Integrative analysis of multi-omics data reveals links between human diseases and the gut microbiota
Doktorsavhandling, 2022
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.
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.
multi-omics
gut microbiota
metabolic modeling
type 2 diabetes
machine learning
osteoporosis
metabolomics
Konferensrummet 10’an, Forskarhus 1, Kemigården 4, Chalmers
Opponent: Associate Prof. Mani Arumugam, University of Copenhagen, Denmark
Författare
Peishun Li
Chalmers, Biologi och bioteknik, Systembiologi
Machine learning for data integration in human gut microbiome
Microbial Cell Factories,;Vol. 21(2022)
Reviewartikel
Peishun Li, Boyang Ji, Dimitra Lappa, Abraham S Meijnikman, Lisa M. Olsson, Ömrüm Aydin, et.al, Thue W. Schwartz, Fredrik Bäckhed, Max Nieuwdorp, Louise E. Olofsson, Jens Nielsen. Systems analysis of metabolic responses to a mixed meal test in an obese cohort reveals links between tissue metabolism and the gut microbiota. (Under revision in Communications Medicine)
Peishun Li*, Hao Luo*, Boyang Ji and Jens Nielsen. Metagenomic analysis of type 2 diabetes datasets identifies cross-cohort microbial and metabolic signatures. (Manuscript)
Genome-scale insights into the metabolic versatility of Limosilactobacillus reuteri
BMC Biotechnology,;Vol. 21(2021)
Artikel i vetenskaplig tidskrift
Metabolic Alterations in Older Women With Low Bone Mineral Density Supplemented With Lactobacillus reuteri
JBMR Plus,;Vol. 5(2021)
Artikel i vetenskaplig tidskrift
One-year supplementation with Lactobacillus reuteri ATCC PTA 6475 counteracts a degradation of gut microbiota in older women with low bone mineral density
npj Biofilms and Microbiomes,;Vol. 8(2022)
Artikel i vetenskaplig tidskrift
Within the human intestine, a huge number of microbes live collectively, referred to as the gut microbiota. Dysbiosis of the gut microbiota has been suggested to be associated with human diseases, such as type 2 diabetes (T2D) and osteoporosis characterized by reduced bone mineral density (BMD). Moreover, growing studies have indicated that modulation of the gut microbiota, particularly oral supplementation with probiotics, could be a potential strategy for prevention and treatment of diseases.
This thesis mainly elucidates relationships between the gut microbiota, probiotics and human diseases by integrative analysis of plasma metabolomics and gut metagenomics, using machine learning and metabolic models. This work first systematically investigated metabolisms of both the gut microbiota and human host with (pre) diabetes. A number of gut microbial signatures, including a depleted short-chain fatty acids producing bacterial species and an enriched phenylalanine metabolism capacity of the microbiome, were identified as key factors that might contribute to T2D pathogenesis or abnormal glucose control.
In addition, this thesis systematically explored the effects of orally administrated Lactobacillus reuteri ATCC PTA 6475 on bone metabolism of older women with low BMD. This work found that supplementation with L. reuteri ATCC PTA 6475 had the potential to prevent a deterioration of both the gut microbiota and the host metabolism in older women. This provides a novel insight into the mechanism underlying the beneficial effects of L. reuteri ATCC PTA 6475 on metabolism of the elderly, which could be crucial for developing the novel intervention strategy of osteoporosis.
This thesis mainly elucidates relationships between the gut microbiota, probiotics and human diseases by integrative analysis of plasma metabolomics and gut metagenomics, using machine learning and metabolic models. This work first systematically investigated metabolisms of both the gut microbiota and human host with (pre) diabetes. A number of gut microbial signatures, including a depleted short-chain fatty acids producing bacterial species and an enriched phenylalanine metabolism capacity of the microbiome, were identified as key factors that might contribute to T2D pathogenesis or abnormal glucose control.
In addition, this thesis systematically explored the effects of orally administrated Lactobacillus reuteri ATCC PTA 6475 on bone metabolism of older women with low BMD. This work found that supplementation with L. reuteri ATCC PTA 6475 had the potential to prevent a deterioration of both the gut microbiota and the host metabolism in older women. This provides a novel insight into the mechanism underlying the beneficial effects of L. reuteri ATCC PTA 6475 on metabolism of the elderly, which could be crucial for developing the novel intervention strategy of osteoporosis.
Ämneskategorier
Klinisk medicin
Mikrobiologi inom det medicinska området
Bioinformatik och systembiologi
ISBN
978-91-7905-595-0
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5062
Utgivare
Chalmers
Konferensrummet 10’an, Forskarhus 1, Kemigården 4, Chalmers
Opponent: Associate Prof. Mani Arumugam, University of Copenhagen, Denmark