The human body is colonized by a vast number of microorganisms collectively referred to as the human microbiota. One of the main microbiota body sites is the female genital tract, commonly dominated by Lactobacillus spp., in approximately 70% of women. Each individual species can constitute approximately 99% of the ribotypes observed in any individual woman. The most frequently isolated species are Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus jensenii and Lactobacillus iners. Residing at the port of entry of bacterial and viral pathogens, the vaginal Lactobacillus species can create a barrier against pathogen invasion since mainly products of their metabolism secreted in the cervicovaginal fluid can play an important role in the inhibition of bacterial and viral infections. Therefore, a Lactobacillus-dominated microbiota appears to be a good biomarker for a healthy vaginal ecosystem. This balance can be rapidly altered during processes such as menstruation, sexual activity, pregnancy and various infections. An abnormal vaginal microbiota is characterized by an increased diversity of microbial species, leading to a condition known as bacterial vaginosis. Information on the vaginal microbiota can be gathered from the analysis of cervicovaginal fluid, by using the Nugent scoring or the Amsel’s criteria, or at the molecular level by investigating the number and type of Lactobacillus species. However, when translating this to the clinical setting, it should be noted that the absence of a Lactobacillus-dominated microbiota does not appear to directly imply a diseased condition or dysbiosis. Nevertheless, the widely documented beneficial role of vaginal Lactobacillus species demonstrates the potential of data on the composition and activity of lactobacilli as biomarkers for vaginal health. The substantiation and further validation of such biomarkers will allow the design of better targeted probiotic strategies.

Lactobacillus rhamnosus GG (LGG) is one of the most widely used probiotic strains. Various health effects are well documented including the prevention and treatment of gastro-intestinal infections and diarrhea, and stimulation of immune responses that promote vaccination or even prevent certain allergic symptoms. However, not all intervention studies could show a clinical benefit and even for the same conditions, the results are not univocal. Clearly, the host phenotype governed by age, genetics and environmental factors such as the endogenous microbiota, plays a role in whether individuals are responders or non-responders. However, we believe that a detailed knowledge of the bacterial physiology and the LGG molecules that play a key role in its host-interaction capacity is crucial for a better understanding of its potential health benefits. Molecules that were yet identified as important factors governing host interactions include its adhesive pili or fimbriae, its lipoteichoic acid molecules, its major secreted proteins and its galactose-rich exopolysaccharides, as well as specific DNA motifs. Nevertheless, future studies are needed to correlate specific health effects to these molecular effectors in LGG, and also in other probiotic strains.

Bacterial interactions with the environment- and/or host largely depend on the bacterial glycome. The specificities of a bacterial glycome are largely determined by glycosyltransferases (GTs), the enzymes involved in transferring sugar moieties from an activated donor to a specific substrate. Of these GTs their coding regions, but mainly also their substrate specificity are still largely unannotated as most sequence-based annotation flows suffer from the lack of characterized sequence motifs that can aid in the prediction of the substrate specificity. In this work, we developed an analysis flow that uses sequence-based strategies to predict novel GTs, but also exploits a network-based approach to infer the putative substrate classes of these predicted GTs. Our analysis flow was benchmarked with the well-documented GT-repertoire of Campylobacter jejuni NCTC 11168 and applied to the probiotic model Lactobacillus rhamnosus GG to expand our insights in the glycosylation potential of this bacterium. In L. rhamnosus GG we could predict 48 GTs of which eight were not previously reported. For at least 20 of these GTs a substrate relation was inferred. We confirmed through experimental validation our prediction of WelI acting upstream of WelE in the biosynthesis of exopolysaccharides. We further hypothesize to have identified in L. rhamnosus GG the yet undiscovered genes involved in the biosynthesis of glucose-rich glycans and novel GTs involved in the glycosylation of proteins. Interestingly, we also predict GTs with well-known functions in peptidoglycan synthesis to also play a role in protein glycosylation.