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Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome

Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentrations of individual bacterial species. Quantitative PCR (qPCR) can quantify individual species, but it is n...

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Autores principales: Tettamanti Boshier, Florencia A., Srinivasan, Sujatha, Lopez, Anthony, Hoffman, Noah G., Proll, Sean, Fredricks, David N., Schiffer, Joshua T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141891/
https://www.ncbi.nlm.nih.gov/pubmed/32265316
http://dx.doi.org/10.1128/mSystems.00777-19
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author Tettamanti Boshier, Florencia A.
Srinivasan, Sujatha
Lopez, Anthony
Hoffman, Noah G.
Proll, Sean
Fredricks, David N.
Schiffer, Joshua T.
author_facet Tettamanti Boshier, Florencia A.
Srinivasan, Sujatha
Lopez, Anthony
Hoffman, Noah G.
Proll, Sean
Fredricks, David N.
Schiffer, Joshua T.
author_sort Tettamanti Boshier, Florencia A.
collection PubMed
description Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentrations of individual bacterial species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We sought to determine the accuracy of an inferred measure of bacterial concentration using total bacterial load and relative abundance. We analyzed 1,320 samples from 20 women with a history of frequent bacterial vaginosis who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and bacterial load (measured by broad-range 16S rRNA gene qPCR). Log(10)-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, P < 2.2e–16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacteria associated with larger errors. A total of 92% of the >0.5-log(10) errors occurred when the relative abundance was <10%. Many errors occurred during early bacterial expansion from or late contraction to low abundance. When the relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR in the vaginal microbiome. However, targeted qPCR is required to capture bacteria at low relative abundance and is preferable for characterizing growth and decay kinetics of single species. IMPORTANCE Microbiome studies primarily use 16S rRNA gene amplicon sequencing to assess the relative abundance of bacterial taxa in a community. However, these measurements do not accurately reflect absolute taxon concentrations. We sought to determine whether the product of species’ relative abundance and total bacterial load measured by broad-range qPCR is an accurate proxy for individual species’ concentrations, as measured by taxon-specific qPCR assays. Overall, the inferred bacterial concentrations were a reasonable proxy of species-specific qPCR values, particularly when bacteria are present at a higher relative abundance. This approach offers an opportunity to assess the concentrations of bacterial species and how they change in a community over time without developing individual qPCR assays for each taxon.
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spelling pubmed-71418912020-04-15 Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome Tettamanti Boshier, Florencia A. Srinivasan, Sujatha Lopez, Anthony Hoffman, Noah G. Proll, Sean Fredricks, David N. Schiffer, Joshua T. mSystems Methods and Protocols Whereas 16S rRNA gene amplicon sequencing quantifies relative abundances of bacterial taxa, variation in total bacterial load between samples restricts its ability to reflect absolute concentrations of individual bacterial species. Quantitative PCR (qPCR) can quantify individual species, but it is not practical to develop a suite of qPCR assays for every bacterium present in a diverse sample. We sought to determine the accuracy of an inferred measure of bacterial concentration using total bacterial load and relative abundance. We analyzed 1,320 samples from 20 women with a history of frequent bacterial vaginosis who self-collected vaginal swabs daily over 60 days. We inferred bacterial concentrations by taking the product of species relative abundance (assessed by 16S rRNA gene amplicon sequencing) and bacterial load (measured by broad-range 16S rRNA gene qPCR). Log(10)-converted inferred concentrations correlated with targeted qPCR (r = 0. 935, P < 2.2e–16) for seven key bacterial species. The mean inferred concentration error varied across bacteria, with rarer bacteria associated with larger errors. A total of 92% of the >0.5-log(10) errors occurred when the relative abundance was <10%. Many errors occurred during early bacterial expansion from or late contraction to low abundance. When the relative abundance of a species is >10%, inferred concentrations are reliable proxies for targeted qPCR in the vaginal microbiome. However, targeted qPCR is required to capture bacteria at low relative abundance and is preferable for characterizing growth and decay kinetics of single species. IMPORTANCE Microbiome studies primarily use 16S rRNA gene amplicon sequencing to assess the relative abundance of bacterial taxa in a community. However, these measurements do not accurately reflect absolute taxon concentrations. We sought to determine whether the product of species’ relative abundance and total bacterial load measured by broad-range qPCR is an accurate proxy for individual species’ concentrations, as measured by taxon-specific qPCR assays. Overall, the inferred bacterial concentrations were a reasonable proxy of species-specific qPCR values, particularly when bacteria are present at a higher relative abundance. This approach offers an opportunity to assess the concentrations of bacterial species and how they change in a community over time without developing individual qPCR assays for each taxon. American Society for Microbiology 2020-04-07 /pmc/articles/PMC7141891/ /pubmed/32265316 http://dx.doi.org/10.1128/mSystems.00777-19 Text en Copyright © 2020 Tettamanti Boshier et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Methods and Protocols
Tettamanti Boshier, Florencia A.
Srinivasan, Sujatha
Lopez, Anthony
Hoffman, Noah G.
Proll, Sean
Fredricks, David N.
Schiffer, Joshua T.
Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title_full Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title_fullStr Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title_full_unstemmed Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title_short Complementing 16S rRNA Gene Amplicon Sequencing with Total Bacterial Load To Infer Absolute Species Concentrations in the Vaginal Microbiome
title_sort complementing 16s rrna gene amplicon sequencing with total bacterial load to infer absolute species concentrations in the vaginal microbiome
topic Methods and Protocols
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141891/
https://www.ncbi.nlm.nih.gov/pubmed/32265316
http://dx.doi.org/10.1128/mSystems.00777-19
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