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Evaluation of methods to purify virus-like particles for metagenomic sequencing of intestinal viromes

Overview of attention for article published in BMC Genomics, January 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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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1 news outlet
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14 X users
wikipedia
1 Wikipedia page

Citations

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167 Dimensions

Readers on

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381 Mendeley
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2 CiteULike
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Title
Evaluation of methods to purify virus-like particles for metagenomic sequencing of intestinal viromes
Published in
BMC Genomics, January 2015
DOI 10.1186/s12864-014-1207-4
Pubmed ID
Authors

Manuel Kleiner, Lora V Hooper, Breck A Duerkop

Abstract

BackgroundViruses are a significant component of the intestinal microbiota in mammals. In recent years, advances in sequencing technologies and data analysis techniques have enabled detailed metagenomic studies investigating intestinal viromes (collections of bacteriophage and eukaryotic viral nucleic acids) and their potential contributions to the ecology of the microbiota. An important component of virome studies is the isolation and purification of virus-like particles (VLPs) from intestinal contents or feces. Several methods have been applied to isolate VLPs from intestinal samples, yet to our knowledge, the efficiency and reproducibility between methods have not been explored. A rigorous evaluation of methods for VLP purification is critical as many studies begin to move from descriptive analyses of virus diversity to studies striving to quantitatively compare viral abundances across many samples. Therefore, reproducible VLP purification methods which allow for high sample throughput are needed. Here we compared and evaluated four methods for VLP purification using artificial intestinal microbiota samples of known bacterial and viral composition.ResultsWe compared the following four methods of VLP purification from fecal samples: (i) filtration¿+¿DNase, (ii) dithiothreitol treatment¿+¿filtration¿+¿DNase, (iii) filtration¿+¿DNase¿+¿PEG precipitation and (iv) filtration¿+¿DNase¿+¿CsCl density gradient centrifugation. Three of the four tested methods worked well for VLP purification. We observed several differences between methods related to the removal efficiency of bacterial and host DNAs and biases against specific phages. In particular the CsCl density gradient centrifugation method, which is frequently used for VLP purification, was most efficient in removing host derived DNA, but also showed strong discrimination against specific phages and showed a lower reproducibility of quantitative results.ConclusionsBased on our data we recommend the use of methods (i) or (ii) for large scale studies when quantitative comparison of viral abundances across samples is required. The CsCl density gradient centrifugation method, while being excellently suited to achieve highly purified samples, in our opinion, should be used with caution when performing quantitative studies.

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X Demographics

The data shown below were collected from the profiles of 14 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 381 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 1%
Switzerland 2 <1%
South Africa 2 <1%
United States 2 <1%
Canada 2 <1%
United Kingdom 1 <1%
Unknown 368 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 87 23%
Researcher 73 19%
Student > Master 61 16%
Student > Bachelor 31 8%
Student > Doctoral Student 16 4%
Other 46 12%
Unknown 67 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 117 31%
Biochemistry, Genetics and Molecular Biology 82 22%
Immunology and Microbiology 49 13%
Engineering 12 3%
Medicine and Dentistry 11 3%
Other 28 7%
Unknown 82 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 23 May 2023.
All research outputs
#1,858,298
of 25,381,384 outputs
Outputs from BMC Genomics
#404
of 11,234 outputs
Outputs of similar age
#25,289
of 362,344 outputs
Outputs of similar age from BMC Genomics
#10
of 287 outputs
Altmetric has tracked 25,381,384 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,234 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 96% 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 362,344 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 92% of its contemporaries.
We're also able to compare this research output to 287 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.