# Development of serologic diagnostic test based on in silico predicted synthetic peptides for Brucella canis in dogs

## TL;DR

This paper describes the development of a new, more accurate serologic test for diagnosing canine brucellosis using synthetic peptides predicted through computational methods.

## Contribution

The study introduces a novel diagnostic approach using in silico predicted and validated B cell epitopes for Brucella canis in dogs.

## Key findings

- A combination of 10 synthetic peptides was developed into an iELISA protocol with 100% specificity and 80% sensitivity.
- A multi-epitope protein expressed in E. coli showed similar performance to the iELISA protocol for detecting anti-B. canis antibodies.
- Combining IgM and IgG detection may improve diagnostic sensitivity.

## Abstract

Serologic diagnosis of canine brucellosis caused by Brucella canis remains quite challenging since the currently available methods have considerable limitations, although the relevance and awareness about this zoonotic pathogen is increasing over the past few years. Therefore, the development of novel strategies is highly desirable. In this study, in silico analyses resulted in prediction of B. canis specific B cell epitopes, which were validated by synthesizing the corresponding peptides on a membrane followed by immunobloting with sera from dogs naturally infected with B. canis or uninfected controls as well as by excluding epitopes that cross reacted with sera from cattle and sheep infected with B. abortus and B. ovis, respectively. This approach resulted in the identification of 26 epitopes that reacted exclusively with sera from dogs infected with B. canis, from which the 15 with strongest signal in the immunoblot were selected and synthesized in soluble form for further analyses. The best 10 synthetic peptides (considering the noise to signal ratio) were used in combination as antigens for development of a B. canis specific indirect enzyme-linked immunosorbent assay (iELISA) protocol, which yielded improved specificity to differentiate from other common canine pathogens (Leishmania sp. and Babesia sp.) and an improved performance (100% specificity and 80% sensitivity) when compared to crude bacterial protein extracts used as antigen for iELISA. These selected epitopes were also incorporated in a multi-B. canis epitope protein that was expressed in E. coli and employed as antigen for detection of anti-B. canis IgG and IgM from naturally infected dogs, resulting in analytical performance similar to the iELISA protocol in which synthetic peptides were used as antigens (100% specificity and 75% sensitivity). The results clearly indicate that combination of detection of IgM and IgG may result in higher sensitivity. Therefore, this study provides novel tools for improving the accuracy of serologic diagnosis of canine brucellosis caused by B. canis.