This study aimed to examine whether probiotics, which suppressed the differentiation of splenic T cells into type 2 helper T (Th2) cells and induced into regulatory T cells in vitro, alleviate allergic rhinitis (AR) and gut microbiota disturbance. We isolated Bifidobacterium longum IM55 and Lactobacillus plantarum IM76 from human faecal microbiota and kimchi, respectively, and examined their effects on ovalbumin (OVA)-induced AR and gut microbiota disturbance in mice. Treatment with IM55, IM76, or their probiotic mixture (PM) significantly reduced OVA-induced allergic nasal symptoms and blood immunoglobulin E (IgE) levels in mice. These also reduced OVA-induced interleukin (IL)-4 and IL-5 levels in nasal tissues and bronchoalveolar lavage fluid (BALF) but increased OVA-suppressed IL-10 levels. Treatment with IM55, IM76, or PM reduced OVA-induced increase in the populations of mast cells, eosinophils, and Th2 cells and increased OVA-suppressed population of regulatory T cells in the BALF. Treatment with IM55, IM76, or PM also inhibited OVA-induced expression of IL-5 in lung and colon tissues and restored OVA-disturbed composition of gut microbiota Proteobacteria, Bacteroidetes, and Actinobacteria. These results suggest that IM55 and IM67 can alleviate AR by restoring Th2/Treg imbalance and gut microbiota disturbance.

Age-related gut microbes and urine metabolites were investigated in 568 healthy individuals using metataxonomics and metabolomics. The richness and evenness of the fecal microbiota significantly increased with age, and the abundance of 16 genera differed between the young and old groups. Additionally, 17 urine metabolites contributed to the differences between the young and old groups. Among the microbes that differed by age, Bacteroides and Prevotella 9 were confirmed to be correlated with some urine metabolites. The machine learning algorithm eXtreme gradient boosting (XGBoost) was shown to produce the best performing age predictors, with a mean absolute error of 5.48 years. The accuracy of the model improved to 4.93 years with the inclusion of urine metabolite data. This study shows that the gut microbiota and urine metabolic profiles can be used to predict the age of healthy individuals with relatively good accuracy.