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Ranking of persister genes in the same Escherichia coli genetic background demonstrates varying importance of individual persister genes in tolerance to different antibiotics

Overview of attention for article published in Frontiers in Microbiology, September 2015
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Title
Ranking of persister genes in the same Escherichia coli genetic background demonstrates varying importance of individual persister genes in tolerance to different antibiotics
Published in
Frontiers in Microbiology, September 2015
DOI 10.3389/fmicb.2015.01003
Pubmed ID
Authors

Nan Wu, Lei He, Peng Cui, Wenjie Wang, Youhua Yuan, Shuang Liu, Tao Xu, Shanshan Zhang, Jing Wu, Wenhong Zhang, Ying Zhang

Abstract

Despite the identification of many genes and pathways involved in the persistence phenomenon of bacteria, the relative importance of these genes in a single organism remains unclear. Here, using Escherichia coli as a model, we generated mutants of 21 known candidate persister genes and compared the relative importance of these mutants in persistence to various antibiotics (ampicillin, gentamicin, norfloxacin, and trimethoprim) at different times. We found that oxyR, dnaK, sucB, relA, rpoS, clpB, mqsR, and recA were prominent persister genes involved in persistence to multiple antibiotics. These genes map to the following pathways: antioxidative defense pathway (oxyR), global regulators (dnaK, clpB, and rpoS), energy production (sucB), stringent response (relA), toxin-antitoxin (TA) module (mqsR), and SOS response (recA). Among the TA modules, the ranking order was mqsR, lon, relE, tisAB, hipA, and dinJ. Intriguingly, rpoS deletion caused a defect in persistence to gentamicin but increased persistence to ampicillin and norfloxacin. Mutants demonstrated dramatic differences in persistence to different antibiotics at different time points: some mutants (oxyR, dnaK, phoU, lon, recA, mqsR, and tisAB) displayed defect in persistence from early time points, while other mutants (relE, smpB, glpD, umuD, and tnaA) showed defect only at later time points. These results indicate that varying hierarchy and importance of persister genes exist and that persister genes can be divided into those involved in shallow persistence and those involved in deep persistence. Our findings suggest that the persistence phenomenon is a dynamic process with different persister genes playing roles of variable significance at different times. These findings have implications for improved understanding of persistence phenomenon and developing new drugs targeting persisters for more effective cure of persistent infections.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 156 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 <1%
Estonia 1 <1%
Belgium 1 <1%
Unknown 153 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 24%
Student > Bachelor 25 16%
Student > Master 20 13%
Researcher 19 12%
Student > Doctoral Student 7 4%
Other 15 10%
Unknown 33 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 42 27%
Agricultural and Biological Sciences 41 26%
Immunology and Microbiology 15 10%
Medicine and Dentistry 7 4%
Chemical Engineering 3 2%
Other 9 6%
Unknown 39 25%
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 30 September 2015.
All research outputs
#17,774,112
of 22,829,683 outputs
Outputs from Frontiers in Microbiology
#17,178
of 24,800 outputs
Outputs of similar age
#184,627
of 274,274 outputs
Outputs of similar age from Frontiers in Microbiology
#271
of 430 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,800 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 22nd percentile – i.e., 22% 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 274,274 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 430 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.