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Tracing mother-infant transmission of bacteriophages by means of a novel analytical tool for shotgun metagenomic datasets: METAnnotatorX

Overview of attention for article published in Microbiome, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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1 blog
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43 X users
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1 Facebook page

Citations

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56 Dimensions

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115 Mendeley
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Title
Tracing mother-infant transmission of bacteriophages by means of a novel analytical tool for shotgun metagenomic datasets: METAnnotatorX
Published in
Microbiome, August 2018
DOI 10.1186/s40168-018-0527-z
Pubmed ID
Authors

Christian Milani, Eoghan Casey, Gabriele Andrea Lugli, Rebecca Moore, Joanna Kaczorowska, Conor Feehily, Marta Mangifesta, Leonardo Mancabelli, Sabrina Duranti, Francesca Turroni, Francesca Bottacini, Jennifer Mahony, Paul D. Cotter, Fionnuala M. McAuliffe, Douwe van Sinderen, Marco Ventura

Abstract

Despite the relevance of viral populations, our knowledge of (bacterio) phage populations, i.e., the phageome, suffers from the absence of a "gold standard" protocol for viral DNA extraction with associated in silico sequence processing analyses. To overcome this apparent hiatus, we present here a comprehensive performance evaluation of various protocols and propose an optimized pipeline that covers DNA extraction, sequencing, and bioinformatic analysis of phageome data. Five widely used protocols for viral DNA extraction from fecal samples were tested for their performance in removal of non-viral DNA. Moreover, we developed a novel bioinformatic platform, METAnnotatorX, for metagenomic dataset analysis. This in silico tool facilitates a range of read- and assembly-based analyses, including taxonomic profiling using an iterative multi-database pipeline, classification of contigs at genus and species level, as well as functional characterizations of reads and assembled data. Performances of METAnnotatorX were assessed through investigation of seven mother-newborn pairs, leading to the identification of shared phage genotypes, of which two were genomically decoded and characterized. METAnnotatorX was furthermore employed to evaluate a protocol for the identification of contaminant non-viral DNA in sequenced datasets and was exploited to determine the amount of metagenomic data needed for robust evaluation of human adult-derived (fecal) phageomes. Results obtained in this study demonstrate that a comprehensive pipeline for analysis of phageomes will be pivotal for future explorations of the ecology of phages in the gut environment as well as for understanding their impact on the physiology and bacterial community kinetics as players of dysbiosis and homeostasis in the gut microbiota.

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 115 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 19%
Student > Ph. D. Student 19 17%
Student > Master 16 14%
Student > Bachelor 7 6%
Professor > Associate Professor 5 4%
Other 12 10%
Unknown 34 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 23%
Agricultural and Biological Sciences 24 21%
Immunology and Microbiology 6 5%
Computer Science 6 5%
Medicine and Dentistry 4 3%
Other 12 10%
Unknown 37 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 31 January 2019.
All research outputs
#1,285,645
of 25,711,518 outputs
Outputs from Microbiome
#413
of 1,790 outputs
Outputs of similar age
#26,551
of 342,945 outputs
Outputs of similar age from Microbiome
#15
of 55 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,790 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.9. This one has done well, scoring higher than 76% 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 342,945 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 55 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 72% of its contemporaries.