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Stool metatranscriptomics: A technical guideline for mRNA stabilisation and isolation

Overview of attention for article published in BMC Genomics, July 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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9 X users
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Title
Stool metatranscriptomics: A technical guideline for mRNA stabilisation and isolation
Published in
BMC Genomics, July 2015
DOI 10.1186/s12864-015-1694-y
Pubmed ID
Authors

Michael Reck, Jürgen Tomasch, Zhiluo Deng, Michael Jarek, Peter Husemann, Irene Wagner-Döbler, On behalf of COMBACTE consortium

Abstract

The complex microbiome of the gut has an enormous impact on human health. Analysis of the transcriptional activity of microorganisms through mRNA sequencing (metatranscriptomics) opens a completely new window into their activity in vivo, but it is highly challenging due to numerous technical and bioinformatical obstacles. Here we present an optimized pipeline for extraction of high quality mRNA from stool samples. Comparison of three commercially available RNA extraction kits with the method of Zoetendal revealed that the Powermicrobiome Kit (MoBio) performed best with respect to RNA yield and purity. Next, the influence of the stabilization reagent during sample storage for up to 15 days was studied. RIN analysis and qRT-PCR of spiked-in and indigenous genes revealed that RNA Later preserved mRNA integrity most efficiently, while samples conserved in RNA Protect showed substantial mRNA decay. Using the optimized pipeline developed here, recovery rates for spiked-in E.coli cells expressing fluorescing proteins were 8.7-9.7 % for SuperfolderGFP and 14.7-17.8 % for mCherry. The mRNA of stabilized stool samples as well as of snap-frozen controls was sequenced with Illumina Hiseq, yielding on average 74 million reads per sample. PCoA analysis, taxonomic classification using Kraken and functional classification using bwa showed that the transcriptomes of samples conserved in RNA Later were unchanged for up to 6 days even at room temperature, while RNA Protect was inefficient for storage durations exceeding 24 h. However, our data indicate that RNA Later introduces a bias which is then maintained throughout storage, while RNA Protect conserved samples are initially more similar to the snap frozen controls. RNA Later conserved samples had a reduced abundance of e.g. Prevotellaceae transcripts and were depleted for e.g. COG category "Carbohydrate transport and metabolism". Since the overall similarity between all stool transcriptional profiles studied here was >0.92, these differences are unlikely to affect global comparisons, but should be taken into account when rare but critically important members of the stool microbiome are being studied.

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X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 368 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 1%
France 2 <1%
United Kingdom 2 <1%
Ireland 1 <1%
Italy 1 <1%
Brazil 1 <1%
Germany 1 <1%
Taiwan 1 <1%
Korea, Republic of 1 <1%
Other 2 <1%
Unknown 351 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 93 25%
Student > Ph. D. Student 86 23%
Student > Master 40 11%
Student > Bachelor 22 6%
Student > Doctoral Student 16 4%
Other 65 18%
Unknown 46 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 121 33%
Biochemistry, Genetics and Molecular Biology 76 21%
Immunology and Microbiology 30 8%
Medicine and Dentistry 20 5%
Environmental Science 18 5%
Other 40 11%
Unknown 63 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 December 2021.
All research outputs
#4,007,817
of 22,745,803 outputs
Outputs from BMC Genomics
#1,650
of 10,634 outputs
Outputs of similar age
#50,503
of 262,658 outputs
Outputs of similar age from BMC Genomics
#42
of 254 outputs
Altmetric has tracked 22,745,803 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,634 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,658 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 254 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.