Identification of putative adhesins and carbohydrate ligands of Lactobacillus paracasei using a combinatorial in silico and glycomics microarray profiling approach

Commensal bacteria must colonize host mucosal surfaces to exert health-promoting properties, and bind to gastrointestinal tract (GIT) mucins via their cell surface adhesins. Considerable effort has been directed towards discovery of pathogen adhesins and their ligands to develop anti-infective strategies; however, little is known about the lectin-like adhesins and associated carbohydrate ligands in commensals. In this study, an in silico approach was used to detect surface exposed adhesins in the human commensal Lactobacillus paracasei subsp. paracasei, a promising probiotic commonly used in dairy product fermentation that presents anti-microbial activity. Of the 13 adhesin candidates, 3 sortase-dependent pili clusters were identified in this strain and expression of the adhesin candidate genes was confirmed in vitro. Mass spectrometry analysis confirmed the presence of surface adhesin elongation factor Tu and the chaperonin GroEL, but not pili expression. Whole cells were subsequently incubated on microarrays featuring a panel of GIT mucins from nine different mammalian species and two human-derived cell lines and a library of carbohydrate structures. Binding profiles were compared to those of two known pili-producing lactobacilli, L. johnsonii and L. rhamnosus and all Lactobacillus species displayed overlapping but distinct signatures, which may indicate different abilities for regiospecific GIT colonization. In addition, L. paracasei whole cells favoured binding to α-(2 → 3)-linked sialic acid and α-(1 → 2)-linked fucose-containing carbohydrate structures including blood groups A, B and O and Lewis antigens x, y and b. This study furthers our understanding of host-commensal cross-talk by identifying potential adhesins and specific GIT mucin and carbohydrate ligands and provides insight into the selection of colonization sites by commensals in the GIT.