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In silico identification of bacteriocin gene clusters in the gastrointestinal tract, based on the Human Microbiome Project’s reference genome database

Overview of attention for article published in BMC Microbiology, September 2015
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Title
In silico identification of bacteriocin gene clusters in the gastrointestinal tract, based on the Human Microbiome Project’s reference genome database
Published in
BMC Microbiology, September 2015
DOI 10.1186/s12866-015-0515-4
Pubmed ID
Authors

Calum J. Walsh, Caitriona M. Guinane, Colin Hill, R. Paul Ross, Paul W. O’Toole, Paul D. Cotter

Abstract

The human gut microbiota comprises approximately 100 trillion microbial cells which significantly impact many aspects of human physiology - including metabolism, nutrient absorption and immune function. Disturbances in this population have been implicated in many conditions and diseases, including obesity, type-2 diabetes and inflammatory bowel disease. This suggests that targeted manipulation or shaping of the gut microbiota, by bacteriocins and other antimicrobials, has potential as a therapeutic tool for the prevention or treatment of these conditions. With this in mind, several studies have used traditional culture-dependent approaches to successfully identify bacteriocin-producers from the mammalian gut. In silico-based approaches to identify novel gene clusters are now also being utilised to take advantage of the vast amount of data currently being generated by next generation sequencing technologies. In this study, we employed an in silico screening approach to mine potential bacteriocin clusters in genome-sequenced isolates from the gastrointestinal tract (GIT). More specifically, the bacteriocin genome-mining tool BAGEL3 was used to identify potential bacteriocin producers in the genomes of the GIT subset of the Human Microbiome Project's reference genome database. Each of the identified gene clusters were manually annotated and potential bacteriocin-associated genes were evaluated. We identified 74 clusters of note from 59 unique members of the Firmicutes, Bacteroidetes, Actinobacteria, Fusobacteria and Synergistetes. The most commonly identified class of bacteriocin was the >10 kDa class, formerly known as bacteriolysins, followed by lantibiotics and sactipeptides. Multiple bacteriocin gene clusters were identified in a dataset representative of the human gut microbiota. Interestingly, many of these were associated with species and genera which are not typically associated with bacteriocin production.

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The data shown below were collected from the profiles of 3 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 231 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Canada 2 <1%
Italy 1 <1%
Brazil 1 <1%
Unknown 225 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 19%
Researcher 38 16%
Student > Master 33 14%
Student > Bachelor 20 9%
Student > Doctoral Student 10 4%
Other 34 15%
Unknown 51 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 54 23%
Biochemistry, Genetics and Molecular Biology 42 18%
Immunology and Microbiology 27 12%
Medicine and Dentistry 13 6%
Chemistry 8 3%
Other 24 10%
Unknown 63 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 January 2016.
All research outputs
#13,956,297
of 22,828,180 outputs
Outputs from BMC Microbiology
#1,358
of 3,191 outputs
Outputs of similar age
#122,268
of 245,084 outputs
Outputs of similar age from BMC Microbiology
#29
of 75 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,191 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 54% 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 245,084 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 75 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 61% of its contemporaries.