MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling
Understanding microbial metabolism is crucial for evaluating shifts in human host–microbiome interactions during periods of health and disease. However, the primary hurdle in the realm of constraint-based modeling and genome-scale metabolic models (GEMs) pertaining to host–microbiome interactions la...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Metabolites |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-1989/14/3/132 |
| _version_ | 1797240068508745728 |
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| author | Gholamreza Bidkhori Saeed Shoaie |
| author_facet | Gholamreza Bidkhori Saeed Shoaie |
| author_sort | Gholamreza Bidkhori |
| collection | DOAJ |
| description | Understanding microbial metabolism is crucial for evaluating shifts in human host–microbiome interactions during periods of health and disease. However, the primary hurdle in the realm of constraint-based modeling and genome-scale metabolic models (GEMs) pertaining to host–microbiome interactions lays in the efficient utilization of metagenomic data for constructing GEMs that encompass unexplored and uncharacterized genomes. Challenges persist in effectively employing metagenomic data to address individualized microbial metabolisms to investigate host–microbiome interactions. To tackle this issue, we have created a computational framework designed for personalized microbiome metabolisms. This framework takes into account factors such as microbiome composition, metagenomic species profiles and microbial gene catalogues. Subsequently, it generates GEMs at the microbial level and individualized microbiome metabolisms, including reaction richness, reaction abundance, reactobiome, individualized reaction set enrichment (iRSE), and community models. Using the toolbox, our findings revealed a significant reduction in both reaction richness and GEM richness in individuals with liver cirrhosis. The study highlighted a potential link between the gut microbiota and liver cirrhosis, i.e., increased level of LPS, ammonia production and tyrosine metabolism on liver cirrhosis, emphasizing the importance of microbiome-related factors in liver health. |
| first_indexed | 2024-04-24T18:01:33Z |
| format | Article |
| id | doaj.art-6938e2ecffde4ce9bacaa1ba244bbe90 |
| institution | Directory Open Access Journal |
| issn | 2218-1989 |
| language | English |
| last_indexed | 2024-04-24T18:01:33Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj.art-6938e2ecffde4ce9bacaa1ba244bbe902024-03-27T13:54:05ZengMDPI AGMetabolites2218-19892024-02-0114313210.3390/metabo14030132MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network ModellingGholamreza Bidkhori0Saeed Shoaie1Centre for Host–Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London SE1 9RT, UKCentre for Host–Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London SE1 9RT, UKUnderstanding microbial metabolism is crucial for evaluating shifts in human host–microbiome interactions during periods of health and disease. However, the primary hurdle in the realm of constraint-based modeling and genome-scale metabolic models (GEMs) pertaining to host–microbiome interactions lays in the efficient utilization of metagenomic data for constructing GEMs that encompass unexplored and uncharacterized genomes. Challenges persist in effectively employing metagenomic data to address individualized microbial metabolisms to investigate host–microbiome interactions. To tackle this issue, we have created a computational framework designed for personalized microbiome metabolisms. This framework takes into account factors such as microbiome composition, metagenomic species profiles and microbial gene catalogues. Subsequently, it generates GEMs at the microbial level and individualized microbiome metabolisms, including reaction richness, reaction abundance, reactobiome, individualized reaction set enrichment (iRSE), and community models. Using the toolbox, our findings revealed a significant reduction in both reaction richness and GEM richness in individuals with liver cirrhosis. The study highlighted a potential link between the gut microbiota and liver cirrhosis, i.e., increased level of LPS, ammonia production and tyrosine metabolism on liver cirrhosis, emphasizing the importance of microbiome-related factors in liver health.https://www.mdpi.com/2218-1989/14/3/132microbiomemetabolismgenome scale metabolic modelhost–microbiome interaction |
| spellingShingle | Gholamreza Bidkhori Saeed Shoaie MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling Metabolites microbiome metabolism genome scale metabolic model host–microbiome interaction |
| title | MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling |
| title_full | MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling |
| title_fullStr | MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling |
| title_full_unstemmed | MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling |
| title_short | MIGRENE: The Toolbox for Microbial and Individualized GEMs, Reactobiome and Community Network Modelling |
| title_sort | migrene the toolbox for microbial and individualized gems reactobiome and community network modelling |
| topic | microbiome metabolism genome scale metabolic model host–microbiome interaction |
| url | https://www.mdpi.com/2218-1989/14/3/132 |
| work_keys_str_mv | AT gholamrezabidkhori migrenethetoolboxformicrobialandindividualizedgemsreactobiomeandcommunitynetworkmodelling AT saeedshoaie migrenethetoolboxformicrobialandindividualizedgemsreactobiomeandcommunitynetworkmodelling |