Metagenome-assembled genome: MGYG000041133
Eubacteriales bacterium
This sample represents a Third Party Annotation (TPA) Metagenome-assembled genome generated from the metagenomic sample ERS971966 of study ERP012929.
ENA first public
2026-06-12
INSDC center name
EMG
INSDC status
public
Submitter Id
MGYG000041133
assembly quality
Many fragments with little to no review of assembly other than reporting of standard assembly statistics
assembly software
missing: third party data
binning parameters
missing: third party data
binning software
missing: third party data
broad-scale environmental context
human-associated habitat
broker name
EBI-EMG
collection date
missing: third party data
completeness score
99.98
completeness software
CheckM2_v1.1.0
contamination score
0.46
environmental medium
missing: third party data
geographic location (country and/or sea)
missing: third party data
geographic location (latitude)
missing: third party data
geographic location (longitude)
missing: third party data
investigation type
metagenome-assembled genome
isolation_source
human gut metagenome
local environmental context
human gut
metagenomic source
human gut metagenome
project name
Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type-II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in a 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences.
sample derived from
ERS971966
sample name
MGYG000041133
scientific_name
Eubacteriales bacterium
sequencing method
missing: third party data
taxonomic identity marker
multi-marker approach