Back to Search Start Over

Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples.

Authors :
Barb JJ
Oler AJ
Kim HS
Chalmers N
Wallen GR
Cashion A
Munson PJ
Ames NJ
Source :
PloS one [PLoS One] 2016 Feb 01; Vol. 11 (2), pp. e0148047. Date of Electronic Publication: 2016 Feb 01 (Print Publication: 2016).
Publication Year :
2016

Abstract

Objectives: There is much speculation on which hypervariable region provides the highest bacterial specificity in 16S rRNA sequencing. The optimum solution to prevent bias and to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene; however, this is not possible with second generation standard library design and short-read next-generation sequencing technology.<br />Methods: This paper examines a new process using seven hypervariable or V regions of the 16S rRNA (six amplicons: V2, V3, V4, V6-7, V8, and V9) processed simultaneously on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were amplified using the 16S Ion Metagenomics Kitâ„¢ (Life Technologies) and their sequencing data is subjected to a novel analytical pipeline.<br />Results: Results are presented at family and genus level. The Kullback-Leibler divergence (DKL), a measure of the departure of the computed from the nominal bacterial distribution in the mock samples, was used to infer which region performed best at the family and genus levels. Three different hypervariable regions, V2, V4, and V6-7, produced the lowest divergence compared to the known mock sample. The V9 region gave the highest (worst) average DKL while the V4 gave the lowest (best) average DKL. In addition to having a high DKL, the V9 region in both the forward and reverse directions performed the worst finding only 17% and 53% of the known family level and 12% and 47% of the genus level bacteria, while results from the forward and reverse V4 region identified all 17 family level bacteria.<br />Conclusions: The results of our analysis have shown that our sequencing methods using 6 hypervariable regions of the 16S rRNA and subsequent analysis is valid. This method also allowed for the assessment of how well each of the variable regions might perform simultaneously. Our findings will provide the basis for future work intended to assess microbial abundance at different time points throughout a clinical protocol.

Details

Language :
English
ISSN :
1932-6203
Volume :
11
Issue :
2
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
26829716
Full Text :
https://doi.org/10.1371/journal.pone.0148047