The proteomic characteristics of airway mucus from critical ill COVID-19 patients
Abstract Background: The pandemic of the coronavirus disease 2019 (COVID-19) has brought a global public health crisis. However, the pathogenesis underlying COVID-19 are barely understood. Methods: In this study, we performed proteomic analyses of airway mucus obtained by bronchoscopy from severe COVID-19 patients. In total, 2351 and 2073 proteins were identified and quantified in COVID-19 patients and healthy controls, respectively. Results: Among them, 92 differentiated expressed proteins (DEPs) (46 up-regulated and 46 down-regulated) were found with a fold change > 1.5 or < 0.67 and a p-value < 0.05, and 375 proteins were uniquely present in airway mucus from COVID-19 patients. Pathway and network enrichment analyses revealed that the 92 DEPs were mostly associated with metabolic, complement and coagulation cascades, lysosome, and cholesterol metabolism pathways, and the 375 COVID-19 only proteins were mainly enriched in amino acid degradation (Valine, Leucine and Isoleucine degradation), amino acid metabolism (beta-Alanine, Tryptophan, Cysteine and Methionine metabolism), oxidative phosphorylation, phagosome, and cholesterol metabolism pathways. Conclusions: This study aims to provide fundamental data for elucidating proteomic changes of COVID-19, which may implicate further investigation of molecular targets directing at specific therapy..
| Medienart: |
|
|---|
Preprint| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
ResearchSquare.com - (2022) vom: 28. Juli Zur Gesamtaufnahme - year:2022 |
|---|
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Zhang, Zili [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| doi: |
10.21203/rs.3.rs-52433/v1 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
XRA034230351 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | XRA034230351 | ||
| 003 | DE-627 | ||
| 005 | 20230429191301.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 220113s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.21203/rs.3.rs-52433/v1 |2 doi | |
| 035 | |a (DE-627)XRA034230351 | ||
| 035 | |a (ResearchSquare)10.21203/rs.3.rs-52433/v1 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Zhang, Zili |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a The proteomic characteristics of airway mucus from critical ill COVID-19 patients |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a Abstract Background: The pandemic of the coronavirus disease 2019 (COVID-19) has brought a global public health crisis. However, the pathogenesis underlying COVID-19 are barely understood. Methods: In this study, we performed proteomic analyses of airway mucus obtained by bronchoscopy from severe COVID-19 patients. In total, 2351 and 2073 proteins were identified and quantified in COVID-19 patients and healthy controls, respectively. Results: Among them, 92 differentiated expressed proteins (DEPs) (46 up-regulated and 46 down-regulated) were found with a fold change > 1.5 or < 0.67 and a p-value < 0.05, and 375 proteins were uniquely present in airway mucus from COVID-19 patients. Pathway and network enrichment analyses revealed that the 92 DEPs were mostly associated with metabolic, complement and coagulation cascades, lysosome, and cholesterol metabolism pathways, and the 375 COVID-19 only proteins were mainly enriched in amino acid degradation (Valine, Leucine and Isoleucine degradation), amino acid metabolism (beta-Alanine, Tryptophan, Cysteine and Methionine metabolism), oxidative phosphorylation, phagosome, and cholesterol metabolism pathways. Conclusions: This study aims to provide fundamental data for elucidating proteomic changes of COVID-19, which may implicate further investigation of molecular targets directing at specific therapy. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Wang, Tao |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Fei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Airu |e verfasserin |4 aut | |
| 700 | 1 | |a Gu, Guoping |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Jieping |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Jingyi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Jincun |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Yiming |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Xiaoqing |e verfasserin |4 aut | |
| 700 | 1 | |a Zhong, Nanshan |e verfasserin |4 aut | |
| 700 | 1 | |a Lu, Wenju |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t ResearchSquare.com |g (2022) vom: 28. Juli |
| 773 | 1 | 8 | |g year:2022 |g day:28 |g month:07 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.lfs.2021.119046 |z lizenzpflichtig |3 Volltext |
| 856 | 4 | 0 | |u http://dx.doi.org/10.21203/rs.3.rs-52433/v1 |z kostenfrei |3 Volltext |
| 912 | |a GBV_XRA | ||
| 912 | |a SSG-OLC-PHA | ||
| 951 | |a AR | ||
| 952 | |j 2022 |b 28 |c 07 | ||