↓ Skip to main content

Gene Network Homology in Prokaryotes Using a Similarity Search Approach: Queries of Quorum Sensing Signal Transduction

Overview of attention for article published in PLoS Computational Biology, August 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
36 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Gene Network Homology in Prokaryotes Using a Similarity Search Approach: Queries of Quorum Sensing Signal Transduction
Published in
PLoS Computational Biology, August 2012
DOI 10.1371/journal.pcbi.1002637
Pubmed ID
Authors

David N. Quan, William E. Bentley

Abstract

Bacterial cell-cell communication is mediated by small signaling molecules known as autoinducers. Importantly, autoinducer-2 (AI-2) is synthesized via the enzyme LuxS in over 80 species, some of which mediate their pathogenicity by recognizing and transducing this signal in a cell density dependent manner. AI-2 mediated phenotypes are not well understood however, as the means for signal transduction appears varied among species, while AI-2 synthesis processes appear conserved. Approaches to reveal the recognition pathways of AI-2 will shed light on pathogenicity as we believe recognition of the signal is likely as important, if not more, than the signal synthesis. LMNAST (Local Modular Network Alignment Similarity Tool) uses a local similarity search heuristic to study gene order, generating homology hits for the genomic arrangement of a query gene sequence. We develop and apply this tool for the E. coli lac and LuxS regulated (Lsr) systems. Lsr is of great interest as it mediates AI-2 uptake and processing. Both test searches generated results that were subsequently analyzed through a number of different lenses, each with its own level of granularity, from a binary phylogenetic representation down to trackback plots that preserve genomic organizational information. Through a survey of these results, we demonstrate the identification of orthologs, paralogs, hitchhiking genes, gene loss, gene rearrangement within an operon context, and also horizontal gene transfer (HGT). We found a variety of operon structures that are consistent with our hypothesis that the signal can be perceived and transduced by homologous protein complexes, while their regulation may be key to defining subsequent phenotypic behavior.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 3%
Germany 1 3%
France 1 3%
Australia 1 3%
United States 1 3%
Unknown 31 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 28%
Student > Ph. D. Student 8 22%
Student > Master 4 11%
Student > Bachelor 3 8%
Professor 3 8%
Other 7 19%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 31%
Biochemistry, Genetics and Molecular Biology 9 25%
Engineering 5 14%
Computer Science 2 6%
Social Sciences 2 6%
Other 4 11%
Unknown 3 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 02 September 2012.
All research outputs
#20,656,161
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#8,208
of 8,960 outputs
Outputs of similar age
#137,223
of 174,034 outputs
Outputs of similar age from PLoS Computational Biology
#89
of 101 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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 174,034 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.