Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

GNPS - Untargeted metabolomics of

ABSTRACT: 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.

INSTRUMENT(S): 6546 Q-TOF LC/MS (Agilent instrument model)

ORGANISM(S): Escherichia Coli (ncbitaxon:562)

SUBMITTER: Prof. Hannes Link

PROVIDER: MSV000094699 | GNPS | Tue May 07 04:39:00 BST 2024

REPOSITORIES: GNPS

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Untargeted metabolomics of " Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks."

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

GNPS - Targeted metabolomics of

Project description:Compilation of the targeted metabolomics data present in the associated paper: Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks. See "File names association" table in "supplementary files" to link file names with paper figures.

2024-05-07 | MSV000094698 | GNPS

Targeted metabolomics of " Metabolic mutations induce antibiotic resistance by pathway-specific bottlenecks."

2024-05-07 | MSV000094698 | MassIVE

Metabolic mutations induce antibiotic resistance by pathway specific bottlenecks.

Project description:Metabolic mutations induce antibiotic resistance by pathway specific bottlenecks.

| PRJEB75679 | ENA

Metabolic mutations induce antibiotic resistance by pathway-specific mechanisms and tolerance by slow-growth

Project description:Metabolic mutations induce antibiotic resistance

| PRJEB75208 | ENA

Drug-driven phenotypic convergence supports rational treatment strategies of chronic infections

Project description:Chronic Pseudomonas aeruginosa infections evades antibiotic therapy and are associated with mortality in cystic fibrosis (CF) patients. We find that in vitro resistance evolution of P.aeruginosa towards clinically relevant antibiotics leads to phenotypic convergence towards distinct states. These states are associated with collateral sensitivity towards several antibiotic classes and encoded by mutations in antibiotic resistance genes, including transcriptional regulator nfxB. Longitudinal analysis of isolates from CF patients reveals similar and defined phenotypic states, which are associated with extinction of specific sub-lineages in patients. In depth investigation of chronic P.aeruginosa populations in a CF patient during antibiotic therapy revealed dramatic genotypic and phenotypic convergence. Notably, fluoroquinolone-resistant subpopulations harboring nfxB mutations were eradicated by antibiotic therapy as predicted by our in vitro data. This study supports the hypothesis that antibiotic treatment of chronic infections can be optimized by targeting phenotypic states associated with specific mutations to improve treatment success in chronic infections.

2018-10-23 | PXD007972 | Pride

Network integrative genomic and transcriptomic analysis of carbapenem-resistant Klebsiella pneumoniae strains identifies genes for resistance and virulence

Project description:With the global increase in the use of carbapenems, several gram-negative bacteria have acquired carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is one of such notorious pathogen that is being widely studied to find novel resistance mechanisms and drug targets. These antibiotic-resistant clinical isolates generally harbor many genetic alterations, and identification of causal mutations will provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance, in which mutated genes that also show significant expression changes among their functionally coupled genes become more likely candidates. For network-based analyses, we developed a genome-scale co-functional network of K. pneumoniae genes, KlebNet (www.inetbio.org/klebnet). Using KlebNet, we could reconstruct functional modules for antibiotic-resistance, and virulence, and retrieved functional association between them. With complementation assays with top candidate genes, we could validate a gene for negative regulation of meropenem resistance and four genes for positive regulation of virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antimicrobial resistance and virulence of human pathogenic bacteria with genomic and transcriptomic profiles from antibiotic-resistant clinical isolates.

2018-06-10 | GSE115539 | GEO

Project description:Stress-specific antibiotic resistance mutations in Bacillus subtilis

| PRJNA703389 | ENA

Proteomic Investigation of Multiple Methicillin-Resistant Staphylococcus aureus strains with distinct Daptomycin Tolerance and Resistance Phenotypes

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. Using this experimental strategy, we performed in vitro laboratory evolution in MRSA using daptomycin, and mine novel daptomycin tolerance and resistance mutants, which were isolated at specific time points during the evolution experiments. Three daptomycin-tolerant isolates with different tolerance level were generated from our laboratory evolution (TOL2 and TOL5 with a mild-tolerance phenotype, and TOL6 with a high-tolerance phenotype). They all bear mutations at different genes, and have no increase in MIC towards daptomycin. Besides, we also isolated three daptomycin-resistant isolates (RES1, RES2, RES3) that have a single point mutation in the same gene, mprF, but at different locations, leading to an increased MIC towards daptomycin. 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.

2022-07-14 | PXD026741 | Pride

Transcriptome analyses reveal antibiotic-resistant pathways in Klebsiella pneumonia

Project description:The increasing antibiotic resistance of Klebsiella pneumoniae poses a serious threat to global public health. To investigate the antibiotic resistance mechanism of Klebsiella pneumonia, we performed gene expression profiling analysis using RNA-seq data for clinical isolates of Klebsiella pneumonia, KPN16 and ATCC13883. Our results showed that mutant strain KPN16 is likely to act against the antibiotics through increased increased butanoate metabolism and lipopolysaccharide biosynthesis, and decreased transmembrane transport activity.

2023-04-18 | GSE229867 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data