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Metagenomic growth rate inferences of strains in situ

We developed a method for strain-level metagenomic estimation of growth rate (SMEG) for inferring growth rates of bacterial subspecies, or strains, from complex metagenomic samples. We applied our method, which is based on both reference strains and de novo approaches, to different gut metagenomic d...

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Detalles Bibliográficos
Autores principales: Emiola, Akintunde, Zhou, Wei, Oh, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176420/
https://www.ncbi.nlm.nih.gov/pubmed/32494636
http://dx.doi.org/10.1126/sciadv.aaz2299
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author Emiola, Akintunde
Zhou, Wei
Oh, Julia
author_facet Emiola, Akintunde
Zhou, Wei
Oh, Julia
author_sort Emiola, Akintunde
collection PubMed
description We developed a method for strain-level metagenomic estimation of growth rate (SMEG) for inferring growth rates of bacterial subspecies, or strains, from complex metagenomic samples. We applied our method, which is based on both reference strains and de novo approaches, to different gut metagenomic datasets, accurately identifying an outbreak-associated Escherichia coli strain and a previously unidentified association of an Akkermansia muciniphila strain in cancer immunotherapy responders. SMEG resolves strain-specific growth rates from mixtures of commensal or pathogenic strains to provide new insights into microbial interactions and disease associations at the strain level. SMEG is available for download at https://github.com/ohlab/SMEG.
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spelling pubmed-71764202020-06-02 Metagenomic growth rate inferences of strains in situ Emiola, Akintunde Zhou, Wei Oh, Julia Sci Adv Research Articles We developed a method for strain-level metagenomic estimation of growth rate (SMEG) for inferring growth rates of bacterial subspecies, or strains, from complex metagenomic samples. We applied our method, which is based on both reference strains and de novo approaches, to different gut metagenomic datasets, accurately identifying an outbreak-associated Escherichia coli strain and a previously unidentified association of an Akkermansia muciniphila strain in cancer immunotherapy responders. SMEG resolves strain-specific growth rates from mixtures of commensal or pathogenic strains to provide new insights into microbial interactions and disease associations at the strain level. SMEG is available for download at https://github.com/ohlab/SMEG. American Association for the Advancement of Science 2020-04-22 /pmc/articles/PMC7176420/ /pubmed/32494636 http://dx.doi.org/10.1126/sciadv.aaz2299 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Research Articles
Emiola, Akintunde
Zhou, Wei
Oh, Julia
Metagenomic growth rate inferences of strains in situ
title Metagenomic growth rate inferences of strains in situ
title_full Metagenomic growth rate inferences of strains in situ
title_fullStr Metagenomic growth rate inferences of strains in situ
title_full_unstemmed Metagenomic growth rate inferences of strains in situ
title_short Metagenomic growth rate inferences of strains in situ
title_sort metagenomic growth rate inferences of strains in situ
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176420/
https://www.ncbi.nlm.nih.gov/pubmed/32494636
http://dx.doi.org/10.1126/sciadv.aaz2299
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