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Targeting bacterial gyrase with cystobactamid, fluoroquinolone and aminocoumarin antibiotics induces distinct molecular signatures in Pseudomonas aeruginosa

ABSTRACT: Targeting bacterial gyrase with cystobactamid, fluoroquinolone and aminocoumarin antibiotics induces distinct molecular signatures in Pseudomonas aeruginosa

PROVIDER: PRJNA701395 | ENA |

REPOSITORIES: ENA

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Targeting bacterial gyrase with cystobactamid, fluoroquinolone and aminocoumarin antibiotics induces distinct molecular signatures in Pseudomonas aeruginosa

Project description:The design of novel antibiotics that break antimicrobial resistance relies on a profound understanding of their mechanism of action. While it has been shown that the cellular effects of antibiotics cluster according to their molecular targets, we investigated whether compounds binding to different sites of the same target can be differentiated by their transcriptome or metabolome signatures. The effects of three fluoroquinolones, two aminocoumarins and two cystobactamids, all inhibiting bacterial gyrase, on Pseudomonas aeruginosa at sub-inhibitory concentrations were captured by RNA sequencing.

2021-05-03 | GSE166602 | GEO

Targeting Bacterial Gyrase with Cystobactamid, Fluoroquinolone, and Aminocoumarin Antibiotics Induces Distinct Molecular Signatures in Pseudomonas aeruginosa.

Project description: Not available

| S-EPMC8407119 | biostudies-literature

Genome-wide mapping of fluoroquinolone-induced gyrase cleavage sites displays drug specific effects that correlate with bacterial persistence

Project description:Persisters are rare phenotypic variants that can survive bactericidal doses of antibiotics and resume growth after the conclusion of treatment. They are suspected to be culprits of recurrent infections, and are distinct from resistant mutants because they are genetically identical to bacteria that die from treatment. Persisters to fluoroquinolones (FQs) experience DNA damage from treatment in stationary-phase culture, which suggests that FQs can corrupt their primary target, DNA gyrase, even in these super-tolerant cells. Since DNA damage from FQs originates from its stabilization of DNA gyrase in complexes with cleaved DNA, we hypothesized that the characteristics of FQ-stabilized DNA gyrase cleavage sites (GCS), such as the abundance, and/or location, might be influential to persistence. To test this hypothesis, we measured genome-wide distributions of GCS after treatment with a panel of FQs.We found drug-specific effects on the location and abundances of GCSs and discovered a negative correlation between the number of GCSs and FQ persister levels. Further, additional experiments and analyses suggested that persister levels are not governed by cleavage to a single specific site, but rather survival is a more complex function with respect to GCSs. Together, these findings demonstrate that there are drug specific differences in GCSs that correlate with persister levels, and suggest that the ability of an FQ to stabilize DNA-gyrase complexes at more sites will improve its bactericidal ability.

2022-12-05 | GSE206608 | GEO

Effect of fluoroquinolone-induced gyrase cleavage sites on gene expression during drug treatment period and recovery period on E. coli

2022-12-05 | GSE206609 | GEO

Transcriptional consequences of DNA gyrase inhibition

Project description:DNA gyrase is an essential enzyme whose activity is required for DNA replication and chromosome maintenance. Inhibition of gyrase results in multiple physiological effects including changes in DNA superhelicity, replication arrest and DNA damage. Using genetic, genomic, statistical and biochemical techniques, we have untangled the contribution of individual effects, assessed their relative significance and concluded that: i) DNA replication is required for the formation of spatial transcriptional domains; ii) transcriptional response to gyrase inhibition is coordinated between at least two modules involved in DNA maintenance, relaxation and damage response; iii) genes whose transcriptional response to gyrase inhibition does not depend on the activity of topoisomerase I can be classified on the basis of the GC excess in their upstream and coding sequences into, respectively, activated and repressed by gyrase inhibition; iv) relaxation by topoisomerase I dominates the transcriptional response upon gyrase inhibition, followed by the effects of replication and RecA. Keywords: time course

2006-03-10 | GSE4408 | GEO

Fluoroquinolone-induced gyrase cleavage sites

Project description:This SuperSeries is composed of the SubSeries listed below.

2022-12-05 | GSE206610 | GEO

Gyrase binding in wild type and gyrA D82G mutant

Project description:Raw data for spatial pattern analysis of gyrase binding in E. coli MG1655 wild type and gyrA D82G mutant (ChIP-chip data) Keywords: other

2004-09-09 | GSE1735 | GEO

Transcription facilitated genome-wide recruitment of topoisomerase I and DNA gyrase

Project description:Genome-wide distribution of topoisomerase I and DNA gyrase is directed by transcription induced supercoiling

2017-01-31 | GSE85357 | GEO

Gyrase binding in wild type and gyrA D82G mutant

Project description:Raw data for spatial pattern analysis of gyrase binding in E. coli MG1655 wild type and gyrA D82G mutant (ChIP-chip data)

2004-09-09 | E-GEOD-1735 | biostudies-arrayexpress

Predictive signatures of 19 antibiotics-induced Escherichia coli proteomes

Project description:Identifying the mode of action (MOA) of antibacterial compounds is the fundamental basis for the development of new antibiotics, and the challenge increases with the emerging secondary and indirect effect from antibiotic stress. Although various omics-based system biology approaches of defining antibiotic MOA are currently available, they still need improved throughput, accuracy and comprehensiveness. Using high resolution accurate mass (HR/AM) based proteomics, we present here a comprehensive reference map of proteomic signatures of Escherichia coli under antibiotics challenge. With state-of-the-art label-free approach, we quantified > 1,500 protein groups in response to 19 FDA-approved antibiotics. Applying several machine learning techniques, we derived a panel of 14 proteins that can be used to classify antibiotics into different MOAs with nearly 100% accuracy. Interestingly, these proteins tend to mediate diverse bacterial cellular and metabolic processes. Transcriptomic level profiling correlates well with changes in protein expression in discriminating different antibiotics. Such expression signatures will aid future studies in identifying MOA of unknown compounds and facilitate the discovery of novel antibiotics. In summary, our study offers a practical approach for effective and rapid proteomic profiling, establishes a high quality reference compendium of microbial proteome in response to a wide range of antibiotics exposure, and provides a previously undescribed group of proteins and RNAs that allows rapid antibiotic classification and MOA determination.

2020-07-23 | PXD016074 | Pride

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