Digital serology for parallel parasitic disease detection

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The proposed project aims to build a diagnostic test for chronic T. cruzi infection and Chagas disease that not only improves testing performance but that can be readily integrated with similarly developed tests for most clinically important parasitoses. Current assays for Chagas disease, and other parasitic infections, lack desired levels of specificity, and require multiple independent assays and testing formats. Consequently, testing a single specimen for several different clinically important parasitic diseases becomes cost prohibitive and time consuming, delaying disease detection and treatment. We propose to address this problem by creating a single, all-in-one diagnostic test able to detect ten or more different clinically important parasitic diseases. Importantly, the proposed strategy could be expanded to a nearly arbitrary number of infectious diseases without resultant increases in final test cost. Towards a multiplexed parasitic disease test, we will first create an improved test for Chagas disease, that impacts about 350,000 individuals in the US, and 8 million in the Americas. To accomplish this, we will apply bacterial display peptide libraries, next-generation sequencing, and computational bioinformatics to identify a set of motifs and consensus peptides corresponding to antigenic peptide epitopes that when combined yield optimal sensitivity and specificity values in the discovery set. The motif and peptide panels will be validated using an independent specimen set. Assay reproducibility and stability will be measured. This project may thus lead to clinically useful tests to improve the rates of detection parasitic diseases their resultant complications.