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Variable Persister Gene Interactions with (p)ppGpp for Persister Formation in Escherichia coli

Overview of attention for article published in Frontiers in Microbiology, September 2017
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Title
Variable Persister Gene Interactions with (p)ppGpp for Persister Formation in Escherichia coli
Published in
Frontiers in Microbiology, September 2017
DOI 10.3389/fmicb.2017.01795
Pubmed ID
Authors

Shuang Liu, Nan Wu, Shanshan Zhang, Youhua Yuan, Wenhong Zhang, Ying Zhang

Abstract

Persisters comprise a group of phenotypically heterogeneous metabolically quiescent bacteria with multidrug tolerance and contribute to the recalcitrance of chronic infections. Although recent work has shown that toxin-antitoxin (TA) system HipAB depends on stringent response effector (p)ppGppin persister formation, whether other persister pathways are also dependent on stringent response has not been explored. Here we examined the relationship of (p)ppGpp with 15 common persister genes (dnaK, clpB, rpoS, pspF, tnaA, sucB, ssrA, smpB, recA, umuD, uvrA, hipA, mqsR, relE, dinJ) using Escherichia coli as a model. By comparing the persister levels of wild type with their single gene knockout and double knockout mutants with relA, we divided their interactions into five types, namely A "dependent" (dnaK, recA), B "positive reinforcement" (rpoS, pspF, ssrA, recA), C "antagonistic" (clpB, sucB, umuD, uvrA, hipA, mqsR, relE, dinJ), D "epistasis" (clpB, rpoS, tnaA, ssrA, smpB, hipA), and E "irrelevant" (dnaK, clpB, rpoS, tnaA, sucB, smpB, umuD, uvrA, hipA, mqsR, relE, dinJ). We found that the persister gene interactions are intimately dependent on bacterial culture age, cell concentrations (diluted versus undiluted culture), and drug classifications, where the same gene may belong to different groups with varying antibiotics, culture age or cell concentrations. Together, this study represents the first attempt to systematically characterize the intricate relationships among the different mechanisms of persistence and as such provide new insights into the complexity of the persistence phenomenon at the level of persister gene network interactions.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 21 22%
Student > Ph. D. Student 19 20%
Student > Master 13 14%
Researcher 9 10%
Student > Doctoral Student 6 6%
Other 11 12%
Unknown 15 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 35%
Agricultural and Biological Sciences 19 20%
Immunology and Microbiology 11 12%
Chemistry 3 3%
Medicine and Dentistry 2 2%
Other 9 10%
Unknown 17 18%
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 06 October 2017.
All research outputs
#17,490,610
of 26,437,155 outputs
Outputs from Frontiers in Microbiology
#15,946
of 30,336 outputs
Outputs of similar age
#201,948
of 330,015 outputs
Outputs of similar age from Frontiers in Microbiology
#317
of 506 outputs
Altmetric has tracked 26,437,155 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 30,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 40th percentile – i.e., 40% 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 330,015 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 506 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.