Heinken Almut, Hulshof Timothy Otto, Nap Bram, Martinelli Filippo, Basile Arianna, O'Brolchain Amy, O'Sullivan Neil Francis, Gallagher Celine, Magee Eimer, McDonagh Francesca, Lalor Ian, Bergin Maeve, Evans Phoebe, Daly Rachel, Farrell Ronan, Delaney Rose Marie, Hill Saoirse, McAuliffe Saoirse Roisin, Kilgannon Trevor, Fleming Ronan M T, Thinnes Cyrille C, Thiele Ines
School of Medicine, University of Galway, Galway, Ireland.
Ryan Institute, University of Galway, Galway, Ireland.
bioRxiv. 2023 Oct 3:2023.10.02.560573. doi: 10.1101/2023.10.02.560573.
Computational modelling of microbiome metabolism has proved instrumental to catalyse our understanding of diet-host-microbiome-disease interactions through the interrogation of mechanistic, strain- and molecule-resolved metabolic models. We present APOLLO, a resource of 247,092 human microbial genome-scale metabolic reconstructions spanning 19 phyla and accounting for microbial genomes from 34 countries, all age groups, and five body sites. We explored the metabolic potential of the reconstructed strains and developed a machine learning classifier able to predict with high accuracy the taxonomic strain assignments. We also built 14,451 sample-specific microbial community models, which could be stratified by body site, age, and disease states. Finally, we predicted faecal metabolites enriched or depleted in gut microbiomes of people with Crohn's disease, Parkinson disease, and undernourished children. APOLLO is compatible with the human whole-body models, and thus, provide unprecedented opportunities for systems-level modelling of personalised host-microbiome co-metabolism. APOLLO will be freely available under https://www.vmh.life/.
微生物组代谢的计算模型已被证明有助于通过对机械、菌株和分子解析的代谢模型进行研究,来促进我们对饮食-宿主-微生物组-疾病相互作用的理解。我们展示了APOLLO,这是一个包含247,092个人类微生物基因组规模代谢重建的资源,涵盖19个门,涵盖来自34个国家、所有年龄组和五个身体部位的微生物基因组。我们探索了重建菌株的代谢潜力,并开发了一种能够高精度预测分类菌株归属的机器学习分类器。我们还构建了14,451个样本特异性微生物群落模型,这些模型可以按身体部位、年龄和疾病状态进行分层。最后,我们预测了克罗恩病、帕金森病患者以及营养不良儿童肠道微生物组中富集或消耗的粪便代谢物。APOLLO与人类全身模型兼容,因此为个性化宿主-微生物组共代谢的系统级建模提供了前所未有的机会。APOLLO将在https://www.vmh.life/上免费提供。