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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

NATURE BIOTECHNOLOGY

ISSN

1087-0156

e-ISSN

1087-0156

Svazek periodika

41

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

22

Strana od-do

1320-1331

Kód UT WoS článku

000916149200003

EID výsledku v databázi Scopus

2-s2.0-85146589321