Bioinformatic prediction of the antigenic epitopes of recombinant ferritin of Echinococcus granulosus

Abstract

Echinococcosis is a zoonotic parasitic disease affecting humans and other mammals, which is mainly caused Echinococcus at larval stages. It is predominantly endemic in Chinese pasture regions, including Xinjiang, Qinghai, Gansu and Ningxia. The aim of the present study was to predict the T- and B-combined epitopes of Echinococcus granulosus (Eg). ferritin, and to analyze its secondary structure using online software. Prediction of the T- and B-combined epitopes of Eg. ferritin was performed using IEDB, SYFPEITHI and LEPS software, which are used to identify common areas of T- and B-cells. The results of the present study identified several potential antigenic epitopes of Eg. ferritin, including seven B-cell antigen epitope amino acid sequences with high values: 8-16, 54-61, 70-75, 80-90, 103-109, 117-124 and 167-173; and four T-cell antigen epitope amino acid sequences with high values: 85-93, 105-113, 133-141 and 157-165. Furthermore, a combined epitope region comprising an 105-109 amino acid sequence was identified. In conclusion, using bioinformatic methods, the present study confirmed the existence of Eg. ferritin on four T-cell antigen epitopes, seven B-cell antigen epitopes, and one T- and B-combined epitope region. These findings provide significant information for further investigation of the antigenicity of Eg. ferritin and the development of highly efficient epitope vaccines.