2024-09-20
ENA first public
ERC000050
ENA-CHECKLIST
EMBL Heidelberg
INSDC center name
public
INSDC status
ERS21074191
SRA accession
spire_mag_02675728
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
2015-09-24
collection date
87.43
%
completeness score
checkm2 0.1.3
completeness software
0.79
%
contamination score
This sample represents a Third Party Annotation (TPA) binned metagenome assembled from the metagenomic run ERR3461571 of study ERP116574.
description
stool
environmental medium
USA
geographic location (country and/or sea)
33.45480560
DD
geographic location (latitude)
-112.36427778
DD
geographic location (longitude)
metagenome-assembled genome
investigation type
human gut metagenome
isolation_source
human gut
local environmental context
human gut metagenome
metagenomic source
Bacteroides uniformis
organism
Microbial ecology has witnessed tremendous progress over the last decade empowered by new sequencing technologies. These innovations in DNA sequencing resulted in a paradigm shift concerning our understanding of pathogenic processes and gave birth to a new scientific concept, namely the “pathobiome”. In the pathobiome concept, the microbial community containing a pathogenic agent exerts a major influence on the persistence, transmission and evolution of the pathogen. It is therefore mandatory to identify those species that contribute, either as partners or antagonists, to pathogen’s survival, extinction or dispersal by applying concepts and approaches of systems biology. Developing multi-meta-omic systems biology frameworks would allow us to go beyond the identification of mere statistical co-occurrence patterns and instead develop computational models that describe the spatio-temporal dynamics of the pathogen and the functional interactions with its biotic environment. To demonstrate the power of our approach, we will use systems level analysis and modelling to investigate the contribution of the biotic environment to the colonization and dissemination of Candida albicans.
project name
SAMEA5818150
sample derived from
Bacteroides uniformis
scientific_name
unspecified
sequencing method
multi-marker approach
taxonomic identity marker
binned metagenome: spire_mag_02675728
title