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Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates
Patterns of sequencing coverage along a bacterial genome—summarized by a peak-to-trough ratio (PTR)—have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host–microbe interactions. Here, we introduce Compute PTR (CoPTR): a tool for computing PT...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896461/ https://www.ncbi.nlm.nih.gov/pubmed/34987055 http://dx.doi.org/10.1101/gr.275533.121 |
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author | Joseph, Tyler A. Chlenski, Philippe Litman, Aviya Korem, Tal Pe'er, Itsik |
author_facet | Joseph, Tyler A. Chlenski, Philippe Litman, Aviya Korem, Tal Pe'er, Itsik |
author_sort | Joseph, Tyler A. |
collection | PubMed |
description | Patterns of sequencing coverage along a bacterial genome—summarized by a peak-to-trough ratio (PTR)—have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host–microbe interactions. Here, we introduce Compute PTR (CoPTR): a tool for computing PTRs from complete reference genomes and assemblies. Using simulations and data from growth experiments in simple and complex communities, we show that CoPTR is more accurate than the current state of the art while also providing more PTR estimates overall. We further develop a theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with inflammatory bowel disease. We show that growth rates are personalized, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by showing how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome. |
format | Online Article Text |
id | pubmed-8896461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88964612022-09-01 Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates Joseph, Tyler A. Chlenski, Philippe Litman, Aviya Korem, Tal Pe'er, Itsik Genome Res Method Patterns of sequencing coverage along a bacterial genome—summarized by a peak-to-trough ratio (PTR)—have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host–microbe interactions. Here, we introduce Compute PTR (CoPTR): a tool for computing PTRs from complete reference genomes and assemblies. Using simulations and data from growth experiments in simple and complex communities, we show that CoPTR is more accurate than the current state of the art while also providing more PTR estimates overall. We further develop a theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with inflammatory bowel disease. We show that growth rates are personalized, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by showing how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome. Cold Spring Harbor Laboratory Press 2022-03 /pmc/articles/PMC8896461/ /pubmed/34987055 http://dx.doi.org/10.1101/gr.275533.121 Text en © 2022 Joseph et al.; Published by Cold Spring Harbor Laboratory Press https://creativecommons.org/licenses/by-nc/4.0/This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see https://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Method Joseph, Tyler A. Chlenski, Philippe Litman, Aviya Korem, Tal Pe'er, Itsik Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title | Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title_full | Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title_fullStr | Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title_full_unstemmed | Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title_short | Accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
title_sort | accurate and robust inference of microbial growth dynamics from metagenomic sequencing reveals personalized growth rates |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896461/ https://www.ncbi.nlm.nih.gov/pubmed/34987055 http://dx.doi.org/10.1101/gr.275533.121 |
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