16S rRNA gene sequencing on a benchtop sequencer: accuracy for identification of clinically important bacteria.
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Author
Watts, G SYouens-Clark, K
Slepian, M J
Wolk, D M
Oshiro, M M
Metzger, G S
Dhingra, D
Cranmer, L D
Hurwitz, B L
Affiliation
Univ Arizona, Ctr CancUniv Arizona, Dept Pharmacol
Univ Arizona, Dept Agr & Biosyst Engn
Univ Arizona, Dept Med
Univ Arizona, Dept Biomed Engn
Univ Arizona, Arizona Ctr Accelerated Biomed Innovat
Issue Date
2017-12-01
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WILEYCitation
Watts, G. , Youens‐Clark, K. , Slepian, M. , Wolk, D. , Oshiro, M. , Metzger, G. , Dhingra, D. , Cranmer, L. and Hurwitz, B. (2017), 16S rRNA gene sequencing on a benchtop sequencer: accuracy for identification of clinically important bacteria. J Appl Microbiol, 123: 1584-1596. doi:10.1111/jam.13590Journal
JOURNAL OF APPLIED MICROBIOLOGYRights
© 2017 The Authors. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology. This is an open access article under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Test the choice of 16S rRNA gene amplicon and data analysis method on the accuracy of identification of clinically important bacteria utilizing a benchtop sequencer. Nine 16S rRNA amplicons were tested on an Ion Torrent PGM to identify 41 strains of clinical importance. The V1-V2 region identified 40 of 41 isolates to the species level. Three data analysis methods were tested, finding that the Ribosomal Database Project's SequenceMatch outperformed BLAST and the Ion Reporter Metagenomics analysis pipeline. Lastly, 16S rRNA gene sequencing mixtures of four species through a six log range of dilution showed species were identifiable even when present as 0·1% of the mixture. Sequencing the V1-V2 16S rRNA gene region, made possible by the increased read length Ion Torrent PGM sequencer's 400 base pair chemistry, may be a better choice over other commonly used regions for identifying clinically important bacteria. In addition, the SequenceMatch algorithm, freely available from the Ribosomal Database Project, is a good choice for matching filtered reads to organisms. Lastly, 16S rRNA gene sequencing's sensitivity to the presence of a bacterial species at 0·1% of a mixture suggests it has sufficient sensitivity for samples in which important bacteria may be rare. We have validated 16S rRNA gene sequencing on a benchtop sequencer including simple mixtures of organisms; however, our results highlight deficits for clinical application in place of current identification methods.Note
Open access article.ISSN
1365-2672PubMed ID
28940494Version
Final published versionSponsors
Southwest Environmental Health Sciences Center, NIEHS grant [ES06694]; Arizona Cancer Center, NIH grant [CA23074]; Gordon and Betty Moore Foundation [GBMF4733, GBMF4491]Additional Links
https://onlinelibrary.wiley.com/doi/abs/10.1111/jam.13590ae974a485f413a2113503eed53cd6c53
10.1111/jam.13590
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Except where otherwise noted, this item's license is described as © 2017 The Authors. Journal of Applied Microbiology published by John Wiley & Sons Ltd on behalf of The Society for Applied Microbiology. This is an open access article under the terms of the Creative Commons Attribution License.
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