爱尔兰戈尔韦大学Ines Thiele团队近期取得重要工作进展。他们研究了用于个性化医疗的7302株人类微生物基因组尺度的代谢重建。相关研究成果2023年1月19日在线发表于《自然—生物技术》杂志上。

据介绍，人体微生物组影响多种常用处方药的疗效和安全性。设计结合微生物代谢的精确医学方法需要菌株和分子分辨率的、可扩展的计算建模。

研究人员对之前人类肠道微生物基因组尺度的代谢重建资源进行了扩展。AGORA2（通过重建和分析组装肠道生物，第2版）包含7302株菌株，包括98种药物在菌株分辨率上的药物降解和生物转化能力，并根据比较基因组学和文献检索进行了广泛筛选。微生物重建在三个独立组装的实验数据集上表现非常好，精确度为0.72至0.84，超过了其它重建资源，并预测已知的微生物药物转化，精确度为0.81。研究人员证明，AGORA2通过预测616名癌症患者和对照组肠道微生物组的药物转化潜力，实现了个性化的，菌株分辨率的建模，该药物转化潜力在个体之间差异很大，与年龄、性别、体重指数和疾病分期相关。

总之，AGORA2是人类微生物组的知识库，为宿主-微生物组代谢相互作用的个性化预测分析铺平了道路。

附：英文原文

Title: Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

Author: Heinken, Almut, Hertel, Johannes, Acharya, Geeta, Ravcheev, Dmitry A., Nyga, Malgorzata, Okpala, Onyedika Emmanuel, Hogan, Marcus, Magnsdttir, Stefana, Martinelli, Filippo, Nap, Bram, Preciat, German, Edirisinghe, Janaka N., Henry, Christopher S., Fleming, Ronan M. T., Thiele, Ines

Issue&Volume: 2023-01-19

Abstract: The human microbiome influences the efficacy and safety of a wide variety of commonly prescribed drugs. Designing precision medicine approaches that incorporate microbial metabolism would require strain- and molecule-resolved, scalable computational modeling. Here, we extend our previous resource of genome-scale metabolic reconstructions of human gut microorganisms with a greatly expanded version. AGORA2 (assembly of gut organisms through reconstruction and analysis, version 2) accounts for 7,302 strains, includes strain-resolved drug degradation and biotransformation capabilities for 98 drugs, and was extensively curated based on comparative genomics and literature searches. The microbial reconstructions performed very well against three independently assembled experimental datasets with an accuracy of 0.72 to 0.84, surpassing other reconstruction resources and predicted known microbial drug transformations with an accuracy of 0.81. We demonstrate that AGORA2 enables personalized, strain-resolved modeling by predicting the drug conversion potential of the gut microbiomes from 616 patients with colorectal cancer and controls, which greatly varied between individuals and correlated with age, sex, body mass index and disease stages. AGORA2 serves as a knowledge base for the human microbiome and paves the way to personalized, predictive analysis of host–microbiome metabolic interactions.

DOI: 10.1038/s41587-022-01628-0

Source: https://www.nature.com/articles/s41587-022-01628-0