Integrative analysis of multi-omics data reveals links between human diseases and the gut microbiota

Sammanfattning: The gut microbiota plays a critical role in human diseases, including type 2 diabetes (T2D) and osteoporosis. Especially, probiotics have been suggested to provide potential intervention strategies for improving human health. This thesis focuses on elucidating the interrelationships between the gut microbiota, probiotics and human diseases by integrative analysis of plasma metabolomics and gut metagenomics, using machine learning (ML) and genome-scale metabolic model (GEM). This work is mainly structured into two parts, including a systematical investigation of: (I) associations between the gut microbiota and T2D, (II) the effects of probiotic Lactobacillus reuteri ATCC PTA 6475 on bone metabolism of the elderly.      For the first part, a derivative of phenylalanine was identified as a potential link between the gut microbiota and T2D. It was associated with insulin resistance and might contribute to the metabolic imbalance of (pre)diabetes. By performing a systematical analysis of four metagenomic datasets, several short-chain fatty acids (SCFAs)-producing bacteria and metabolic reactions were consistently identified to be important for predicting T2D status across different studies. For the second part, this work revealed that supplementation with L. reuteri ATCC PTA 6475 prevented detrimental alterations in the metabolisms of both the gut microbiota and the elderly as well as increased the microbial gene richness, which might link the beneficial effects of probiotic L. reuteri ATCC PTA 6475 to bone metabolism. In addition, it was demonstrated that the use of ML and GEM have the potential to identify key disease-related metabolic signatures of single L. reuteri strain, the entire gut microbes, or the human host, based on the metabolomics and metagenomics data.      Taken together, this work provides novel insights into links between the gut microbiota and the human diseases as well as the positive effects of L. reuteri ATCC PTA 6475 on bone metabolism by integrating omics data using ML and GEMs.