A multiepitope fusion protein-based p-ELISA method for diagnosing bovine and goat brucellosis

In recent years, the incidence of brucellosis has increased annually, which has caused tremendous economic losses in agriculture and husbandry in various countries. Therefore, developing rapid, sensitive and specific diagnostic techniques for brucellosis has become critical brucellosis research. Bioinformatics technology was used to predict the B cell epitopes of the main antigen proteins of Brucella, and the validity of each epitope was verified by indirect enzyme-linked immunosorbent assay (iELISA). The verified epitopes were connected in series to construct a multiepitope fusion protein, goat, bovine brucellosis sera, and rabbit sera were collected to verify the antigenicity and specificity of this protein. Then, the fusion protein was used as a diagnostic antigen to construct paper-based ELISA (p-ELISA) technology. A total of 22 effective epitopes were predicted, and a fusion protein was successfully constructed, which showed good antigenicity and specificity. The constructed p-ELISA method was used for the simultaneous detection of bovine and goat brucellosis. ROC curve analysis showed that the sensitivity and specificity of protein detection in goat serum were 98.85% and 98.51%, respectively. The positive and the negative predictive value was 99.29% and 98.15%, respectively. When assessing bovine serum, the sensitivity and specificity were 97.85% and 96.61%, respectively. The positive and the negative predictive value was 98.28% and 97.33%, respectively. This study combined bioinformatics, fusion protein development and p-ELISA technologies to establish a sensitive and specific rapid diagnosis technology for brucellosis that can be used to assess the serum of bovine, goats and other livestock. IMPORTANCEBrucellosis has caused tremendous economic losses in agriculture and husbandry in various countries. Therefore, developing rapid, sensitive and specific diagnostic techniques for brucellosis has become critical brucellosis research. In this study, we used immunoinformatic technology to predict the B cell epitopes in the major outer membrane proteins of Brucella, synthesized polypeptides and coupled them with KLH, screened these polypeptides by iELISA methods, selected effective polypeptides as diagnostic antigens, and established a p-ELISA for brucellosis diagnosis based on a multiepitope fusion protein that can be used to assess the serum of bovine, goats and other livestock.