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Metagenomic Quantification of Genes with Internal Standards
We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858063/ https://www.ncbi.nlm.nih.gov/pubmed/33531401 http://dx.doi.org/10.1128/mBio.03173-20 |
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author | Crossette, Emily Gumm, Jordan Langenfeld, Kathryn Raskin, Lutgarde Duhaime, Melissa Wigginton, Krista |
author_facet | Crossette, Emily Gumm, Jordan Langenfeld, Kathryn Raskin, Lutgarde Duhaime, Melissa Wigginton, Krista |
author_sort | Crossette, Emily |
collection | PubMed |
description | We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families. |
format | Online Article Text |
id | pubmed-7858063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-78580632021-02-05 Metagenomic Quantification of Genes with Internal Standards Crossette, Emily Gumm, Jordan Langenfeld, Kathryn Raskin, Lutgarde Duhaime, Melissa Wigginton, Krista mBio Research Article We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families. American Society for Microbiology 2021-02-02 /pmc/articles/PMC7858063/ /pubmed/33531401 http://dx.doi.org/10.1128/mBio.03173-20 Text en Copyright © 2021 Crossette 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 | Research Article Crossette, Emily Gumm, Jordan Langenfeld, Kathryn Raskin, Lutgarde Duhaime, Melissa Wigginton, Krista Metagenomic Quantification of Genes with Internal Standards |
title | Metagenomic Quantification of Genes with Internal Standards |
title_full | Metagenomic Quantification of Genes with Internal Standards |
title_fullStr | Metagenomic Quantification of Genes with Internal Standards |
title_full_unstemmed | Metagenomic Quantification of Genes with Internal Standards |
title_short | Metagenomic Quantification of Genes with Internal Standards |
title_sort | metagenomic quantification of genes with internal standards |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7858063/ https://www.ncbi.nlm.nih.gov/pubmed/33531401 http://dx.doi.org/10.1128/mBio.03173-20 |
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