Literature DB >> 34789881

Observation of universal ageing dynamics in antibiotic persistence.

Yoav Kaplan1, Shaked Reich1, Elyaqim Oster1, Shani Maoz1, Irit Levin-Reisman1, Irine Ronin1, Orit Gefen1, Oded Agam2, Nathalie Q Balaban3.   

Abstract

Stress responses allow cells to adapt to changes in external conditions by activating specific pathways1. Here we investigate the dynamics of single cells that were subjected to acute stress that is too strong for a regulated response but not lethal. We show that when the growth of bacteria is arrested by acute transient exposure to strong inhibitors, the statistics of their regrowth dynamics can be predicted by a model for the cellular network that ignores most of the details of the underlying molecular interactions. We observed that the same stress, applied either abruptly or gradually, can lead to totally different recovery dynamics. By measuring the regrowth dynamics after stress exposure on thousands of cells, we show that the model can predict the outcome of antibiotic persistence measurements. Our results may account for the ubiquitous antibiotic persistence phenotype2, as well as for the difficulty in attempts to link it to specific genes3. More generally, our approach suggests that two different cellular states can be observed under stress: a regulated state, which prepares cells for fast recovery, and a disrupted cellular state due to acute stress, with slow and heterogeneous recovery dynamics. The disrupted state may be described by general properties of large random networks rather than by specific pathway activation. Better understanding of the disrupted state could shed new light on the survival and evolution of cells under stress.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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Year:  2021        PMID: 34789881     DOI: 10.1038/s41586-021-04114-w

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  38 in total

1.  Automated imaging with ScanLag reveals previously undetectable bacterial growth phenotypes.

Authors:  Irit Levin-Reisman; Orit Gefen; Ofer Fridman; Irine Ronin; David Shwa; Hila Sheftel; Nathalie Q Balaban
Journal:  Nat Methods       Date:  2010-08-01       Impact factor: 28.547

2.  Single-cell and population lag times as a function of cell age.

Authors:  Carmen Pin; József Baranyi
Journal:  Appl Environ Microbiol       Date:  2008-02-22       Impact factor: 4.792

3.  Power-law tail in lag time distribution underlies bacterial persistence.

Authors:  Emrah Şimşek; Minsu Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-19       Impact factor: 11.205

Review 4.  (p)ppGpp: still magical?

Authors:  Katarzyna Potrykus; Michael Cashel
Journal:  Annu Rev Microbiol       Date:  2008       Impact factor: 15.500

5.  Age of inoculum strongly influences persister frequency and can mask effects of mutations implicated in altered persistence.

Authors:  Hannes Luidalepp; Arvi Jõers; Niilo Kaldalu; Tanel Tenson
Journal:  J Bacteriol       Date:  2011-05-20       Impact factor: 3.490

6.  Wide lag time distributions break a trade-off between reproduction and survival in bacteria.

Authors:  Stefany Moreno-Gámez; Daniel J Kiviet; Clément Vulin; Susan Schlegel; Kim Schlegel; G Sander van Doorn; Martin Ackermann
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-15       Impact factor: 11.205

7.  Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations.

Authors:  Ofer Fridman; Amir Goldberg; Irine Ronin; Noam Shoresh; Nathalie Q Balaban
Journal:  Nature       Date:  2014-06-25       Impact factor: 49.962

Review 8.  Distinguishing between resistance, tolerance and persistence to antibiotic treatment.

Authors:  Asher Brauner; Ofer Fridman; Orit Gefen; Nathalie Q Balaban
Journal:  Nat Rev Microbiol       Date:  2016-04       Impact factor: 60.633

Review 9.  Persistence: a copacetic and parsimonious hypothesis for the existence of non-inherited resistance to antibiotics.

Authors:  Bruce R Levin; Jeniffer Concepción-Acevedo; Klas I Udekwu
Journal:  Curr Opin Microbiol       Date:  2014-08-02       Impact factor: 7.934

10.  Pharmacodynamics, population dynamics, and the evolution of persistence in Staphylococcus aureus.

Authors:  Paul J T Johnson; Bruce R Levin
Journal:  PLoS Genet       Date:  2013-01-03       Impact factor: 5.917

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  3 in total

1.  Stress and disarray leading to persistence.

Authors:  Ursula Hofer
Journal:  Nat Rev Microbiol       Date:  2022-02       Impact factor: 60.633

2.  Reply to Zhang et al.: The critical temperature dependence of developmental rates is in search of a mechanism.

Authors:  Olga Filina; Burak Demirbas; Rik Haagmans; Jeroen S van Zon
Journal:  Proc Natl Acad Sci U S A       Date:  2022-06-22       Impact factor: 12.779

3.  A Shift in Perspective: A Role for the Type I Toxin TisB as Persistence-Stabilizing Factor.

Authors:  Daniel Edelmann; Bork A Berghoff
Journal:  Front Microbiol       Date:  2022-03-17       Impact factor: 5.640

  3 in total

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