1. Antigen discovery by bioinformatics analysis and peptide microarray for the diagnosis of cystic echinococcosis.
- Author
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Batisti Biffignandi G, Vola A, Sassera D, Najafi-Fard S, Gomez Morales MA, Brunetti E, Teggi A, Goletti D, Petrone L, and Tamarozzi F
- Subjects
- Animals, Humans, Antigens, Helminth, Peptides, Enzyme-Linked Immunosorbent Assay methods, Computational Biology, Echinococcosis diagnosis, Echinococcus granulosus
- Abstract
Background: Cystic echinococcosis (CE), caused by Echinococcus granulosus sensu lato, is a neglected zoonosis. Its diagnosis relies on imaging, supported by serology, while only imaging is useful for staging and follow-up. Since diagnostic tools and expertise are not widely available, new accurate and easily implementable assays for the diagnosis and follow-up of CE are highly needed., Methodology/principal Findings: We aimed to identify new E. granulosus antigens through a bioinformatics selection applied to the parasite genome, followed by peptide microarray screening and validation in ELISA, using independent panels of sera from patients with hepatic CE and clinically relevant controls. From 950 proteins selected in silico, 2,379 peptides were evaluated by microarray for IgG reactivity and eight candidates selected for validation. Reactivity to one peptide was significantly higher in the CE group (p = 0.044), but had suboptimal diagnostic accuracy., Conclusions/significance: Here we performed bioinformatics analysis and peptide microarray for antigen discovery, useful for the diagnosis of CE. Eight candidates were selected and validated. Reactivity to one peptide associated to CE but had suboptimal diagnostic accuracy. Importantly, the database developed in this study may be used to identify other antigenic candidates for CE diagnosis and follow-up., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Batisti Biffignandi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
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