| 1. |
- Fromentin, S., et al.
(författare)
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Microbiome and metabolome features of the cardiometabolic disease spectrum
- 2022
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 28:2, s. 303-314
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Tidskriftsartikel (refereegranskat)abstract
- By studying individuals along a spectrum of cardiometabolic disease and adjusting for effects of lifestyle and medication, this investigation identifies alterations of the metabolome and microbiome from dysmetabolic conditions, such as obesity and type 2 diabetes, to ischemic heart disease. Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages-acute coronary syndrome, chronic IHD and IHD with heart failure-and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.
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| 2. |
- Li, Peishun, 1988, et al.
(författare)
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Metabolic Alterations in Older Women With Low Bone Mineral Density Supplemented With Lactobacillus reuteri
- 2021
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Ingår i: JBMR Plus. - : Wiley. - 2473-4039. ; 5:4
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Tidskriftsartikel (refereegranskat)abstract
- JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research. Osteoporosis and its associated fractures are highly prevalent in older women. Recent studies have shown that gut microbiota play important roles in regulating bone metabolism. A previous randomized controlled trial (RCT) found that supplementation with Lactobacillus reuteri ATCC PTA 6475 (L.reuteri) led to substantially reduced bone loss in older women with low BMD. However, the total metabolic effects of L. reuteri supplementation on older women are still not clear. In this study, a post hoc analysis (not predefined) of serum metabolomic profiles of older women from the previous RCT was performed to investigate the metabolic dynamics over 1 year and to evaluate the effects of L. reuteri supplementation on human metabolism. Distinct segregation of the L. reuteri and placebo groups in response to the treatment was revealed by partial least squares-discriminant analysis. Although no individual metabolite was differentially and significantly associated with treatment after correction for multiple testing, 97 metabolites responded differentially at any one time point between L. reuteri and placebo groups (variable importance in projection score >1 and p value <0.05). These metabolites were involved in multiple processes, including amino acid, peptide, and lipid metabolism. Butyrylcarnitine was particularly increased at all investigated time points in the L. reuteri group compared with placebo, indicating that the effects of L. reuteri on bone loss are mediated through butyrate signaling. Furthermore, the metabolomic profiles in a case (low BMD) and control population (high BMD) of elderly women were analyzed to confirm the associations between BMD and the identified metabolites regulated by L. reuteri supplementation. The amino acids, especially branched-chain amino acids, showed association with L. reuteri treatment and with low BMD in older women, and may serve as potential therapeutic targets. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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| 3. |
- Li, Peishun, 1988
(författare)
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Integrative analysis of multi-omics data reveals links between human diseases and the gut microbiota
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 4. |
- Li, Peishun, 1988, et al.
(författare)
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Machine learning for data integration in human gut microbiome
- 2022
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Ingår i: Microbial Cell Factories. - : Springer Science and Business Media LLC. - 1475-2859. ; 21:1
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Forskningsöversikt (refereegranskat)abstract
- Recent studies have demonstrated that gut microbiota plays critical roles in various human diseases. High-throughput technology has been widely applied to characterize the microbial ecosystems, which led to an explosion of different types of molecular profiling data, such as metagenomics, metatranscriptomics and metabolomics. For analysis of such data, machine learning algorithms have shown to be useful for identifying key molecular signatures, discovering potential patient stratifications, and particularly for generating models that can accurately predict phenotypes. In this review, we first discuss how dysbiosis of the intestinal microbiota is linked to human disease development and how potential modulation strategies of the gut microbial ecosystem can be used for disease treatment. In addition, we introduce categories and workflows of different machine learning approaches, and how they can be used to perform integrative analysis of multi-omics data. Finally, we review advances of machine learning in gut microbiome applications and discuss related challenges. Based on this we conclude that machine learning is very well suited for analysis of gut microbiome and that these approaches can be useful for development of gut microbe-targeted therapies, which ultimately can help in achieving personalized and precision medicine.
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| 5. |
- Li, Peishun, 1988, et al.
(författare)
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Metabolic engineering of human gut microbiome: Recent developments and future perspectives
- 2023
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Ingår i: Metabolic Engineering. - 1096-7176 .- 1096-7184. ; 79, s. 1-13
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Forskningsöversikt (refereegranskat)abstract
- Many studies have demonstrated that the gut microbiota is associated with human health and disease. Manipulation of the gut microbiota, e.g. supplementation of probiotics, has been suggested to be feasible, but subject to limited therapeutic efficacy. To develop efficient microbiota-targeted diagnostic and therapeutic strategies, metabolic engineering has been applied to construct genetically modified probiotics and synthetic microbial consortia. This review mainly discusses commonly adopted strategies for metabolic engineering in the human gut microbiome, including the use of in silico, in vitro, or in vivo approaches for iterative design and construction of engineered probiotics or microbial consortia. Especially, we highlight how genome-scale metabolic models can be applied to advance our understanding of the gut microbiota. Also, we review the recent applications of metabolic engineering in gut microbiome studies as well as discuss important challenges and opportunities.
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| 6. |
- Li, Peishun, 1988, et al.
