Cargando…

New Proteomic Signatures to Distinguish Between Zika and Dengue Infections

Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika a...

Descripción completa

Detalles Bibliográficos
Autores principales: Allgoewer, Kristina, Maity, Shuvadeep, Zhao, Alice, Lashua, Lauren, Ramgopal, Moti, Balkaran, Beni N., Liu, Liyun, Purushwani, Savita, Arévalo, Maria T., Ross, Ted M., Choi, Hyungwon, Ghedin, Elodie, Vogel, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042398/
https://www.ncbi.nlm.nih.gov/pubmed/33582300
http://dx.doi.org/10.1016/j.mcpro.2021.100052
_version_ 1783678119566114816
author Allgoewer, Kristina
Maity, Shuvadeep
Zhao, Alice
Lashua, Lauren
Ramgopal, Moti
Balkaran, Beni N.
Liu, Liyun
Purushwani, Savita
Arévalo, Maria T.
Ross, Ted M.
Choi, Hyungwon
Ghedin, Elodie
Vogel, Christine
author_facet Allgoewer, Kristina
Maity, Shuvadeep
Zhao, Alice
Lashua, Lauren
Ramgopal, Moti
Balkaran, Beni N.
Liu, Liyun
Purushwani, Savita
Arévalo, Maria T.
Ross, Ted M.
Choi, Hyungwon
Ghedin, Elodie
Vogel, Christine
author_sort Allgoewer, Kristina
collection PubMed
description Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ∼70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections.
format Online
Article
Text
id pubmed-8042398
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher American Society for Biochemistry and Molecular Biology
record_format MEDLINE/PubMed
spelling pubmed-80423982021-04-15 New Proteomic Signatures to Distinguish Between Zika and Dengue Infections Allgoewer, Kristina Maity, Shuvadeep Zhao, Alice Lashua, Lauren Ramgopal, Moti Balkaran, Beni N. Liu, Liyun Purushwani, Savita Arévalo, Maria T. Ross, Ted M. Choi, Hyungwon Ghedin, Elodie Vogel, Christine Mol Cell Proteomics Research Distinguishing between Zika and dengue virus infections is critical for accurate treatment, but we still lack detailed understanding of their impact on their host. To identify new protein signatures of the two infections, we used next-generation proteomics to profile 122 serum samples from 62 Zika and dengue patients. We quantified >500 proteins and identified 13 proteins that were significantly differentially expressed (adjusted p-value < 0.05). These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain function. We successfully validated expression differences with Carbonic Anhydrase 2 in both the original and an independent sample set. Three of the differentially expressed proteins, i.e., Fibrinogen Alpha, Platelet Factor 4 Variant 1, and Pro-Platelet Basic Protein, predicted Zika virus infection at a ∼70% true-positive and 6% false-positive rate. Further, we showed that intraindividual temporal changes in protein signatures can disambiguate diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can provide new resources that serve to distinguish between different viral infections. American Society for Biochemistry and Molecular Biology 2021-02-12 /pmc/articles/PMC8042398/ /pubmed/33582300 http://dx.doi.org/10.1016/j.mcpro.2021.100052 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research
Allgoewer, Kristina
Maity, Shuvadeep
Zhao, Alice
Lashua, Lauren
Ramgopal, Moti
Balkaran, Beni N.
Liu, Liyun
Purushwani, Savita
Arévalo, Maria T.
Ross, Ted M.
Choi, Hyungwon
Ghedin, Elodie
Vogel, Christine
New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title_full New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title_fullStr New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title_full_unstemmed New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title_short New Proteomic Signatures to Distinguish Between Zika and Dengue Infections
title_sort new proteomic signatures to distinguish between zika and dengue infections
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042398/
https://www.ncbi.nlm.nih.gov/pubmed/33582300
http://dx.doi.org/10.1016/j.mcpro.2021.100052
work_keys_str_mv AT allgoewerkristina newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT maityshuvadeep newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT zhaoalice newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT lashualauren newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT ramgopalmoti newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT balkaranbenin newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT liuliyun newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT purushwanisavita newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT arevalomariat newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT rosstedm newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT choihyungwon newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT ghedinelodie newproteomicsignaturestodistinguishbetweenzikaanddengueinfections
AT vogelchristine newproteomicsignaturestodistinguishbetweenzikaanddengueinfections