2024-09-19
ENA first public
ERC000050
ENA-CHECKLIST
EMBL Heidelberg
INSDC center name
public
INSDC status
ERS21061713
SRA accession
spire_mag_01411879
Submitter Id
Many fragments with little to no review of assembly other than reporting of standard assembly statistics
assembly quality
megahit 1.2.9
assembly software
default
binning parameters
metabat 2.12.1
binning software
human digestive system
broad-scale environmental context
EBI-EMG
broker name
2015
collection date
65.63
%
completeness score
checkm2 0.1.3
completeness software
0.14
%
contamination score
This sample represents a Third Party Annotation (TPA) binned metagenome assembled from the metagenomic run ERR2198692 of study ERP105282.
description
stool
environmental medium
USA
geographic location (country and/or sea)
42.00000000
DD
geographic location (latitude)
71.00000000
DD
geographic location (longitude)
metagenome-assembled genome
investigation type
human gut metagenome
isolation_source
human gut
local environmental context
human gut metagenome
metagenomic source
Phocaeicola vulgatus
organism
The metadata for this study is available on Dropbox: dropbox [DOT] com/sh/kfiu4wb53oemn6j/AAB13sgaKS7MV4lVqXLCxTuMa?dl=0 Abstract: Fecal microbiota transplantation (FMT) is a treatment for microbiome-associated diseases in which gut microbiota are transferred from a healthy donor to a patient. Although the success of FMT requires donor bacteria to engraft in the patient's gut, the forces governing bacterial engraftment in humans are unknown. Here, we use a vast, ongoing clinical experiment - the treatment of recurrent Clostridium difficile infection with FMT - to uncover the rules of engraftment in humans. First, we built a machine learning model that accurately predicts which bacterial species will engraft in a given host. We then developed a maximum-likelihood strain inference method, Strain Finder, allowing us to infer the genotypes of donor strains and to track them through patients' guts over time. Surprisingly, engraftment could be predicted largely from the abundance and phylogeny of bacteria in the donor and the pre-FMT patient. We also found that donor strains within a species engraft in an all-or-nothing manner and that previously undetected strains frequently colonize the patient after FMT. We validated these findings in another disease context, metabolic syndrome, suggesting that the same principles of engraftment extend to other indications. These findings may guide the design of bacterial therapeutics that target diseases ranging from ulcerative colitis to cancer.
project name
SAMEA104393767
sample derived from
Phocaeicola vulgatus
scientific_name
Illumina Genome Analyzer IIx
sequencing method
multi-marker approach
taxonomic identity marker
binned metagenome: spire_mag_01411879
title