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Characterization of integrated prophages within diverse species of clinical nontuberculous mycobacteria

Overview of attention for article published in Virology Journal, August 2020
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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 (81st percentile)

Mentioned by

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1 news outlet
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4 tweeters

Citations

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9 Dimensions

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14 Mendeley
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Title
Characterization of integrated prophages within diverse species of clinical nontuberculous mycobacteria
Published in
Virology Journal, August 2020
DOI 10.1186/s12985-020-01394-y
Pubmed ID
Authors

Cody Glickman, Sara M. Kammlade, Nabeeh A. Hasan, L. Elaine Epperson, Rebecca M. Davidson, Michael Strong

Abstract

Nontuberculous mycobacterial (NTM) infections are increasing in prevalence, with current estimates suggesting that over 100,000 people in the United States are affected each year. It is unclear how certain species of mycobacteria transition from environmental bacteria to clinical pathogens, or what genetic elements influence the differences in virulence among strains of the same species. A potential mechanism of genetic evolution and diversity within mycobacteria is the presence of integrated viruses called prophages in the host genome. Prophages may act as carriers of bacterial genes, with the potential of altering bacterial fitness through horizontal gene transfer. In this study, we quantify the frequency and composition of prophages within mycobacteria isolated from clinical samples and compare them against the composition of PhagesDB, an environmental mycobacteriophage database. Prophages were predicted by agreement between two discovery tools, VirSorter and Phaster, and the frequencies of integrated prophages were compared by growth rate. Prophages were assigned to PhagesDB lettered clusters. Bacterial virulence gene frequency was calculated using a combination of the Virulence Factor Database (VFDB) and the Pathosystems Resource Integration Center virulence database (Patric-VF) within the gene annotation software Prokka. CRISPR elements were discovered using CRT. ARAGORN was used to quantify tRNAs. Rapidly growing mycobacteria (RGM) were more likely to contain prophage than slowly growing mycobacteria (SGM). CRISPR elements were not associated with prophage abundance in mycobacteria. The abundance of tRNAs was enriched in SGM compared to RGM. We compared the abundance of bacterial virulence genes within prophage genomes from clinical isolates to mycobacteriophages from PhagesDB. Our data suggests that prophages from clinical mycobacteria are enriched for bacterial virulence genes relative to environmental mycobacteriophage from PhagesDB. Prophages are present in clinical NTM isolates. Prophages are more likely to be present in RGM compared to SGM genomes. The mechanism and selective advantage of this enrichment by growth rate remain unclear. In addition, the frequency of bacterial virulence genes in prophages from clinical NTM is enriched relative to the PhagesDB environmental proxy. This suggests prophages may act as a reservoir of genetic elements bacteria could use to thrive within a clinical environment.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 21%
Student > Doctoral Student 3 21%
Student > Master 2 14%
Lecturer > Senior Lecturer 1 7%
Researcher 1 7%
Other 1 7%
Unknown 3 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 29%
Agricultural and Biological Sciences 3 21%
Immunology and Microbiology 2 14%
Unknown 5 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 11 March 2021.
All research outputs
#2,133,659
of 18,829,177 outputs
Outputs from Virology Journal
#186
of 2,705 outputs
Outputs of similar age
#56,472
of 308,153 outputs
Outputs of similar age from Virology Journal
#1
of 1 outputs
Altmetric has tracked 18,829,177 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,705 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.1. This one has done particularly well, scoring higher than 92% 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 308,153 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 81% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them