New prebiotic index of foods based on gut microbiome health index (GMHI) using case studies of commercial prebiotics analyzed by in vitro fecal fermentation

Abstract

Abstract Measuring prebiotic activities of foods on human microbiome and providing dietary guidelines on one’s health status are an emerging research topic. However, it is difficult to directly compare different foods using the prebiotic index (PI) proposed in 2003 to determine their prebiotic activities. This ambiguity can be resolved with the gut microbiome health index (GMHI), newly built in 2020, using a consortium of 50 microbial species associated with human health. As a translational application of this index, we used this formula to predict the PI of five commercial prebiotics, fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2`-fucosyllactose (2FL), using in vitro human fecal fermentation. To calculate the GMHI-based PI values, microbial community changes were analyzed at the species level using shotgun sequencing during the fermentation of the prebiotics. As a result, the five compounds exerted a prebiotic effect, increasing the abundance of health-prevalent species, such as Bifidobacterium adolescentis and decreasing health-scarce species. In this context, the GMHI of prebiotics increased after 24 h, but that of the control group without carbon sources decreased. GMHI was highest in the order of IN (0.48 ± 0.06), FOS (0.47 ± 0.03), XOS (0.33 ± 0.02), GOS (0.26 ± 0.02), and 2FL (0.16 ± 0.06), which more accurately reflects the prebiotic effect than PI. Additionally, GMHI stratified the prebiotics more effectively than ecological metrics analyses, such as Shannon diversity, species richness, species evenness, and the inverse Simpson diversity index. This study demonstrates that GMHI-based PI can be used to measure prebiotic activities of several bifidogenic oligosaccharides and perhaps predict the health-beneficial effects of diets after collecting substantial amounts of population-scale meta-datasets.