Bacteroides uniformis
ENA first public
2024-09-21
INSDC center name
EMBL Heidelberg
INSDC status
public
Submitter Id
spire_mag_01448287
assembly quality
Many fragments with little to no review of assembly other than reporting of standard assembly statistics
assembly software
megahit 1.2.9
binning parameters
default
binning software
metabat 2.12.1
broad-scale environmental context
human digestive system
broker name
EBI-EMG
collection date
missing: third party data
completeness score
71.22
completeness software
checkm2 0.1.3
contamination score
1.1
environmental medium
not provided
geographic location (country and/or sea)
not provided
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
SAMEA3664860
sample name
spire_mag_01448287
scientific_name
Bacteroides uniformis
sequencing method
Illumina HiSeq 2500
taxonomic identity marker
multi-marker approach