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16S rRNA gene-based profiling of the human infant gut microbiota is strongly influenced by sample processing and PCR primer choice

Overview of attention for article published in Microbiome, June 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

blogs
1 blog
twitter
67 X users
peer_reviews
1 peer review site

Citations

dimensions_citation
210 Dimensions

Readers on

mendeley
507 Mendeley
citeulike
2 CiteULike
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Title
16S rRNA gene-based profiling of the human infant gut microbiota is strongly influenced by sample processing and PCR primer choice
Published in
Microbiome, June 2015
DOI 10.1186/s40168-015-0087-4
Pubmed ID
Authors

Alan W. Walker, Jennifer C. Martin, Paul Scott, Julian Parkhill, Harry J. Flint, Karen P. Scott

Abstract

Characterisation of the bacterial composition of the gut microbiota is increasingly carried out with a view to establish the role of different bacterial species in causation or prevention of disease. It is thus essential that the methods used to determine the microbial composition are robust. Here, several widely used molecular techniques were compared to establish the optimal methods to assess the bacterial composition in faecal samples from babies, before weaning. The bacterial community profile detected in the faeces of infants is highly dependent on the methodology used. Bifidobacteria were the most abundant bacteria detected at 6 weeks in faeces from two initially breast-fed babies using fluorescent in situ hybridisation (FISH), in agreement with data from previous culture-based studies. Using the 16S rRNA gene sequencing approach, however, we found that the detection of bifidobacteria in particular crucially depended on the optimisation of the DNA extraction method, and the choice of primers used to amplify the V1-V3 regions of 16S rRNA genes prior to subsequent sequence analysis. Bifidobacteria were only well represented among amplified 16S rRNA gene sequences when mechanical disruption (bead-beating) procedures for DNA extraction were employed together with optimised "universal" PCR primers. These primers incorporate degenerate bases at positions where mismatches to bifidobacteria and other bacterial taxa occur. The use of a DNA extraction kit with no bead-beating step resulted in a complete absence of bifidobacteria in the sequence data, even when using the optimised primers. This work emphasises the importance of sample processing methodology to downstream sequencing results and illustrates the value of employing multiple approaches for determining microbiota composition.

X Demographics

X Demographics

The data shown below were collected from the profiles of 67 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 507 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 2%
United Kingdom 6 1%
New Zealand 1 <1%
Mexico 1 <1%
Denmark 1 <1%
Belgium 1 <1%
Japan 1 <1%
Croatia 1 <1%
Unknown 487 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 117 23%
Researcher 110 22%
Student > Master 75 15%
Student > Bachelor 41 8%
Student > Doctoral Student 20 4%
Other 69 14%
Unknown 75 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 184 36%
Biochemistry, Genetics and Molecular Biology 88 17%
Immunology and Microbiology 57 11%
Medicine and Dentistry 36 7%
Environmental Science 18 4%
Other 34 7%
Unknown 90 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 21 June 2017.
All research outputs
#935,479
of 25,382,440 outputs
Outputs from Microbiome
#265
of 1,757 outputs
Outputs of similar age
#10,979
of 278,315 outputs
Outputs of similar age from Microbiome
#5
of 14 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,757 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.3. 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 278,315 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.