MG-MLST: Characterizing the Microbiome at the Strain Level in Metagenomic Data.
MLST
Propionibacterium acnes
metagenomics
method
microbiome
strain
Journal
Microorganisms
ISSN: 2076-2607
Titre abrégé: Microorganisms
Pays: Switzerland
ID NLM: 101625893
Informations de publication
Date de publication:
08 May 2020
08 May 2020
Historique:
received:
01
04
2020
revised:
26
04
2020
accepted:
02
05
2020
entrez:
14
5
2020
pubmed:
14
5
2020
medline:
14
5
2020
Statut:
epublish
Résumé
The microbiome plays an important role in human physiology. The composition of the human microbiome has been described at the phylum, class, genus, and species levels, however, it is largely unknown at the strain level. The importance of strain-level differences in microbial communities has been increasingly recognized in understanding disease associations. Current methods for identifying strain populations often require deep metagenomic sequencing and a comprehensive set of reference genomes. In this study, we developed a method, metagenomic multi-locus sequence typing (MG-MLST), to determine strain-level composition in a microbial community by combining high-throughput sequencing with multi-locus sequence typing (MLST). We used a commensal bacterium,
Identifiants
pubmed: 32397065
pii: microorganisms8050684
doi: 10.3390/microorganisms8050684
pmc: PMC7284976
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : NIH HHS
ID : R01GM099530
Pays : United States
Organisme : NIMH NIH HHS
ID : R25 MH109172
Pays : United States
Organisme : NIH HHS
ID : UH2AR057503
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM099530
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR057503
Pays : United States
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