Information

Proteomic analysis of human Sertoli cells-derived extracellular vesicles

ABSTRACT: We performed a proteomic analysis of EVs derived from human Sertoli cells, aiming to obtain the profiling of the proteins in these EVs to explore their possible roles in the development of testis.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Primary Cell

SUBMITTER: Xiao-Hui Tan

LAB HEAD: Rui-Li Guan

PROVIDER: PXD030640 | Pride | 2021-12-24

REPOSITORIES: Pride

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Publications

Extracellular vesicles derived from human Sertoli cells: characterizations, proteomic analysis, and miRNA profiling.

Tan Xiao-Hui XH Gu Sheng-Ji SJ Tian Wen-Jie WJ Song Wen-Peng WP Gu Yang-Yang YY Yuan Yi-Ming YM Li Xue-Song XS Xin Zhong-Cheng ZC Kim Sae Woong SW Guan Rui-Li RL Bae Woong Jin WJ

Molecular biology reports 20220402 6

<h4>Background</h4>Extracellular vesicles (EVs) contain thousands of proteins and nucleic acids, playing an important role in cell-cell communications. Sertoli cells have been essential in the testis as a "nurse cell". However, EVs derived from human Sertoli cells (HSerCs) have not been well investigated.<h4>Methods</h4>EVs were isolated from HSerCs via ultracentrifugation and characterized by transmission electron microscopy, tunable resistive pulse sensing, and Western blotting. The cargo carr ...[more]

PMID: 35366759

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Project description:Background: Acute coronary syndromes (ACS) are associated with aberrant gene expression and epigenetic mechanisms. In particular, de novo DNA methylation is typically linked to gene silencing, but its role in heart disease remains not fully understood. Extracellular vesicles (EVs) are active components in cellular communication for their ability to carry a plethora of signalling biomolecules, thus representing a promising new diagnostic/therapeutic approach in cardiovascular diseases (CVDs). Indeed, there is the need of novel biomarkers for ACS prediction and timely detection. Purpose: We hypothesized that specific epigenetic signals can be carried by EVs. In this regard, we isolated and characterized circulating EVs from ACS patients and evaluated their potential role to influence DNA methylation in target cells. Methods: Circulating EVs were recovered, by ultracentrifugation, from plasma samples of 19 ACS patients and 50 healthy subjects (HS). Nanoparticle tracking analysis (NTA) and western blot (WB) were used to confirm the EVs integrity and purity. Peripheral blood mononuclear cells (PBMCs) of volunteer donors were treated with both ACS and HS derived EVs and genomic DNA was extracted to perform epigenome wide analysis through Reduced Representation Bisulfite Sequencing. ShinyGO, PANTHER, and STRING tools were interrogated to perform GO and PPI network analyses. Flow Cytometry, qRT-PCR, and WB analysis were also performed to evaluate and validate both intra-vesicular and intra-cellular signals. Results: Plasma ACS-derived EVs showed a significant up-regulation of DNA methyltransferases (DNMTs) gene expression levels as compared to HS (P<0.001). Specifically, de novo methylation transcripts, as DNMT3A and DNMT3B were significantly increased in plasma ACS-EVs. DNA methylation analysis of PBMCs from volunteer donors treated with HS- and ACS-derived EVs showed that RNF166 and CCND3 genes resulted the most hyper- and hypo-methylated, respectively, after by ACS-EV treatment. In addition, PPI network analysis specifically evidenced the subnetwork with SRC, as a hub gene, connecting it to NOTCH1, FOXO3, CDC42, IKBKG, RXRA, DGKG, known as important genes already involved in the onset of CVDs. Surprising, other novel genes, BAIAP2, SYP, CHL1, and SHB, which were hypomethylated, were found significantly overexpressed in PBMCs (P<0.005), underlying the fundamental modulating properties of EV cargo in atherosclerosis. Conclusions: These findings support the significant role of ACS plasma-derived EVs, inducing de novo DNA methylation signals, and modulating specific signaling pathways in target cells.

			Action	DRS
	HserC.raw	Raw
	MaxquantResult.zip	Other
	Parameters.xlsx	Xlsx
	Peptides.xlsx	Xlsx
	ProteinGroups.xlsx	Xlsx