Noisy Response to Antibiotic Stress Predicts Subsequent Single-Cell Survival in an Acidic Environment

Mitosch, Karin; Rieckh, Georg; Bollenbach, Tobias

doi:10.1016/j.cels.2017.03.001

Cited by 83 publications

(98 citation statements)

References 86 publications

(115 reference statements)

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“…Fermentation products are known to acidify the medium Kleman and Strohl, 1994, which can activate the response to acid stress in some cells. Moreover, the fact that we find GadX and GadW as noise propagators is in accordance with a recent publication, where it was shown that heterogeneous expression of the gadBC operon (heavily regulated by GadX and GadW) correlated with single-cell survival to high acid induced by an antibiotic Mitosch et al , 2017.…”

Section: Noise Propagation Explains the Condition-dependent Noise Levsupporting

confidence: 93%

Noise propagation shapes condition-dependent gene expression noise inEscherichia coli

Urchueguía

Galbusera

Bellement-Theroue

et al. 2019

Preprint

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Although it is well appreciated that gene expression is inherently noisy and that transcriptional noise is encoded in a promoter's sequence, little is known about the variation in transcriptional noise across growth conditions. Using flow cytometry we here quantify transcriptional noise in E. coli genome-wide across 8 growth conditions, and find that noise and gene regulation are intimately coupled. Apart from a growth-rate dependent lower bound on noise, we find that individual promoters show highly condition-dependent noise and that condition-dependent expression noise is shaped by noise propagation from regulators to their targets. A simple model of noise propagation identifies TFs that most contribute to both conditionspecific and condition-independent noise propagation. The overall correlation structure of sequence and expression properties of E. coli genes uncovers that genes are organized along two principal axes, with the first axis sorting genes by their mean expression and evolutionary rate of their coding regions, and the second axis sorting genes by their expression noise, the number of regulatory inputs in their promoter, and their expression plasticity.

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Section: Noise Propagation Explains the Condition-dependent Noise Levsupporting

confidence: 93%

Noise propagation shapes condition-dependent gene expression noise inEscherichia coli

Urchueguía

Galbusera

Bellement-Theroue

et al. 2019

Preprint

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“…Studies on multidrug contexts highlight the roles of cellular respiration [34], ATP synthesis and polysaccharide synthesis [69] in determining treatment efficacy. Pretreatment with sub-lethal doses of single antibiotics induces physiological stress responses that protect against antibiotic lethality [60] and other environmental stresses [105]. Extended antibiotic exposure leads to genetically encoded resistance with collateral sensitivity or resistance to antibiotics of different classes [106], which may be exploited to potentiate population-level lethality by antibiotic cycling [107,108].…”

Section: Environmental Factorsmentioning

confidence: 99%

Antibiotic efficacy — context matters

Yang

Bening

Collins

2017

Current Opinion in Microbiology

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Antibiotic lethality is a complex physiological process, sensitive to external cues. Recent advances using systems approaches have revealed how events downstream of primary target inhibition actively participate in antibiotic death processes. In particular, altered metabolism, translational stress and DNA damage each contribute to antibiotic-induced cell death. Moreover, environmental factors such as oxygen availability, extracellular metabolites, population heterogeneity and multidrug contexts alter antibiotic efficacy by impacting bacterial metabolism and stress responses. Here we review recent studies on antibiotic efficacy and highlight insights gained on the involvement of cellular respiration, redox stress and altered metabolism in antibiotic lethality. We discuss the complexity found in natural environments and highlight knowledge gaps in antibiotic lethality that may be addressed using systems approaches.

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“…Of particular interest were recurring 299 mutations in gadX, a regulator of the acid response system, and the insertion sequences (IS1) in 300 dusB. Trimethoprim is known to induce an acid response in E. coli that results in up-regulation 301 of the gadX target genes gadB/C [38], and dusB is located in an operon upstream of the global E. 302 coli transcriptional regulator fis [39]. Thus, we wanted to test if mutations in DHFR and TYMS 303 alone were sufficient to explain the resistance phenotype.…”

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confidence: 99%

A two-enzyme adaptive unit within bacterial folate metabolism

Schober

Ingle

Park

et al. 2017

Preprint

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2The ability to predict cell behavior is complicated by an unknown pattern of functional interdependence among genes. Here, we use the conservation of gene proximity across species (synteny) to infer functional couplings between genes. For the folate metabolic pathway, we observe a sparse, modular architecture of interactions, with two small groups of genes coevolving in the midst of others that evolve independently. For one such module -dihydrofolate reductase and thymidylate synthase -we use epistasis measurements and forward evolution to demonstrate both internal functional coupling and independence from the remainder of the genome. Mechanistically, the coupling is driven by a constraint on their relative activities, which must be balanced to prevent accumulation of a metabolic intermediate. The results indicate an organization of cellular systems not apparent from inspection of biochemical pathways or physical complexes, and support the strategy of using evolutionary information to decompose cellular systems into functional units. Keywords:co-evolution, statistical genomics, folate metabolism, dihydrofolate reductase (DHFR), epistasis, experimental evolution . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/120006 doi: bioRxiv preprint first posted online Mar. 23, 2017; 3 IntroductionThe activity of one gene is often modified by the activity of other genes in the genome.This functional coupling between genes makes it difficult to predict cellular behavior as a whole from measurements of each gene (or protein) taken independently. As a consequence, our ability to rationally engineer new metabolic systems (Kim and Copley, 2012; Michener et al., 2014a; Michener et al., 2014b), and quantify the relationship between mutations and disease (Kondrashov et al., 2002; Zuk et al., 2012) is limited. Further, this interdependency amongst genes makes it non-trivial to understand how complex cellular systems are possible through an evolutionary process of stepwise variation with selection (Breen et al., 2012; Wagner and Altenberg, 1996; Weinreich et al., 2013). Thus, an ability to globally map functional couplings between genes and subsequently decompose cellular systems into quasi-independent moduleseach module consisting of several genes engaged in cooperative function -would help render biological systems tractable and predictable.However, it remains unclear if such a modular decomposition is possible, and if so, what the general strategy should be for finding it. A fundamental aspect of this problem is to distinguish functional couplings associated with core, conserved processes from those couplings that reflect species and/or environment specific adaptations. In this sense, we seek a general description of genetic interactions that can serve as a basis for guiding targeted experiments and modeling cellular systems. Here, we develop a map of pairwise gene interactions through ...

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Noisy Response to Antibiotic Stress Predicts Subsequent Single-Cell Survival in an Acidic Environment

Cited by 83 publications

References 86 publications

Noise propagation shapes condition-dependent gene expression noise inEscherichia coli

Noise propagation shapes condition-dependent gene expression noise inEscherichia coli

Antibiotic efficacy — context matters

A two-enzyme adaptive unit within bacterial folate metabolism

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