z-logo
open-access-imgOpen Access
RETRACTED: (p)ppGpp Controls Bacterial Persistence by Stochastic Induction of Toxin-Antitoxin Activity
Author(s) -
Etienne Maisonneuve,
Manuela Castro-Camargo,
Kenn Gerdes
Publication year - 2013
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2013.07.048
Subject(s) - biology , antitoxin , escherichia coli , multidrug tolerance , population , microbiology and biotechnology , protease , bacteria , toxin , phenotype , persistence (discontinuity) , exponential growth , stringent response , wild type , biofilm , genetics , gene , biochemistry , enzyme , mathematical analysis , demography , geotechnical engineering , mathematics , sociology , engineering , mutant
Persistence refers to the phenomenon in which isogenic populations of antibiotic-sensitive bacteria produce rare cells that transiently become multidrug tolerant. Whether slow growth in a rare subset of cells underlies the persistence phenotype has not be examined in wild-type bacteria. Here, we show that an exponentially growing population of wild-type Escherichia coli cells produces rare cells that stochastically switch into slow growth, that the slow-growing cells are multidrug tolerant, and that they are able to resuscitate. The persistence phenotype depends hierarchically on the signaling nucleotide (p)ppGpp, Lon protease, inorganic polyphosphate, and toxin-antitoxins. We show that the level of (p)ppGpp varies stochastically in a population of exponentially growing cells and that the high (p)ppGpp level in rare cells induces slow growth and persistence. (p)ppGpp triggers slow growth by activating toxin-antitoxin loci through a regulatory cascade depending on inorganic polyphosphate and Lon protease.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom