Ontology highlight
ABSTRACT:
PROVIDER: PRJNA450591 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7013931_1.fastq.gz | Fastqsanger.gz | |||
| SRR7013931_2.fastq.gz | Fastqsanger.gz | |||
| SRR7013932_1.fastq.gz | Fastqsanger.gz | |||
| SRR7013932_2.fastq.gz | Fastqsanger.gz | |||
| SRR7013933_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 16 |
Similar Datasets
Project description:Metabolic mutations induce antibiotic resistance
| PRJEB75208 | ENA
Project description:Cationic antimicrobial peptides (CAPs) are promising novel alternatives to conventional antibacterial agents, but the overlap in resistance mechanisms between small-molecule antibiotics and CAPs is unknown. Does evolution of antibiotic resistance decrease (cross-resistance) or increase (collateral sensitivity) susceptibility to CAPs? We systematically addressed this issue by studying the susceptibilities of a comprehensive set of antibiotic resistant Escherichia coli strains towards 24 antimicrobial peptides. Strikingly, antibiotic resistant bacteria frequently showed collateral sensitivity to CAPs, while cross-resistance was relatively rare. We identified clinically relevant multidrug resistance mutations that simultaneously elevate susceptibility to certain CAPs. Transcriptome and chemogenomic analysis revealed that such mutations frequently alter the lipopolysaccharide composition of the outer cell membrane and thereby increase the killing efficiency of membrane-interacting antimicrobial peptides. Furthermore, we identified CAP-antibiotic combinations that rescue the activity of existing antibiotics and slow down the evolution of resistance to antibiotics. Our work provides a proof of principle for the development of peptide based antibiotic adjuvants that enhance antibiotic action and block evolution of resistance.
2018-03-29 | GSE96706 | GEO
Project description:Bacterial evolution of antibiotic resistance frequently has deleterious side effects on microbial growth, virulence, and susceptibility to other antimicrobial agents. However, it is unclear how these trade-offs could be utilized for manipulating antibiotic resistance in the clinic, not least because the underlying molecular mechanisms are poorly understood. Using laboratory evolution, we demonstrate that clinically relevant resistance mutations in Escherichia coli constitutively rewire a large fraction of the transcriptome in a repeatable and stereotypic manner. Strikingly, lineages adapted to functionally distinct antibiotics and having no resistance mutations in common show a wide range of parallel gene expression changes that alter oxidative stress response, iron homeostasis, and the composition of the bacterial outer membrane and cell surface. These common physiological alterations are associated with changes in cell morphology and enhanced sensitivity to antimicrobial peptides. Finally, the constitutive transcriptomic changes induced by resistance mutations are largely distinct from those induced by antibiotic stresses in the wild-type. This indicates a limited role for genetic assimilation of the induced antibiotic stress response during resistance evolution. Our work suggests that diverse resistance mutations converge on similar global transcriptomic states that shape genetic susceptibility to antimicrobial compounds.
2023-01-26 | GSE223493 | GEO
Project description:Bacteria often evolve antibiotic resistance through mutagenesis. However, the processes causing the mutagenesis have not been fully resolved. Here we found that a broad range of ribosome-targeting antibiotics caused mutations through an underexplored pathway. Focusing on the clinically important aminoglycoside gentamicin, we found that the translation inhibitor caused genome-wide premature stalling of RNA polymerase (RNAP) in a loci-dependent manner. Further analysis showed that the stalling was caused by disruption of transcription-translation coupling. Anti-intuitively, the stalled RNAPs subsequently induced lesions to the DNA via transcription-coupled repair. While most of the bacteria were killed by genotoxicity, a small subpopulation acquired mutations via SOS-induced mutagenesis. Given that these processes were triggered shortly after antibiotic addition, resistance rapidly emerged in the population. Our work revealed a new mechanism of action of ribosomal antibiotics, illustrates the importance of dissecting the complex interplay between multiple molecular processes in understanding antibiotic efficacy, and suggests new strategies for countering the development of resistance.
