Development and evaluation of multiepitope fusion proteins for serological diagnosis of animal brucellosis.

Brucellosis, a zoonotic disease caused by Brucella spp., leads to severe reproductive issues in livestock and economic losses. Current serological diagnostics using lipopolysaccharide (LPS) antigens often exhibit cross-reactivity, reducing diagnostic specificity. This study aimed to develop multiepitope fusion proteins based on Brucella B-cell epitopes using bioinformatics tools and the Immune Epitope Database (IEDB) to enhance diagnostic accuracy. B-cell epitopes from major Brucella outer membrane proteins and other antigenic proteins were predicted using bioinformatics tools (BepiPred, ABCpred, and IEDB). Two fusion proteins were designed and produced. The diagnostic performance of the two fusion proteins was evaluated using indirect enzyme-linked immunosorbent assay with 198 small ruminant serum samples and 232 bovine serum samples in comparison with conventional LPS and Rose Bengal antigen. Sensitivity, specificity, and cross-reactivity were evaluated. Both fusion proteins exhibited high sensitivity and specificity. For ruminant samples, Fusion Protein 2 achieved an area under the curve (AUC) of 0.9849, with sensitivity and specificity of 93.90% and 97.26%, respectively. For bovine samples, it showed an AUC of 0.9664, sensitivity of 92.71%, and specificity of 90.44%. Minimal cross-reactivity with other pathogens was observed, indicating high diagnostic specificity. The developed multiepitope fusion proteins demonstrated superior diagnostic performance. These proteins provide a novel tool for rapid and accurate diagnosis of brucellosis, with potential applications in vaccine development and disease control. Future work will focus on optimizing fusion protein design and expanding clinical validation.IMPORTANCEBrucellosis, a zoonotic disease caused by Brucella spp., poses a significant threat to livestock industries and human health. Current serological diagnostic methods using LPS antigens often suffer from cross-reactivity, leading to reduced diagnostic specificity. This study addresses this challenge by developing multiepitope fusion proteins based on Brucella B-cell epitopes. Using bioinformatics tools and IEDB, we designed and produced two fusion proteins and evaluated their diagnostic performance. The results demonstrated that these fusion proteins exhibited high sensitivity and specificity, with minimal cross-reactivity, offering a more accurate tool for brucellosis diagnosis. This advancement not only enhances the effectiveness of disease surveillance and control but also provides a foundation for potential vaccine development. The successful application of these fusion proteins in serological diagnosis highlights their importance in improving the accuracy and reliability of brucellosis detection, which is crucial for minimizing economic losses and public health risks associated with the disease.