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(Received: April 18, 2015; Accepted: May 11, 2015)Abstract : Johne’s disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is one of the mostwidespread and economically important diseases in cattle. Current diagnostic methods are based on the detection ofanti-MAP antibodies in serum or isolation of the causative agent. However, these techniques are often not applicablefor cases of subclinical infection due to relatively low sensitivity. Therefore, finding new antigen candidates that stronglyreact with the host immune system had been attempted. To effectively detect infection during the subclinical stage,several antigen candidates were selected based on previous researches. Characteristics of the selected antigen candidateswere analyzed using bioinformatics-based prediction tools. A total of nine antigens were selected (MAP0862,MAP3817c, MAP2077c, MAP0860c, MAP3954, MAP3155c, MAP1204, MAP1087, and MAP2963c) that have MAP-specific and/or high immune responses to infected animals. Using a transmembrane prediction tool, five of the nineantigen candidates were predicted to be membrane protein (MAP3817c, MAP3954, MAP3155c, MAP1087, andMAP1204). Some of the predicted protein structures identified using the I-TASSER server shared similarities withknown proteins found in the Protein Data Bank database (MAP0862, MAP1204, and MAP2077c). In future studies,the characteristics and diagnostic efficiency of the selected antigen candidates will be evaluated.Keywords : antigen, bioinformatics, discovery, Johne’s disease

Discovery of antigens for early detection of Mycobacterium avium subsp. paratuberculosis and analysis of characteristics using bioinformatics tools