| 1. |
- Babaei, Parizad, 1990, et al.
(författare)
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Challenges in modeling the human gut microbiome
- 2018
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Ingår i: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 36:8, s. 682-686
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- El-Semman, Ibrahim, 1977, et al.
(författare)
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Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism
- 2016
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Ingår i: Molecular Biosystems. - : Royal Society of Chemistry. - 1742-206X .- 1742-2051. ; 12:5, s. 1496-1506
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Tidskriftsartikel (refereegranskat)abstract
- Hepatitis C virus (HCV) infection is a worldwide healthcare problem; however, traditional treatment methods have failed to cure all patients, and HCV has developed resistance to new drugs. Systems biology-based analyses could play an important role in the holistic analysis of the impact of HCV on hepatocellular metabolism. Here, we integrated HCV assembly reactions with a genome-scale hepatocyte metabolic model to identify metabolic targets for HCV assembly and metabolic alterations that occur between different HCV progression states (cirrhosis, dysplastic nodule, and early and advanced hepatocellular carcinoma (HCC)) and healthy liver tissue. We found that diacylglycerolipids were essential for HCV assembly. In addition, the metabolism of keratan sulfate and chondroitin sulfate was significantly changed in the cirrhosis stage, whereas the metabolism of acyl-carnitine was significantly changed in the dysplastic nodule and early HCC stages. Our results explained the role of the upregulated expression of BCAT1, PLOD3 and six other methyltransferase genes involved in carnitine biosynthesis and S-adenosylmethionine metabolism in the early and advanced HCC stages. Moreover, GNPAT and BCAP31 expression was upregulated in the early and advanced HCC stages and could lead to increased acyl-CoA consumption. By integrating our results with copy number variation analyses, we observed that GNPAT, PPOX and five of the methyltransferase genes (ASH1L, METTL13, SMYD2, TARBP1 and SMYD3), which are all located on chromosome 1q, had increased copy numbers in the cancer samples relative to the normal samples. Finally, we confirmed our predictions with the results of metabolomics studies and proposed that inhibiting the identified targets has the potential to provide an effective treatment strategy for HCV-associated liver disorders.
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| 3. |
- Ghaffari Nouran, Pouyan, 1980, et al.
(författare)
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Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling
- 2015
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 5, s. 8183-
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Tidskriftsartikel (refereegranskat)abstract
- Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted 85 antimetabolites that can inhibit growth of, or even kill, any of the cell lines, while at the same time not being toxic for 83 different healthy human cell types. 60 of these antimetabolites were found to inhibit growth in all cell lines. Finally, we experimentally validated one of the predicted antimetabolites using two cell lines with different phenotypic origins, and found that it is effective in inhibiting the growth of these cell lines. Using immunohistochemistry, we also showed high or moderate expression levels of proteins targeted by the validated antimetabolite. Identified anti-growth factors for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies.
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| 4. |
- Kovatcheva-Datchary, Petia, et al.
(författare)
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Simplified Intestinal Microbiota to Study Microbe-Diet-Host Interactions in a Mouse Model
- 2019
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Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 26:13
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Tidskriftsartikel (refereegranskat)abstract
- The gut microbiota can modulate human metabolism through interactions with macronutrients. However, microbiota-diet-host interactions are difficult to study because bacteria interact in complex food webs in concert with the host, and many of the bacteria are not yet characterized. To reduce the complexity, we colonize mice with a simplified intestinal microbiota (SIM) composed of ten sequenced strains isolated from the human gut with complementing pathways to metabolize dietary fibers. We feed the SIM mice one of three diets (chow [fiber rich], high-fat/high-sucrose, or zero-fat/high-sucrose diets [both low in fiber]) and investigate (1) how dietary fiber, saturated fat, and sucrose affect the abundance and transcriptome of the SIM community, (2) the effect of microbe-diet interactions on circulating metabolites, and (3) how microbiota-diet interactions affect host metabolism. Our SIM model can be used in future studies to help clarify how microbiota-diet interactions contribute to metabolic diseases.
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| 5. |
- Mardinoglu, Adil, 1982, et al.
(författare)
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The gut microbiota modulates host amino acid and glutathione metabolism in mice
- 2015
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- The gut microbiota has been proposed as an environmental factor that promotes the progression of metabolic diseases. Here, we investigated how the gut microbiota modulates the global metabolic differences in duodenum, jejunum, ileum, colon, liver, and two white adipose tissue depots obtained from conventionally raised (CONV-R) and germ-free (GF) mice using gene expression data and tissue-specific genome-scale metabolic models (GEMs). We created a generic mouse metabolic reaction (MMR) GEM, reconstructed 28 tissue-specific GEMs based on proteomics data, and manually curated GEMs for small intestine, colon, liver, and adipose tissues. We used these functional models to determine the global metabolic differences between CONV-R and GF mice. Based on gene expression data, we found that the gut microbiota affects the host amino acid (AA) metabolism, which leads to modifications in glutathione metabolism. To validate our predictions, we measured the level of AAs and N-acetylated AAs in the hepatic portal vein of CONV-R and GF mice. Finally, we simulated the metabolic differences between the small intestine of the CONV-R and GF mice accounting for the content of the diet and relative gene expression differences. Our analyses revealed that the gut microbiota influences host amino acid and glutathione metabolism in mice.
