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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...

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Autores principales: Joseph, Tyler A., Chlenski, Philippe, Litman, Aviya, Korem, Tal, Pe'er, Itsik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2022
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.
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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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