Use of bioinformatics to model the structure of the cell surface fucosyl transferasegsd on Mycobacterium avium subspecies paratuberculosis (MAP) and develop specific anti-peptide antibodies for the immunolocalization of these pathogens

Abstract

AIM: To model the gsd sequence on the crystal structure of the homologue protein spsA from Bacillus subtilis and identify peptide regions suitable for the generation of specific anti-peptide antibody.

METHODS: Available bioinformatics programs were used to develop a predicted structure for gsd. A 15 residue peptide forming a surface loop in the carboxyterminal domain of gsd was synthesized and used to immunize rabbits. Specific antibody was purified by affinity chromatography on the corresponding synthetic peptide and tested in ELISA for peptide recognition and by immunostaining of in vitro cultured MAP.

RESULTS: A good structural prediction for gsd was obtained showing an aminoterminal GDP-fucose binding domain and a carboxy terminal rhamnose binding domain. The peptide loop TGFSMRQGTDKEFRK in the carbody-terminal domain was synthesized. Affinity purified anti-peptide antibodies showed tight binding to the synthetic peptide in ELISA, and strong immunostaining of MAP which was enhanced by prior treatment of the target organisms with lysosyme. Control M. avium lacking the GS element was not stained.

CONCLUSION: The use of bioinformatics to select appropriate peptide regions on target molecules for the generation of specific antibodies is an effective strategy in the rapid development of reagents for the specific recognition and immunolocalization of MAP.

Key Words: Mycobacterium avium, Paratuberculosis, Glycosyltransferases, Bacillus subtilis, Chromatography, affinity, Antibodies, anti-idiotypic