<i>Escherichia coli</i>can survive stress by noisy growth modulation

Patange, Om; Schwall, Christian; Jones, Molly Morgan; Griffith, Douglas A.; Phillips, Andrew; Locke, James

doi:10.1101/265801

Cited by 11 publications

(18 citation statements)

References 30 publications

(93 reference statements)

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“…Growth rate fluctuations have also been observed in single cells across many bacterial species 2,8,[18][19][20] . They can arise due to temporal variation in the expression of metabolic enzymes 2 , the expression of burdensome proteins 12 , and due to regulatory effects such as feedback involved in cell size control 19 .…”

Section: Introductionmentioning

confidence: 97%

“…Genes involved in adaptation to stress are among the noisiest genome-wide 3,5 . Studies on individual pathways have revealed specific examples in which heterogeneous expression of stress response genes can allow subpopulations of cells to survive sudden environmental stress, such as transient exposure to antimicrobial drugs, oxidative stress, and acid stress [6][7][8][9] . Recent studies also indicate that heterogeneity in the expression of genes involved in DNA repair can lead to variability in mutation rates, contributing to microbial evolution [10][11][12] .…”

Section: Introductionmentioning

confidence: 99%

“…For instance, pulsatile expression of the transcription factor ComK enables Bacillus subtilis cells to enter a transient competent state 15,16 . In E. coli, heterogeneous expression of RpoS, a key regulator of general stress response, originates from pulses of activation that are inversely correlated with growth, allowing cells to survive oxidative stress 8 . Additionally, Kim et al recently demonstrated that genes in the flagellar synthesis network, a process with a pivotal role in microbial pathogenicity, are expressed with different pulsing programs that allow cells to switch between flagellar phenotypes 17 .…”

Section: Introductionmentioning

confidence: 99%

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Dynamic gene expression and growth underlie cell-to-cell heterogeneity inEscherichia colistress response

Sampaio

Blassick

Lugagne

et al. 2020

Preprint

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Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. However, the timescales of the dynamics that underlie this heterogeneity are often unknown. This is a critical piece of information because different phenotypic outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we conducted detailed measurements of gene expression and growth over many generations using 15 reporters in Escherichia coli, focusing on genes related to stress response. In constant environmental conditions without stress, we found many examples of pulsatile gene expression, suggesting that this may be a widespread dynamic property. Pulse lengths often exceeded the cell cycle, leading to multi-generational correlations. Temporal properties of the pulses, such as their frequency, duration, and amplitude, varied widely across the reporters. Single-cell growth rates were often anti-correlated with gene expression, with changes in growth typically preceding changes in expression. These dynamics and the timescales of the pulses have functional consequences, which we demonstrate by measuring single-cell survival after challenging cells with the antibiotic ciprofloxacin. Together, this work reveals that pulsatile expression dynamics are widespread in E. coli stress response networks. Further, these dynamic patterns of gene expression are closely linked with growth and have important consequences for survival.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic gene expression and growth underlie cell-to-cell heterogeneity inEscherichia colistress response

Sampaio

Blassick

Lugagne

et al. 2020

Preprint

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“…Nutrient stress is a strong trigger of phenotypic diversification that can be eventually used for controlling the degree of diversification of a bacterial population. Previous studies have shown that such phenotypic diversification mechanisms are governed by a complex set of physiological mechanisms involving noise in gene expression, metabolism and growth (Kiviet et al ., ; Kleijn et al ., ; Patange et al ., ), these three mechanisms being highly cross‐correlated and being controlled through mutual feedback loops. Ultimately, the superimposition of these three mechanisms leads to population phenotypic heterogeneity that can in turn confer interesting functionalities to the whole population (e.g.…”

Section: Introductionmentioning

confidence: 99%

Segregostat: a novel concept to control phenotypic diversification dynamics on the example of Gram‐negative bacteria

Sassi

Nguyen

Telek

et al. 2019

Microbial Biotechnology

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Summary Controlling and managing the degree of phenotypic diversification of microbial populations is a challenging task. This task not only requires detailed knowledge regarding diversification mechanisms but also advanced technical set‐ups for the real‐time analyses and control of population behaviour on single‐cell level. In this work, set‐up, design and operation of the so called segregostat are described which, in contrast to a traditional chemostat, allows the control of phenotypic diversification of microbial populations over time. Two exemplary case studies will be discussed, i.e. phenotypic diversification dynamics of Eschericia coli and Pseudomonas putida based on outer membrane permeabilization, emphasizing the applicability and versatility of the proposed approach. Upon nutrient limitation, cell population tends to diversify into several subpopulations exhibiting distinct phenotypic features (non‐permeabilized and permeabilized cells). Online analysis leads to the determination of the ratio between cells in these two states, which in turn triggers the addition of glucose pulses in order to maintain a predefined diversification ratio. These results prove that phenotypic diversification can be controlled by means of defined pulse‐frequency modulation within continuously running bioreactor set‐ups. This lays the foundation for systematic studies, not only of phenotypic diversification but also for all processes where dynamics single‐cell approaches are required, such as synthetic co‐culture processes.

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“…Noisy gene expression is known to be beneficial under conditions that are stressful or are prone to change. This lets a cell hedge its bet and adapt to changing scenarios [6][7][8][9][10]. Study of the effects of noise on gene expression can therefore lead to a better understanding of the phenotypic variability in these systems.…”

Section: Introductionmentioning

confidence: 99%

Extrinsic noise acts to lower protein production at higher translation initiation rates

Sharma

2020

Preprint

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Any cellular process at the microscopic level is governed by both extrinsic and intrinsic noise. In this article, we incorporate extrinsic noise in a model of mRNA translation and carry out stochastic simulations of the same. We then evaluate various statistics related to the residence time of the ribosome on the mRNA and subsequent protein production. We also study the effect of slow codons. From our simulations, we show that noise in the translation initiation rate rather than the translation termination rate acts to significantly broaden the distribution of mRNA residence times near the membrane. Further, the presence of slow codons acts to increase the mean residence times. However, this increase also depends on the number and position of the slow codons on the lattice. We also show that the the slow codons act to mask any effect from the extrinsic noise themselves. Our results have implications towards a better understanding of the role the individual components play during the translation process.

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Escherichia colican survive stress by noisy growth modulation

Abstract: Gene expression can be noisy 1,2 , as can the growth of single cells 3,4 . Such cell-to-cell variation has 7 been implicated in survival strategies for bacterial populations [5][6][7] .

Cited by 11 publications

References 30 publications

Dynamic gene expression and growth underlie cell-to-cell heterogeneity inEscherichia colistress response

Dynamic gene expression and growth underlie cell-to-cell heterogeneity inEscherichia colistress response

Segregostat: a novel concept to control phenotypic diversification dynamics on the example of Gram‐negative bacteria

Extrinsic noise acts to lower protein production at higher translation initiation rates

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