Ontology highlight
ABSTRACT:
PROVIDER: PRJNA725112 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14324400_1.fastq.gz | Fastqsanger.gz | |||
| SRR14324400_2.fastq.gz | Fastqsanger.gz | |||
| SRR14324500_1.fastq.gz | Fastqsanger.gz | |||
| SRR14324500_2.fastq.gz | Fastqsanger.gz | |||
| SRR14324401_1.fastq.gz | Fastqsanger.gz |
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Project description:Several groups have shown that through evolution experiments, tolerance and resistance evolved rapidly under cyclic antibiotic treatment. In other words, intermittent antibiotic exposure performed in a typical adaptive laboratory evolution (ALE) experiments will “train” the bacteria to become tolerant/resistant to the drug. Although ALE has added new knowledge regarding the impact of varying treatment conditions on the evolution of tolerance/resistance, the role of some parameters such as population bottlenecks remains poorly understood. In this study, we employed ALE to investigate the evolution of methicillin-resistant S. aureus under repetitive daptomycin treatment using a modified protocol that incorporated population bottleneck following antibiotic exposure. We observed that although tolerance development is slower under bottlenecking conditions, the populations finally attained tolerance mutation in the yycH gene after twelve cycles of treatment. Extending the evolution experiment and changing the treatment scheme to a fast evolution protocol (treatment during exponential phase without bottlenecking) led to the emergence of daptomycin resistance (mutation in mprF gene). Through proteomics, we uncovered the differential adaptation strategies of these daptomycin tolerant and resistant MRSA strains, and how they respond differently to antibiotics compared to the ancestral wild-type.
2022-07-16 | PXD031078 | Pride
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin). We treated Escherichia coli cells with a highly toxic level of ciprofloxacin (gyrase inhibitor) for RNA extraction and hybridization on Affymetrix microarrays. We planned to find genotype specific transcriptional responses using WT control (BW25113) and fur-knockout mutant (selected from the KEIO collection) strains during antibiotic treatments. For each treatment type we used two biological replicates.
2014-09-11 | E-GEOD-55662 | biostudies-arrayexpress
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin).
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Project description:The evolution of antibiotic resistance is a clear example of adaptation by natural selection. Although a number of mutations contributing to the resistance have been identified, the relationship between the mutations and the related phenotypic changes responsible for the resistance has yet to be fully elucidated. To better characterize phenotype-genotype mapping for drug resistance, we performed parallel laboratory evolution of Escherichia coli under the selection of single antibiotics and after 90 days propagation obtained resistant strains. We find that an acquisition of resistance to one drug drastically changes the resistance and susceptibility to other drugs. Based on transcriptome data of these strains, we demonstrated that the resistances could be quantitatively predicted by the expression changes of a small number of genes. Whole-genome resequencing analysis provided several candidate mutations contributing to the resistances, while phenotype-genotype mapping was suggested to be complex and included various mutations that caused similar phenotypic changes. The integration of transcriptome and genome data enables us to extract essential phenotypic changes for drug resistances. To examine the contribution of the gene expression changes to the antibiotic resistances, transcriptome of the parent strain (duplicated) and 40 resistant strains (4 parallel-evolved resistant strains for 10 antibiotics) were analyzed.
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