An extended reconstruction of human gut microbiota metabolism of dietary compounds
Understanding how diet and gut microbiota interact in the context of human health is a key question in personalized nutrition. Genome-scale metabolic networks and constraint-based modeling approaches are promising to systematically address this complex problem. However, when applied to nutritional q...
| Authors: | , , , , , , , , , , , , , |
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| Format: | article |
| Publication Date: | 2021 |
| Country: | España |
| Institution: | Universidad de Navarra |
| Repository: | Dadun. Depósito Académico Digital de la Universidad de Navarra |
| Language: | English |
| OAI Identifier: | oai:dadun.unav.edu:10171/114486 |
| Online Access: | https://hdl.handle.net/10171/114486 |
| Access Level: | Open access |
| Keyword: | Diet Gut microbiota Personalized nutrition Genome-scale metabolic networks Constraint-based |
| Summary: | Understanding how diet and gut microbiota interact in the context of human health is a key question in personalized nutrition. Genome-scale metabolic networks and constraint-based modeling approaches are promising to systematically address this complex problem. However, when applied to nutritional questions, a major issue in existing reconstructions is the limited information about compounds in the diet that are metabolized by the gut microbiota. Here, we present AGREDA, an extended reconstruction of diet metabolism in the human gut microbiota. AGREDA adds the degradation pathways of 209 compounds present in the human diet, mainly phenolic compounds, a family of metabolites highly relevant for human health and nutrition. We show that AGREDA outperforms existing reconstructions in predicting diet-specific output metabolites from the gut microbiota. Using 16S rRNA gene sequencing data of faecal samples from Spanish children representing different clinical conditions, we illustrate the potential of AGREDA to establish relevant metabolic interactions between diet and gut microbiota. |
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