Ontology highlight
ABSTRACT:
PROVIDER: PRJNA839096 | ENA |
REPOSITORIES: ENA
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Project description:Methicillin-resistant Staphylococcus aureus (MRSA) infections result in more than 200,000 hospitalizations and 10,000 deaths in the United States each year and remain an important medical challenge. To better understand the transcriptome of Staphylococcus aureus USA300 NRS384, a community-acquired MRSA strain, we have conducted an RNA-Seq experiment on WT samples.
2017-11-15 | GSE102279 | GEO
Project description:Methicillin-resistant Staphylococcus aureus is one of the major causative agents associated to infections with a high morbidity and mortality in hospitals worldwide. In previous studies, we reported that lignan 3'-demethoxy-6-O-demethylisoguaiacin isolated and characterized from Larrea tridentata showed the best activity towards methicillin-resistant S. aureus. Understanding of mechanism of action of drugs allows design drugs in a better way. Therefore, we employed microarray to obtain gene expression profile of methicillin-resistant S. aureus after exposure to 3'-demethoxy-6-O-demethylisoguaiacin. The results showed that lignan had an effect on cell membrane affecting proteins of the ATP-binding cassette (ABC) transport system causing bacteria death.
2015-06-27 | GSE70309 | GEO
Project description:The Impact of CodY on Virulence Determinant Production in Community-Associated Methicillin Resistant Staphylococcus aureus
2012-05-17 | PRD000448 | Pride
Project description:Methicillin-resistant Staphylococcus aureus is one of the major causative agents associated to infections with a high morbidity and mortality in hospitals worldwide. In previous studies, we reported that lignan 3'-demethoxy-6-O-demethylisoguaiacin isolated and characterized from Larrea tridentata showed the best activity towards methicillin-resistant S. aureus. Understanding of mechanism of action of drugs allows design drugs in a better way. Therefore, we employed microarray to obtain gene expression profile of methicillin-resistant S. aureus after exposure to 3'-demethoxy-6-O-demethylisoguaiacin. The results showed that lignan had an effect on cell membrane affecting proteins of the ATP-binding cassette (ABC) transport system causing bacteria death. This study consisted of comparison of isolated RNA of MRSA not treated and MRSA treated with lignan 3'-demethoxy-6-O-demethylisoguaiacin. Both RNAs samples were differentially dyed with Cy3 and Cy5 during cDNA synthesis and hybridized on DNA chip. Afterwards, the chip was scanned in a GenePix 4000B scanner. The resulting gene expression profile was analyzed in databases for functional annotations to find a potential mechanism of the lignan in MRSA.
2015-06-27 | E-GEOD-70309 | biostudies-arrayexpress
Project description:Background: Telavancin is a novel semi-synthetic lipoglycopeptide derivative of vancomycin with a decylaminoethyl side chain that is active against Gram-positive bacteria including Staphylococcus aureus strains resistant to methicillin or vancomycin. This study describes transcriptome alterations in S. aureus strain ATCC29213 treated with telavancin for 15 min and 60 min in comparing with other agents treatment, including vancomycin, enduracidin, m-chlorophenylhydrazone.
2012-04-14 | GSE37272 | GEO
Project description:Methicillin-resistant Staphylococcus aureus
| PRJNA66999 | ENA
Project description:Resolving chromatin remodeling-linked gene expression changes is important for understanding disease states. We describe MAGICAL (Multiome Accessible Gene Integration Calling And Looping), a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, regulatory sites and genes as regulatory circuits. By introducing hidden Bayesian variables to allow modeling noise and signal variation across cells and conditions in both transcriptome and chromatin data, in systemic evaluations MAGICAL achieved high accuracy on circuit prediction at cell-type resolution. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single cell data that we generated from infected subjects and healthy uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be sepsis activated. We addressed the challenging problem of distinguishing methicillin-resistant- (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA) infections, where differential expression analysis failed to show predictive value. MAGICAL, however, identified epigenetic circuit biomarkers that distinguished MRSA from MSSA.
2023-05-19 | GSE220188 | GEO
Project description:Resolving chromatin remodeling-linked gene expression changes is important for understanding disease states. We describe MAGICAL (Multiome Accessible Gene Integration Calling And Looping), a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, regulatory sites and genes as regulatory circuits. By introducing hidden Bayesian variables to allow modeling noise and signal variation across cells and conditions in both transcriptome and chromatin data, in systemic evaluations MAGICAL achieved high accuracy on circuit prediction at cell-type resolution. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single cell data that we generated from infected subjects and healthy uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be sepsis activated. We addressed the challenging problem of distinguishing methicillin-resistant- (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA) infections, where differential expression analysis failed to show predictive value. MAGICAL, however, identified epigenetic circuit biomarkers that distinguished MRSA from MSSA.
2023-05-19 | GSE222548 | GEO
Project description:Proteomic profiles of methicillin-resistant Staphylococcus aureus and its Sle1 mutant grown with or without oxacillin
2024-05-06 | PXD052035 | iProX
Project description:Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes.Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.
2022-02-16 | MODEL2007110001 | BioModels