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

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

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

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.

Original languageEnglish
JournalNature Biotechnology
DOIs
Publication statusE-pub ahead of print - 19 Jan 2023

Fingerprint

Dive into the research topics of 'Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine'. Together they form a unique fingerprint.

Cite this