Galacto-oligosaccharides (GOS) are linked to various health benefits, such as the relief of symptoms of constipation. Part of the beneficial effects of GOS are thought to be the consequence of their bifidogenic effect, stimulating the growth of several Bifidobacterium species in vivo. However, GOS may exert additional effects by directly stimulating other bacterial species or by effects that bifidobacteria may have on other commensals in the gut. To get a better insight into the potential health effects induced by GOS, a good understanding of the gut ecosystem, the role of GOS and bifidobacteria is important. An increasing number of 16S DNA profiling and metagenomics studies have led to an expanding inventory of genera, species and strains that can be found in the human gut. To investigate the potential connection of these commensals with GOS and bifidobacteria, we have undertaken a text-mining study to chart the literature landscape around these commensals. To this end, we created controlled vocabularies describing GOS, a large set of gut commensals and a number of terms related to gut health, which were used to mine the entire MEDLINE database. Co-occurrence text-mining revealed that a large number of commensals found in the gut have a connection with Bifidobacterium species and with gut health effects. Word frequency analysis provided more insight into the functional nature of these relationships. Combined co-occurrence search results pointed to putative novel health benefits indirectly linked to bifidobacteria and GOS. The potential beneficial effects of GOS on the protection of epithelial function and epithelial barrier impairment and appendicitis are interesting novel leads. The text-mining approach reported here revealed a number of novel leads through which GOS could exert health effects and that could be investigated in dedicated studies.
Sijbers, A. M., Schoemaker, R. J. W., Nauta, A., & Alkema, W. (2020). Revealing new leads for the impact of galacto-oligosaccharides on gut commensals and gut health benefits through text mining. Beneficial Microbes, 11(3), 283–302. https://doi.org/10.3920/BM2019.0105