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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Association for the Advancement of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7176420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
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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