2024-05-15 | GSE267245 | GEO
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.
2014-09-17 | E-GEOD-59408 | biostudies-arrayexpress
Project description:Untargeted metabolomics dataset for the paper "Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks "
These are the raw files for metabolites of all 41 isolates in Figure 4b of the paper.
2024-05-07 | MSV000094699 | GNPS
Project description:We compared the dynamics and mechanisms of resistance development to ceftazidime, meropenem, ciprofloxacin, and ceftolozane-tazobactam in wild-type (PAO1) and mutator (PAOMS, M-bM-^HM-^FmutS) P. aeruginosa. The strains were incubated for 24 h with 0.5 to 64M-CM-^W MICs of each antibiotic in triplicate experiments. The tubes from the highest antibiotic concentration showing growth were reinoculated in fresh medium containing concentrations up to 64M-CM-^W MIC for 7 consecutive days. The susceptibility profiles and resistance mechanisms were assessed in two isolated colonies from each step, antibiotic, and strain. Ceftolozane-tazobactam-resistant mutants were further characterized by whole-genome analysis through RNA sequencing (RNA-seq). The development of high-level resistance was fastest for ceftazidime, followed by meropenem and ciprofloxacin. None of the mutants selected with these antibiotics showed cross-resistance to ceftolozane-tazobactam. On the other hand, ceftolozane-tazobactam resistance development was much slower, and high-level resistance was observed for the mutator strain only. PAO1 derivatives that were moderately resistant (MICs, 4 to 8 ug/ml) to ceftolozane-tazobactam showed only 2 to 4 mutations, which determined global pleiotropic effects associated with a severe fitness cost. High-level-resistant (MICs, 32 to 128 ug/ml) PAOMS derivatives showed 45 to 53 mutations. Major changes in the global gene expression profiles were detected in all mutants, but only PAOMS mutants showed ampC overexpression, which was caused by dacB or ampR mutations. Moreover, all PAOMS mutants contained 1 to 4 mutations in the conserved residues of AmpC (F147L, Q157R, G183D, E247K, or V356I). Complementation studies revealed that these mutations greatly increased ceftolozane-tazobactam and ceftazidime MICs but reduced those of piperacillin-tazobactam and imipenem, compared to those in wild-type ampC. Therefore, the development of high-level resistance to ceftolozane-tazobactam appears to occur efficiently only in a P. aeruginosa mutator background, in which multiple mutations lead to overexpression and structural modifications of AmpC. Mutants of Pseudomonas aeroginosa PAO1 and PAO1 M-bM-^HM-^FmutS against Ceftolozane-tazobactam were generated and analysed using RNA-Seq
2014-06-12 | E-GEOD-58390 | biostudies-arrayexpress
Project description:Antibiotic binding sites are located in important domains of essential enzymes and have been extensively studied in the context of resistance mutations, however their study is limited by positive selection. Using multiplex genome engineering1 to overcome this constraint, we generate and characterize a collection of 760 single residue mutants encompassing the entire rifampicin binding site of E. coli RNA polymerase (RNAP). By genetically mapping drug-enzyme interactions, we identify an alpha helix where mutations dramatically enhance or disrupt rifampicin binding. We find mutations in this region that prolong antibiotic binding, converting rifampicin from a bacteriostatic to bactericidal drug by inducing lethal DNA breaks. The latter are replication-dependent, indicating that rifampicin kills by causing detrimental transcription-replication conflicts at promoters. We also identify additional binding site mutations that greatly increase the speed of RNAP. Fast RNAP depletes the cell of nucleotides, alters cell sensitivity to different antibiotics, and provides a cold growth advantage. Finally, by mapping natural rpoB sequence diversity, we discover functional rifampicin binding site mutations that alter RNAP properties or confer drug resistance occur frequently in nature.
2023-08-01 | GSE236920 | GEO
Project description:Untargeted metabolomics dataset for the paper "Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks "
These are the raw files for metabolites of all 41 isolates in Figure 4b of the paper.
2024-05-07 | MSV000094699 | MassIVE