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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...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Biochemistry and Molecular Biology
2021
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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 |
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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 |
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