Abstract

<div><p>In human and porcine cysticercosis caused by the tapeworm <i>Taenia solium</i>, the larval stage (cysts) can infest several tissues including the central nervous system (CNS) and the skeletal muscles (SM). The cyst’s proteomics changes associated with the tissue localization in the host tissues have been poorly studied. Quantitative multiplexed proteomics has the power to evaluate global proteome changes in response to different conditions. Here, using a TMT-multiplexed strategy we identified and quantified over 4,200 proteins in cysts obtained from the SM and CNS of pigs, of which 891 were host proteins. To our knowledge, this is the most extensive intermixing of host and parasite proteins reported for tapeworm infections.Several antigens in cysticercosis, <i>i</i>.<i>e</i>., GP50, paramyosin and a calcium-binding protein were enriched in skeletal muscle cysts. Our results suggested the occurrence of tissue-enriched antigen that could be useful in the improvement of the immunodiagnosis for cysticercosis. Using several algorithms for epitope detection, we selected 42 highly antigenic proteins enriched for each tissue localization of the cysts. Taking into account the fold changes and the antigen/epitope contents, we selected 10 proteins and produced synthetic peptides from the best epitopes. Nine peptides were recognized by serum antibodies of cysticercotic pigs, suggesting that those peptides are antigens. Mixtures of peptides derived from SM and CNS cysts yielded better results than mixtures of peptides derived from a single tissue location, however the identification of the ‘optimal’ tissue-enriched antigens remains to be discovered. Through machine learning technologies, we determined that a reliable immunodiagnostic test for porcine cysticercosis required at least five different antigenic determinants.</p></div

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