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Development of a peptide-based serologic multiplex diagnostic nanodevices to differentially identify Dengue and Zika infections


Infections caused by Dengue virus are one of the most important human diseases transmitted by arthropods in the world. Its diagnosis, however, is not trivial, since the symptomatology is not pathognomonic, and the serological tests available present a series of problems that include low/medium specificity or sensitivity (case of rapid tests), or relatively late responses, depending on the end of the immunological window, as in the case of ELISA assays. As if the Dengue issue was not serious enough, we are currently experiencing an epidemiological nightmare with the introduction of Chikungunya and Zika viruses in the country - considering that these infections are virtually indistinguishable from one another's at a clinical point of view (including Dengue). The distinction between these viruses, therefore, is an absolutely pressing need for the adequacy of public health policies. In this context, the efficient development of a multiplex biosensor sensitive to detections of minimum amounts of antibodies is an essential factor for the success of this research. Thus, the aim of this work is to select non-structural protein 1 (NS1) peptides from both viruses, stably immobilized them at the surface of gold nanoparticles (GNS) with defined optical properties and to use this tool for IgG, IgM and IgA immunoassays. Different peptide immobilization strategies will be tested. The final goal is to develop multiplex lateral flow immunochromatography cassettes using a different color of GNS. According to optical properties of the nanoparticles, the cassettes will be adapted to a portable digital image capture platform, through a mobile application, making this a point-of-care and quantitative device. An algorithm will be developed for the quantification of the samples according to the intensity of the test line. Thus, through the selection of specific peptides for each virus and the use of nanoparticle technology, it is expected to build a fast, sensitive, robust and remote-access sensor for epidemiological updating in real time. (AU)

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