Ontology highlight
ABSTRACT:
PROVIDER: PRJNA967250 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24426276_1.fastq.gz | Fastqsanger.gz | |||
| SRR24426276_2.fastq.gz | Fastqsanger.gz | |||
| SRR24426277_1.fastq.gz | Fastqsanger.gz | |||
| SRR24426277_2.fastq.gz | Fastqsanger.gz | |||
| SRR24426278_1.fastq.gz | Fastqsanger.gz |
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Project description:Methicillin-resistant Staphylococcus aureus clonal complex (CC) 398 has emerged from pigs to cause human infections in Europe and North America. We used a new 62-strain S. aureus microarray (SAM-62) to compare genomes of isolates from three geographical areas (Belgium, Denmark, and Netherlands) to understand how CC398 colonizes different mammalian hosts. The core genomes of 44 pig isolates and 32 isolates from humans did not vary. However, mobile genetic element (MGE) distribution was variable including SCCmec. Phi3 bacteriophage and human specificity genes (chp, sak, scn) were found in invasive human but not pig isolates. SaPI5 and putative ruminant specificity gene variants (vwb and scn) were common but not pig specific. Virulence and resistance gene carriage was host associated but country specific. We conclude MGE exchange is frequent in CC398 and greatest among populations in close contact. This feature may help determine epidemiological associations among isolates of the same lineage. [Data is also available from http://bugs.sgul.ac.uk/E-BUGS-120]
2012-01-21 | E-BUGS-120 | biostudies-arrayexpress
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.
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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.
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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.
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Project description:Staphylococcus aureus is a gram-positive cocci and an important human commensal bacteria and pathogen. S. aureus infections are increasingly difficult to treat because of the emergence of highly resistant MRSA (Methicillin-resistant S. aureus) strains. Here we present a method to study differential gene expression in S. aureus using high-throughput RNA-sequencing (RNA-seq). We use RNA-seq to examine the differential gene expression in S. aureus RN4220 cells containing an exogenously expressed transcription factor and between two S. aureus strains (RN4220 and NCTC8325-4). The information provided by RNA-seq was a significant advance over previously described microarray based techniques. We investigated the sequence and gene expression differences between RN4220 and NCTC8325-4 and used the RNA-seq data to identify S. aureus promoters suitable for in vitro analysis. We used RNA-seq to describe, on a genome wide scale, genes positively and negatively regulated by a phage encoded transcription factor, gp67. RNA-seq offers the ability to study differential gene expression with single-nucleotide resolution, and is a considerable improvement over the predominant genome-wide transcriptome technologies used in S. aureus. RNA-seq analysis of Staphylococcus aureus RN4220 (electrocompetent strain) carrying either empty pRMC2 (inducible expression vector) or pRMC2 carrying the ORF67 gene (encodes gp67). Both strains were grown to OD 0.2 and transgene expression was induced with 100ng/ml anhydrotetracycline. As a control, Staphylococcus aureus strain NCTC8325-4 (non-electrocompetent strain) was grown under identical conditions except without the addition of anhydrotetracycline.
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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.
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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.
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