The effect of reverse transcription enzymes and conditions on high throughput amplicon sequencing of the 16S rRNA

Adam Šťovíček, Smadar Cohen-Chalamish, Osnat Gillor

Research output: Contribution to journalArticlepeer-review

Abstract

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here, we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to six fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing toward a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.

Original languageAmerican English
Article numbere7608
JournalPeerJ
Volume2019
Issue number10
DOIs
StatePublished - 1 Jan 2019

Keywords

  • Amplicon sequencing
  • Illumina
  • ImProm-II
  • Methodology
  • RNA
  • RT
  • Reverse transcription
  • Ribosome
  • SuperScript
  • TGIRT

All Science Journal Classification (ASJC) codes

  • General Biochemistry,Genetics and Molecular Biology
  • General Neuroscience
  • General Agricultural and Biological Sciences

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