16S rRNA gene sequencing on a benchtop sequencer: accuracy for identification of clinically important bacteria.
AuthorWatts, G S
Slepian, M J
Wolk, D M
Oshiro, M M
Metzger, G S
Cranmer, L D
Hurwitz, B L
AffiliationUniv Arizona, Ctr Canc
Univ 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
MetadataShow full item record
CitationWatts, 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.13590
JournalJOURNAL OF APPLIED MICROBIOLOGY
Rights© 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 InformationThis 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 firstname.lastname@example.org.
AbstractTest 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.
NoteOpen access article.
VersionFinal published version
SponsorsSouthwest Environmental Health Sciences Center, NIEHS grant [ES06694]; Arizona Cancer Center, NIH grant [CA23074]; Gordon and Betty Moore Foundation [GBMF4733, GBMF4491]
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