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Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR
BACKGROUND: Identification of unexpected taxa in 16S rRNA surveys of low-density microbiota, diluted mock communities and cultures demonstrated that a variable fraction of sequence reads originated from exogenous DNA. The sources of these contaminants are reagents used in DNA extraction, PCR, and ne...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4842273/ https://www.ncbi.nlm.nih.gov/pubmed/27107811 http://dx.doi.org/10.1186/s12866-016-0689-4 |
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author | Lazarevic, Vladimir Gaïa, Nadia Girard, Myriam Schrenzel, Jacques |
author_facet | Lazarevic, Vladimir Gaïa, Nadia Girard, Myriam Schrenzel, Jacques |
author_sort | Lazarevic, Vladimir |
collection | PubMed |
description | BACKGROUND: Identification of unexpected taxa in 16S rRNA surveys of low-density microbiota, diluted mock communities and cultures demonstrated that a variable fraction of sequence reads originated from exogenous DNA. The sources of these contaminants are reagents used in DNA extraction, PCR, and next-generation sequencing library preparation, and human (skin, oral and respiratory) microbiota from the investigators. RESULTS: For in silico removal of reagent contaminants, a pipeline was used which combines the relative abundance of operational taxonomic units (OTUs) in V3–4 16S rRNA gene amplicon datasets with bacterial DNA quantification based on qPCR targeting of the V3 segment of the 16S rRNA gene. Serially diluted cultures of Escherichia coli and Staphylococcus aureus were used for 16S rDNA profiling, and DNA from each of these species was used as a qPCR standard. OTUs assigned to Escherichia or Staphylococcus were virtually unaffected by the decontamination procedure, whereas OTUs from Pseudomonas, which is a major reagent contaminant, were completely or nearly completely removed. The decontamination procedure also attenuated the trend of increase in OTU richness in serially diluted cultures. CONCLUSIONS: Removal of contaminant sequences derived from reagents based on use of qPCR data may improve taxonomic representation in samples with low DNA concentration. Using the described pipeline, OTUs derived from cross-contamination of negative extraction controls were not recognized as contaminants and not removed from the sample dataset. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12866-016-0689-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4842273 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48422732016-04-25 Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR Lazarevic, Vladimir Gaïa, Nadia Girard, Myriam Schrenzel, Jacques BMC Microbiol Research Article BACKGROUND: Identification of unexpected taxa in 16S rRNA surveys of low-density microbiota, diluted mock communities and cultures demonstrated that a variable fraction of sequence reads originated from exogenous DNA. The sources of these contaminants are reagents used in DNA extraction, PCR, and next-generation sequencing library preparation, and human (skin, oral and respiratory) microbiota from the investigators. RESULTS: For in silico removal of reagent contaminants, a pipeline was used which combines the relative abundance of operational taxonomic units (OTUs) in V3–4 16S rRNA gene amplicon datasets with bacterial DNA quantification based on qPCR targeting of the V3 segment of the 16S rRNA gene. Serially diluted cultures of Escherichia coli and Staphylococcus aureus were used for 16S rDNA profiling, and DNA from each of these species was used as a qPCR standard. OTUs assigned to Escherichia or Staphylococcus were virtually unaffected by the decontamination procedure, whereas OTUs from Pseudomonas, which is a major reagent contaminant, were completely or nearly completely removed. The decontamination procedure also attenuated the trend of increase in OTU richness in serially diluted cultures. CONCLUSIONS: Removal of contaminant sequences derived from reagents based on use of qPCR data may improve taxonomic representation in samples with low DNA concentration. Using the described pipeline, OTUs derived from cross-contamination of negative extraction controls were not recognized as contaminants and not removed from the sample dataset. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12866-016-0689-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-04-23 /pmc/articles/PMC4842273/ /pubmed/27107811 http://dx.doi.org/10.1186/s12866-016-0689-4 Text en © Lazarevic et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Lazarevic, Vladimir Gaïa, Nadia Girard, Myriam Schrenzel, Jacques Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title | Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title_full | Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title_fullStr | Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title_full_unstemmed | Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title_short | Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR |
title_sort | decontamination of 16s rrna gene amplicon sequence datasets based on bacterial load assessment by qpcr |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4842273/ https://www.ncbi.nlm.nih.gov/pubmed/27107811 http://dx.doi.org/10.1186/s12866-016-0689-4 |
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