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Validating a 16S rRNA multi-region approach using mock samples

Wednesday, September 16, 2015 — Poster Session I

3:30 p.m. – 5:00 p.m.
FAES Terrace
CIT
COMPBIO-2

Authors

  • JJ Barb
  • AJ Oler
  • HS Kim
  • N Chalmers
  • G Wallen
  • A Cashion
  • PJ Munson
  • NJ Ames

Abstract

There is much speculation on what hypervariable region gives the highest bacteria specificity in 16s rRNA sequencing. The optimum solution to obtain a comprehensive view of complex bacterial communities would be to sequence the entire 16S rRNA gene, which is limited with current standard library short-read second generation sequencing technology. This analysis examines a new process using six hypervariable regions of the 16S rRNA (V2, V3, V4, V67, V8 and V9) on the Ion Torrent Personal Genome Machine (Life Technologies, Grand Island, NY). Four mock samples were subjected to the 16s Ion Metagenomics Kit ™ (Life Technologies) and a customized analytical pipeline. The Kullback-Liebler divergence (DKL) was used to infer which region best recovered the distribution of bacteria to the known. Three hypervariable regions, V2, V4 and V67 diverged the least from the known distribution with the forward and reverse V4 region identifying all 17 family level bacteria. The forward and reverse V9 region gave the highest average DKL identifying only 17% and 53% of the known family level bacteria respectively. The mock samples used in this study allowed for the validation of a new library kit and a customized analytical pipeline while also assessing the performance of multiple different variable regions simultaneously. Future work will include the use of clinical samples from aplastic anemia patients and the presentation of microbial abundance across variable regions at three time points throughout two different courses of treatment.

Category: Computational Biology