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Proteomics Analysis of Serum from COVID-19 Patients.
Liu, Xiaoling; Cao, Yinghao; Fu, Hongmei; Wei, Jie; Chen, Jianhong; Hu, Jun; Liu, Bende.
  • Liu X; Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.
  • Cao Y; Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Fu H; Department of Nosocomial Infection Management, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
  • Wei J; Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.
  • Chen J; Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.
  • Hu J; Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.
  • Liu B; Department of endocrinology, Liyuan Hospital, Tongji Medical College, Huazhong University of Since and Technology, Wuhan, Hubei 430022, China.
ACS Omega ; 6(11): 7951-7958, 2021 Mar 23.
Article in English | MEDLINE | ID: covidwho-1155694
ABSTRACT
Coronavirus disease 2019 (COVID-19) is a worldwide pandemic. To understand the changes in plasma proteomics upon SARS-CoV-2 infection, we analyzed the protein profiles of plasma samples from 10 COVID-19 patients and 10 healthy volunteers by using the DIA quantitative proteomics technology. We compared and identified differential proteins whose abundance changed upon SARS-CoV-2 infection. Bioinformatic analyses were then conducted for these identified differential proteins. The GO/KEEG database was used for functional annotation and enrichment analysis. The interaction relationship of differential proteins was evaluated with the STRING database, and Cytoscape software was used to conduct network analysis of the obtained data. A total of 323 proteins were detected in all samples. Difference between patients and healthy donors was found in 44 plasma proteins, among which 36 proteins were up-regulated and 8 proteins were down-regulated. GO functional annotation showed that these proteins mostly composed of cellular anatomical entities and proteins involved in biological regulation, cellular processes, transport, and other processes. KEEG functional annotation further showed that these proteins were mainly involved in complement system activation and infectious disease processes. Importantly, a KEEG pathway (natural killer cell-mediated cytotoxicity) was enriched, with three important activators of this pathway, ICAM1/2 and IgG, being up-regulated. Protein-protein interaction (PPI) statistics indicated that, among these 44 proteins, 6 were the most significantly up-regulated (DBH, SHGB, TF, ICAM2, THBS1, and C1RL) while 2 were the most significantly down-regulated (APCS and ORM1). Results from this study showed that a few proteins associated with immune activation were up-regulated in patient plasma. In addition, this study established a method for extraction and quantitative determination of plasma components in convalescent plasma from COVID-19 patients.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: ACS Omega Year: 2021 Document Type: Article Affiliation country: Acsomega.1c00616

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Language: English Journal: ACS Omega Year: 2021 Document Type: Article Affiliation country: Acsomega.1c00616