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A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil
Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challeng...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384349/ https://www.ncbi.nlm.nih.gov/pubmed/22434885 http://dx.doi.org/10.1093/nar/gks238 |
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author | Gans, Jason D. Dunbar, John Eichorst, Stephanie A. Gallegos-Graves, La Verne Wolinsky, Murray Kuske, Cheryl R. |
author_facet | Gans, Jason D. Dunbar, John Eichorst, Stephanie A. Gallegos-Graves, La Verne Wolinsky, Murray Kuske, Cheryl R. |
author_sort | Gans, Jason D. |
collection | PubMed |
description | Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33 684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO(2). Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges. |
format | Online Article Text |
id | pubmed-3384349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-33843492012-06-28 A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil Gans, Jason D. Dunbar, John Eichorst, Stephanie A. Gallegos-Graves, La Verne Wolinsky, Murray Kuske, Cheryl R. Nucleic Acids Res Methods Online Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33 684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO(2). Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges. Oxford University Press 2012-07 2012-03-20 /pmc/articles/PMC3384349/ /pubmed/22434885 http://dx.doi.org/10.1093/nar/gks238 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Gans, Jason D. Dunbar, John Eichorst, Stephanie A. Gallegos-Graves, La Verne Wolinsky, Murray Kuske, Cheryl R. A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title | A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title_full | A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title_fullStr | A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title_full_unstemmed | A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title_short | A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil |
title_sort | robust pcr primer design platform applied to the detection of acidobacteria group 1 in soil |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384349/ https://www.ncbi.nlm.nih.gov/pubmed/22434885 http://dx.doi.org/10.1093/nar/gks238 |
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