Please use this identifier to cite or link to this item:
https://doi.org/10.1016/j.mcpro.2021.100052
DC Field | Value | |
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dc.title | New proteomic signatures to distinguish between zika and dengue infections | |
dc.contributor.author | Allgoewer, Kristina | |
dc.contributor.author | Maity, Shuvadeep | |
dc.contributor.author | Zhao, Alice | |
dc.contributor.author | Lashua, Lauren | |
dc.contributor.author | Ramgopal, Moti | |
dc.contributor.author | Balkaran, Beni N. | |
dc.contributor.author | Liu, Liyun | |
dc.contributor.author | Purushwani, Savita | |
dc.contributor.author | Arévalo, M.T. | |
dc.contributor.author | Ross, Ted M. | |
dc.contributor.author | Choi, Hyungwon | |
dc.contributor.author | Ghedin, Elodie | |
dc.contributor.author | Vogel, Christine | |
dc.date.accessioned | 2022-10-13T01:15:57Z | |
dc.date.available | 2022-10-13T01:15:57Z | |
dc.date.issued | 2021-01-01 | |
dc.identifier.citation | Allgoewer, Kristina, Maity, Shuvadeep, Zhao, Alice, Lashua, Lauren, Ramgopal, Moti, Balkaran, Beni N., Liu, Liyun, Purushwani, Savita, Arévalo, M.T., Ross, Ted M., Choi, Hyungwon, Ghedin, Elodie, Vogel, Christine (2021-01-01). New proteomic signatures to distinguish between zika and dengue infections. Molecular and Cellular Proteomics 20 : 100052. ScholarBank@NUS Repository. https://doi.org/10.1016/j.mcpro.2021.100052 | |
dc.identifier.issn | 1535-9476 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/232868 | |
dc.description.abstract | 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. © 2021 THE AUTHORS. Published by Elsevier Inc on behalf of American Society for Biochemistry and Molecular Biology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). | |
dc.publisher | American Society for Biochemistry and Molecular Biology Inc. | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Scopus OA2021 | |
dc.type | Article | |
dc.contributor.department | SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH | |
dc.description.doi | 10.1016/j.mcpro.2021.100052 | |
dc.description.sourcetitle | Molecular and Cellular Proteomics | |
dc.description.volume | 20 | |
dc.description.page | 100052 | |
Appears in Collections: | Elements Staff Publications |
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