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| 6. |
- Rosario, Dorines, et al.
(författare)
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Understanding the representative gut microbiota dysbiosis in metformin-treated Type 2 diabetes patients using genome-scale metabolic modeling
- 2018
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:JUN
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Tidskriftsartikel (refereegranskat)abstract
- Dysbiosis in the gut microbiome composition may be promoted by therapeutic drugs such as metformin, the world's most prescribed antidiabetic drug. Under metformin treatment, disturbances of the intestinal microbes lead to increased abundance of Escherichia spp., Akkermansia muciniphila, Subdoligranulum variabile and decreased abundance of Intestinibacter bartlettii. This alteration may potentially lead to adverse effects on the host metabolism, with the depletion of butyrate producer genus. However, an increased production of butyrate and propionate was verified in metformin-treated Type 2 diabetes (T2D) patients. The mechanisms underlying these nutritional alterations and their relation with gut microbiota dysbiosis remain unclear. Here, we used Genome-scale Metabolic Models of the representative gut bacteria Escherichia spp., I. bartlettii, A. muciniphila, and S. variabile to elucidate their bacterial metabolism and its effect on intestinal nutrient pool, including macronutrients (e.g., amino acids and short chain fatty acids), minerals and chemical elements (e.g., iron and oxygen). We applied flux balance analysis (FBA) coupled with synthetic lethality analysis interactions to identify combinations of reactions and extracellular nutrients whose absence prevents growth. Our analyses suggest that Escherichia sp. is the bacteria least vulnerable to nutrient availability. We have also examined bacterial contribution to extracellular nutrients including short chain fatty acids, amino acids, and gasses. For instance, Escherichia sp. and S. variabile may contribute to the production of important short chain fatty acids (e.g., acetate and butyrate, respectively) involved in the host physiology under aerobic and anaerobic conditions. We have also identified pathway susceptibility to nutrient availability and reaction changes among the four bacteria using both FBA and flux variability analysis. For instance, lipopolysaccharide synthesis, nucleotide sugar metabolism, and amino acid metabolism are pathways susceptible to changes in Escherichia sp. and A. muciniphila. Our observations highlight important commensal and competing behavior, and their association with cellular metabolism for prevalent gut microbes. The results of our analysis have potential important implications for development of new therapeutic approaches in T2D patients through the development of prebiotics, probiotics, or postbiotics.
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| 7. |
- Shoaie, Saeed, 1985
(författare)
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Metabolic Modeling of the Gut Microbiome-Host Interactions and Meta’omics Integration
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A large number of microbes with different strain types occupy the human gut. These gut inhabitant microbes have key roles in decomposition of indigestible dietary macronutrients before they are metabolised by the host. The gut microbiome has a clear effect on human health and perturbations in its diversity may lead to the development of disorders through changes in metabolic functions. To date, different studies have shown the association of the gut microbiome with metabolic disorders such as obesity, type2 diabetes and certain cancers. It has also been shown that there is a complex interaction between microbe-microbe, host-microbe and microbe-diet, and elucidation of the mechanisms behind these interactions and associations remains a challenge. Due to the extreme complexity of cellular metabolism, mathematical models may be employed for deciphering the role of its individual elements and may thereby assist in providing an increased understanding of these interactions. The emerging research field of systems biology can integrate different highthroughput data, in this case metagenomics and metatranscriptomics, through the use of mathematical models and thus provide a holistic interpretation for this complex system. In this context, genome-scale metabolic modeling has been applied to gain increased knowledge in important biotechnology applications.This thesis presents approaches to facilitate understanding of the causalities and go beyond theassociation analysis by considering the interactions between microbiome, host and diet. Usinggenome-scale metabolic models (GEMs), we investigated the contribution of key species in theoverall metabolism of the gut microbiome. We developed methods and generated stand-alonesoftware to apply for different case studies on modeling of gut microbiome and finally addressed relevant biological questions. First, GEMs for three bacteria being representatives of dominant phyla in the human gut microbiome were reconstructed. This modeling approach allowed us to establish effective resources for understanding the microbe interactions in the gut. Increasing the number of relevant GEMs representing all key microbes in the human gut resulted in more complexity and therefore we developed the CASINO toolbox, a comprehensive software platform for the analysis of microbial communities. CASINO was validated based on in-vitro studies and thereafter applied to human studies that showed its capability to predict the phenotype of individuals based on their dietary pattern and gut microbes’ abundances. Finally, the application of CASINO was extended and used for modeling of the interactions between gut microbiota and hostmetabolism. The overall metabolic differences between germ-free and conventionally raised micewere revealed through the use of CASINO. In conclusion, this thesis provides a new approach tohuman gut analysis by using valuable resources (GEMs) and novel methods (CASINO). As suchit contributes to advancing the role of metabolic modeling in human health and designing newclinical interventions.
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| 8. |
- Shoaie, Saeed, 1985, et al.
(författare)
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Quantifying Diet-Induced Metabolic Changes of the Human Gut Microbiome
- 2015
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131 .- 1932-7420. ; 22:2, s. 320-331
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Tidskriftsartikel (refereegranskat)abstract
- The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.
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