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New Proteomic Signatures to Distinguish Between Zika and Dengue Infections.

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.

SUBMITTER: Allgoewer K

PROVIDER: S-EPMC8042398 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The 2015-2016 Zika virus (ZIKV) epidemic in the Americas and the Caribbean demonstrated that clinical assays to detect, distinguish, and characterize immune responses to flaviviral infections are needed. ZIKV and dengue virus (DENV) are mosquito-transmitted flaviviruses sharing overlapping geographic distributions and have significant sequence similarities that can increase the potential for antibody and T cell cross-reaction. Using nonstructural protein 1-based enzyme-linked immunosorbent assays (ELISAs), we determined the serostatus of individuals living in a region of DENV and ZIKV endemicity in Brazil, identifying individuals with primary DENV (pDENV) and primary ZIKV (pZIKV), ZIKV with primary DENV (ZIKVwpDENV), and secondary DENV (sDENV) infections; the presence of pDENV and pZIKV was further confirmed by neutralization tests. Development of an enzyme-linked immunosorbent spot (ELISPOT) assay for DENV and ZIKV structural and nonstructural (NS) protein antigens enabled us to distinguish infections by these viruses based on T cell responses and to characterize those responses. We found that gamma interferon (IFN-?) and tumor necrosis factor alpha (TNF-?) T cell responses to NS3 differentiated DENV and ZIKV infections with 94% sensitivity and 92% specificity. In general, we also showed that pDENV and sDENV cases and pZIKV and ZIKVwpDENV cases elicit similar T cell response patterns and that HIV-infected individuals show T cell responses that are lower than those shown by HIV-negative individuals. These results have important implications for DENV and ZIKV diagnostic and vaccine development and provide critical insights into the T cell response in individuals with multiple flaviviral infections.IMPORTANCE The potential for antibody and T cell cross-reactions to DENV and ZIKV, flaviviruses that cocirculate and can sequentially infect individuals, has complicated diagnostic and vaccine development. Our serological data show that antibodies to nonstructural protein 1 can distinguish sequential human infections by DENV and ZIKV. The development of a simple and inexpensive assay also enables the differentiation of DENV and ZIKV infections based on characterization of T cell responses. Our T cell data reveal strong response patterns that are similar in nature to those seen with individuals with one or multiple DENV infections and with individuals with only primary ZIKV infection and ZIKV-infected individuals with previous DENV exposure. The characterization of T cell responses in a serologically validated group of individuals is of relevance to the development of vaccines and immunotherapeutics against these global threats.

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New Proteomic Signatures to Distinguish Between Zika and Dengue Infections.

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