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Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV...

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Autores principales: Xie, Yongjing, Butler, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487901/
https://www.ncbi.nlm.nih.gov/pubmed/35925863
http://dx.doi.org/10.1093/glycob/cwac051
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author Xie, Yongjing
Butler, Michael
author_facet Xie, Yongjing
Butler, Michael
author_sort Xie, Yongjing
collection PubMed
description Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbor embedding and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable “Long-COVID” surveillance to capture the full spectrum of persistent symptoms.
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spelling pubmed-94879012022-09-21 Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19 Xie, Yongjing Butler, Michael Glycobiology Original Article Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbor embedding and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable “Long-COVID” surveillance to capture the full spectrum of persistent symptoms. Oxford University Press 2022-08-04 /pmc/articles/PMC9487901/ /pubmed/35925863 http://dx.doi.org/10.1093/glycob/cwac051 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Xie, Yongjing
Butler, Michael
Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title_full Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title_fullStr Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title_full_unstemmed Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title_short Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19
title_sort serum n-glycomic profiling may provide potential signatures for surveillance of covid-19
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9487901/
https://www.ncbi.nlm.nih.gov/pubmed/35925863
http://dx.doi.org/10.1093/glycob/cwac051
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