Multiomics data analysis workflow to assess severity in longitudinal plasma samples of COVID-19 patients

多组学数据分析工作流程,用于评估 COVID-19 患者纵向血浆样本的严重程度

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作者:Sakshi Rajoria, Mehar Un Nissa, Kruthi Suvarna, Harsh Khatri, Sanjeeva Srivastava

Abstract

Elucidation of molecular markers related to the mounted immune response is crucial for understanding the disease pathogenesis. In this article, we present the mass-spectrometry-based metabolomic and proteomic data of blood plasma of COVID-19 patients collected at two-time points, which showed a transition from non-severe to severe conditions during these time points. Metabolites were extracted and subjected to mass spectrometric analysis using the Q-Exactive mass spectrometer. For proteomic analysis, depleted plasma samples were tryptic digested and subjected to mass spectrometry analysis. The expression of a few significant proteins was also validated by employing the targeted proteomic approach of multiple reaction monitoring (MRM). Integrative pathway analysis was performed with the significant proteins to obtain biological insights into disease severity. For discussion and more information on the dataset creation, please refer to the related full-length article (Suvarna et al., 2021).

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