Dataset Information

A comprehensive comparison of Rapid and Deep Plasma Proteomics workflows to identify and quantify biomarkers of Sickle Cell Anaemia

ABSTRACT: Plasma serves as a rich source of protein biomarkers but in-depth proteomic analysis is challenging due to the vast dynamic range of protein abundance. Pre-fractionation of plasma proteins is commonly practiced to improve the proteome coverage but the protocols are time-expensive, suffer from flowchart complexity, and often less reproducible. Here, we explore multiple strategies of shotgun proteomics to optimize biomarker discovery workflows for Sickle Cell Anaemia (SCA) patients from remote India. A deep proteomics workflow via off-line reverse phase Ultra High-Pressure Liquid Chromatography based fractionation of tryptic digested plasma peptides followed by optimized pooling of peptides based on charge and hydrophobicity yielded the best depth of plasma proteome with a trade-off of significantly long experimental time. Alternatively, a rapid analysis of tryptic digested plasma peptides via a shorter gradient mass spectrometry run saves time but quantifies only ~ 50% of the proteins than the deep workflow. Intriguingly, despite the difference in proteome coverage, more than 80% of known FDA and SCA biomarkers quantified in the deep workflow are also quantified in the rapid workflow. Given the practical difficulties of sample collection and plasma preservation in rural India, we propose the deep proteomics workflow for biomarker discovery in smaller cohorts and the rapid workflow for biomarker validations in larger cohorts. Additional targeted proteomics based strategies may be designed for the validation of missing biomarkers in the rapid workflow.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Plasma

SUBMITTER: Swasti Raychaudhuri

LAB HEAD: Dr. Swasti Raychaudhuri

PROVIDER: PXD035348 | Pride | 2024-04-04

REPOSITORIES: Pride

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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.

Dataset Information

A comprehensive comparison of Rapid and Deep Plasma Proteomics workflows to identify and quantify biomarkers of Sickle Cell Anaemia

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