Evidence map›Paper›PMID 31667010›Full record

ArticlePeerJ2019

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

Adam Šťovíček, Smadar Cohen-Chalamish, Osnat Gillor

Abstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Adam ŠťovíčekDepartment of Environmental Hydrology and Microbiology, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Smadar Cohen-ChalamishThe Mina and Everard Goodman Faculty of Life Sciences and Advanced Materials and Nanotechnology Institute, Bar-Ilan University, Ramat-Gan, Israel.
Osnat GillorDepartment of Environmental Hydrology and Microbiology, Ben-Gurion University of the Negev, Beer Sheva, Israel.ORCID 0000-0003-0849-2241

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Amplicon sequencingIlluminaImProm-IIMethodologyReverse transcriptionRibosomeRNARTSuperScriptTGIRT

Identifiers

PMID31667010
PMCPMC6816399

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.