Introduction: Brucellosis is a widespread zoonotic disease that poses a considerable challenge to global public health. Existing diagnostic methods for this condition, such as serological assays and bacterial culture, encounter difficulties due to their limited specificity and high operational complexity. Therefore, there is an urgent need for the development of enhanced diagnostic approaches for brucellosis.
Methods: Tandem mass tag (TMT) proteomic analysis was conducted on the wild-type strain Brucella abortus (B. abortus) DT21 and the vaccine strain B. abortus A19 to identify proteins with high expression levels. The proteins that exhibited high expression in the wild-type strain were selected based on the proteomic results. Subsequently, B-cell linear epitopes were predicted using multiple computational tools, including ABCpred, SVMTriP, BCPred, and Bepipred Linear Epitope Prediction 2.0. These epitopes were concatenated to construct a multiepitope fusion protein. Following prokaryotic expression and purification, an indirect enzyme-linked immunosorbent assay (iELISA) was developed. A total of 100 positive serum samples, 96 negative serum samples, and 40 serum samples from patients infected with other pathogens were collected and analyzed using the established iELISA. Furthermore, the protein was assessed for its capability to differentiate human brucellosis from lipopolysaccharide (LPS).
Results: Proteomic analysis revealed the presence of 152 proteins with high expression levels in the wild-type strains. A multiepitope fusion protein, comprising a total of 32 predicted B-cell linear epitopes, was successfully prepared. The results from the iELISA indicated that the multiepitope fusion protein exhibited exceptional diagnostic performance, evidenced by an area under the receiver operating characteristic curve (AUC) of 0.9576, a sensitivity of 0.9300, and a specificity of 0.8542. In comparison to the commonly utilized LPS antigen, the fusion protein demonstrated a reduced level of cross-reactivity.
Conclusions: A novel multiepitope fusion protein has been successfully developed utilizing bioinformatics and TMT proteomics technology. This fusion protein demonstrates significant potential as a diagnostic antigen for brucellosis, exhibiting high sensitivity and specificity.
Keywords: bioinformatics; brucellosis; diagnosis; multiepitope fusion protein; proteomics.
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