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Defining the DNA uptake specificity of naturally competent Haemophilus influenzae cells

Overview of attention for article published in Nucleic Acids Research, June 2012
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Article details
Title
Defining the DNA uptake specificity of naturally competent Haemophilus influenzae cells
Published in
Nucleic Acids Research, June 2012
DOI 10.1093/nar/gks640
Pubmed ID
Authors
Abstract

Some naturally competent bacteria exhibit both a strong preference for DNA fragments containing specific 'uptake sequences' and dramatic overrepresentation of these sequences in their genomes. Uptake sequences are often assumed to directly reflect the specificity of the DNA uptake machinery, but the actual specificity has not been well characterized for any bacterium. We produced a detailed analysis of Haemophilus influenzae's uptake specificity, using Illumina sequencing of degenerate uptake sequences in fragments recovered from competent cells. This identified an uptake motif with the same consensus as the motif overrepresented in the genome, with a 9 bp core (AAGTGCGGT) and two short flanking T-rich tracts. Only four core bases (GCGG) were critical for uptake, suggesting that these make strong specific contacts with the uptake machinery. Other core bases had weaker roles when considered individually, as did the T-tracts, but interaction effects between these were also determinants of uptake. The properties of genomic uptake sequences are also constrained by mutational biases and selective forces acting on USSs with coding and termination functions. Our findings define constraints on gene transfer by natural transformation and suggest how the DNA uptake machinery overcomes the physical constraints imposed by stiff highly charged DNA molecules.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 3%
Turkey 1 1%
Unknown 69 96%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 13 18%
Student > Bachelor 12 17%
Researcher 12 17%
Student > Master 9 13%
Other 3 4%
Other 8 11%
Unknown 15 21%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 30 42%
Biochemistry, Genetics and Molecular Biology 16 22%
Computer Science 2 3%
Chemistry 2 3%
Environmental Science 1 1%
Other 5 7%
Unknown 16 22%
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 05 December 2025.
All research outputs
#27,017,808
of 32,692,245 outputs
Outputs from Nucleic Acids Research
#30,055
of 32,656 outputs
Outputs of similar age
#165,748
of 203,345 outputs
Outputs of similar age from Nucleic Acids Research
#211
of 270 outputs
Altmetric has tracked 32,692,245 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 32,656 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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We're also able to compare this research output to 270 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.