(författare)
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One-year supplementation with Lactobacillus reuteri ATCC PTA 6475 counteracts a degradation of gut microbiota in older women with low bone mineral density
- 2022
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Ingår i: npj Biofilms and Microbiomes. - : Springer Science and Business Media LLC. - 2055-5008. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Recent studies have shown that probiotic supplementation has beneficial effects on bone metabolism. In a randomized controlled trial (RCT) we demonstrated that supplementation of Lactobacillus reuteri ATCC PTA 6475 reduced bone loss in older women with low bone mineral density. To investigate the mechanisms underlying the effect of L. reuteri ATCC PTA 6475 on bone metabolism, 20 women with the highest changes (good responders) and the lowest changes (poor responders) in tibia total volumetric BMD after one-year supplementation were selected from our previous RCT. In the current study we characterized the gut microbiome composition and function as well as serum metabolome in good responders and poor responders to the probiotic treatment as a secondary analysis. Although there were no significant differences in the microbial composition at high taxonomic levels, gene richness of the gut microbiota was significantly higher (P < 0.01 by the Wilcoxon rank-sum test) and inflammatory state was improved (P < 0.05 by the Wilcoxon signed-rank test) in the good responders at the end of the 12-month daily supplementation. Moreover, detrimental changes including the enrichment of E. coli (adjusted P < 0.05 by DESeq2) and its biofilm formation (P < 0.05 by GSA) observed in the poor responders were alleviated in the good responders by the treatment. Our results indicate that L. reuteri ATCC PTA 6475 supplementation has the potential to prevent a deterioration of the gut microbiota and inflammatory status in elderly women with low bone mineral density, which might have beneficial effects on bone metabolism.
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| 7. |
- Luo, Hao, 1992, et al.
(författare)
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Genome-scale insights into the metabolic versatility of Limosilactobacillus reuteri
- 2021
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Ingår i: BMC Biotechnology. - : Springer Science and Business Media LLC. - 1472-6750. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Limosilactobacillus reuteri (earlier known as Lactobacillus reuteri) is a well-studied lactic acid bacterium, with some specific strains used as probiotics, that exists in different hosts such as human, pig, goat, mouse and rat, with multiple body sites such as the gastrointestinal tract, breast milk and mouth. Numerous studies have confirmed the beneficial effects of orally administered specific L. reuteri strains, such as preventing bone loss and promoting regulatory immune system development. L. reuteri ATCC PTA 6475 is a widely used strain that has been applied in the market as a probiotic due to its positive effects on the human host. Its health benefits may be due, in part, to the production of beneficial metabolites. Considering the strain-specific effects and genetic diversity of L. reuteri strains, we were interested to study the metabolic versatility of these strains. Results In this study, we aimed to systematically investigate the metabolic features and diversities of L. reuteri strains by using genome-scale metabolic models (GEMs). The GEM of L. reuteri ATCC PTA 6475 was reconstructed with a template-based method and curated manually. The final GEM iHL622 of L. reuteri ATCC PTA 6475 contains 894 reactions and 726 metabolites linked to 622 metabolic genes, which can be used to simulate growth and amino acids utilization. Furthermore, we built GEMs for the other 35 L. reuteri strains from three types of hosts. The comparison of the L. reuteri GEMs identified potential metabolic products linked to the adaptation to the host. Conclusions The GEM of L. reuteri ATCC PTA 6475 can be used to simulate metabolic capabilities and growth. The core and pan model of 35 L. reuteri strains shows metabolic capacity differences both between and within the host groups. The GEMs provide a reliable basis to investigate the metabolism of L. reuteri in detail and their potential benefits on the host.
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| 8. |
- Luo, Hao, 1992, et al.
(författare)
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Modeling the metabolic dynamics at the genome-scale by optimized yield analysis
- 2023
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Ingår i: Metabolic Engineering. - : Elsevier BV. - 1096-7176 .- 1096-7184. ; 75, s. 119-130
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Tidskriftsartikel (refereegranskat)abstract
- The hybrid cybernetic model (HCM) approach is a dynamic modeling framework that integrates enzyme synthesis and activity regulation. It has been widely applied in bioreaction engineering, particularly in the simulation of microbial growth in different mixtures of carbon sources. In a HCM, the metabolic network is decomposed into elementary flux modes (EFMs), whereby the network can be reduced into a few pathways by yield analysis. However, applying the HCM approach on conventional genome-scale metabolic models (GEMs) is still a challenge due to the high computational demands. Here, we present a HCM strategy that introduced an optimized yield analysis algorithm (opt-yield-FBA) to simulate metabolic dynamics at the genome-scale without the need for EFMs calculation. The opt-yield-FBA is a flux-balance analysis (FBA) based method that can calculate optimal yield solutions and yield space for GEM. With the opt-yield-FBA algorithm, the HCM strategy can be applied to get the yield spaces and avoid the computational burden of EFMs, and it can therefore be applied for developing dynamic models for genome-scale metabolic networks. Here, we illustrate the strategy by applying the concept to simulate the dynamics of microbial communities.
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| 9. |
- Ye, Ling Qun, 1982, et al.
(författare)
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Carbohydrate active enzymes are affected by diet transition from milk to solid food in infant gut microbiota
- 2019
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Ingår i: FEMS microbiology ecology. - : Oxford University Press (OUP). - 1574-6941 .- 0168-6496. ; 95:11
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Tidskriftsartikel (refereegranskat)abstract
- Infants experience a dramatic change in their food in the first year after birth when they shift from breast milk to solid food. This results in a large change in presence of indigestible polysaccharides, a primary energy resource of gut microbes. How the gut microbiota adapts to this dietary shift has not been well examined. Here, by using metagenomics data, we studied carbohydrate-active enzymes (CAZymes) of gut microbiota, which are essential enzymes catalyzing the breakdown of polysaccharides, during this dietary shift. We developed a new approach to categorize CAZyme families by food intake and found CAZyme families associated with milk or solid food. We also found CAZymes with most abundance in 12 months infants that are not associated with solid food or milk but may be related to modulating carbohydrates in the mucus. Additionally, the abundance of gut CAZymes were found to be affected by many other factors, including delivery modes and life style in adults. Taken together, our findings provide novel insights into the dynamic change of gut CAZymes in early human life and provide potential markers for food interference or gut microbiota restoration.
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