Tecnun, University of Navarra, San Sebastián, Spain.
Biomedical Engineering Center, University of Navarra, Campus Universitario, Pamplona, Navarra, Spain.
Nat Commun. 2021 Aug 5;12(1):4728. doi: 10.1038/s41467-021-25056-x.
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.
理解饮食和肠道微生物群在人类健康背景下的相互作用是个性化营养的一个关键问题。基因组规模的代谢网络和基于约束的建模方法有望系统地解决这一复杂问题。然而，当应用于营养问题时，现有重建中的一个主要问题是关于肠道微生物群代谢的饮食化合物的信息有限。在这里，我们提出了 AGREDA，这是对人类肠道微生物群饮食代谢的扩展重建。AGREDA 增加了 209 种存在于人类饮食中的化合物的降解途径，主要是酚类化合物，这是一类与人类健康和营养密切相关的代谢物。我们表明，AGREDA 在预测肠道微生物群中特定饮食的输出代谢物方面优于现有重建。使用来自具有不同临床条件的西班牙儿童的粪便样本的 16S rRNA 基因测序数据，我们说明了 AGREDA 建立饮食和肠道微生物群之间相关代谢相互作用的潜力。
