The Reliability of Metagenome-Assembled Genomes (MAGs) in Representing Natural Populations: Insights from Comparing MAGs against Isolate Genomes Derived from the Same Fecal Sample.

assembly gene abundance genome completeness genome recovery metagenomes metagenomics

Journal

Applied and environmental microbiology
ISSN: 1098-5336
Titre abrégé: Appl Environ Microbiol
Pays: United States
ID NLM: 7605801

Informations de publication

Date de publication:
26 02 2021
Historique:
received: 21 10 2020
accepted: 06 01 2021
pubmed: 17 1 2021
medline: 7 4 2021
entrez: 16 1 2021
Statut: epublish

Résumé

The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock data sets of known composition. However, these mock data sets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population-variable genes (those shared by >10% but <90% of the members of the population) as efficiently as core genes (those shared by >90% of the members). To address these issues, we compared the gene variabilities of pathogenic

Identifiants

pubmed: 33452027
pii: AEM.02593-20
doi: 10.1128/AEM.02593-20
pmc: PMC8105024
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIAID NIH HHS
ID : K01 AI103544
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI137679
Pays : United States

Informations de copyright

Copyright © 2021 American Society for Microbiology.

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Auteurs

Alexandra Meziti (A)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.

Luis M Rodriguez-R (LM)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
Department of Microbiology, University of Innsbruck, Innsbruck, Tyrol, Austria.
Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Tyrol, Austria.

Janet K Hatt (JK)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.

Angela Peña-Gonzalez (A)

School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA.

Karen Levy (K)

Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.

Konstantinos T Konstantinidis (KT)

School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA kostas.konstantinidis@gatech.edu.
School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA.

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Classifications MeSH