Global outbreaks caused by emerging or re-emerging arthropod-borne viruses (arboviruses) are becoming increasingly more common. These pathogens include the mosquito-borne viruses belonging to the and genera. These viruses often cause non-specific or asymptomatic infection, which can confound viral prevalence studies. In addition, many acute phase diagnostic tests rely on the detection of viral components such as RNA or antigen. Standard serological tests are often not reliable for diagnosis after seroconversion and convalescence due to cross-reactivity among flaviviruses. In order to contribute to development efforts for mosquito-borne serodiagnostics, we incubated 137 human sera on individual custom peptide arrays that consisted of over 866 unique peptides in quadruplicate. Our bioinformatics workflow to analyze these data incorporated machine learning, statistics, and B-cell epitope prediction. Here we report the results of our peptide array data analysis, which revealed sets of peptides that have diagnostic potential for detecting past exposure to a subset of the tested human pathogens including Zika virus. These peptides were then confirmed using the well-established ELISA method. These array data, and the resulting peptides can be useful in diverse efforts including the development of new pan-flavivirus antibodies, more accurate epitope mapping, and vaccine development against these viral pathogens.
Copyright: © 2020 Martinez Viedma MdP et al.