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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41340%2F23%3A94096" target="_blank" >RIV/60460709:41340/23:94096 - isvavai.cz</a>

Result on the web

<a href="https://www.nature.com/articles/s41587-022-01628-0" target="_blank" >https://www.nature.com/articles/s41587-022-01628-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41587-022-01628-0" target="_blank" >10.1038/s41587-022-01628-0</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

NATURE BIOTECHNOLOGY

ISSN

1087-0156

e-ISSN

1087-0156

Volume of the periodical

41

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

22

Pages from-to

1320-1331

UT code for WoS article

000916149200003

EID of the result in the Scopus database

2-s2.0-85146589321