Staphylococcus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA503754 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR8246766.fastq.gz | Fastqsanger.gz | |||
| SRR8246767.fastq.gz | Fastqsanger.gz | |||
| SRR8246768.fastq.gz | Fastqsanger.gz |
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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 | MODEL2007150001 | BioModels
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.
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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.
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Project description:Staphylococci are major pathogens in humans and animals and emerging antibiotic-resistant strains have further increased the importance of this health issue. The existence of a genetic basis of host response to bacterial infections has been widely documented but the underlying mechanisms and genes are still largely unknown. Previously, two divergent lines of sheep selected on their milk somatic cell count called high and low SCS lines, have been showed to be respectively more and less susceptible to intra mammary infections (IMI). Transcriptional profiling of milk somatic cells (MSC) of high and low SCS sheep infected successively by S. epidermidis and S. aureus was performed to provide enhanced knowledge about the genetic basis of differential host response to IMI with Staphylococci. Gene expression in MSC of high and low SCS sheep collected 12h post-challenge was performed on a 15K gene ovine oligoarray (Agilent). MSC were mainly neutrophils. The high number of differentially expressed genes between the two bacterial strains indicated, among others, increased number of T-cells in MSC after S. aureus, compared to S. epidermidis challenge. Differential regulation of 366 genes between resistant and susceptible animals was largely associated with immune and inflammatory response (including pathogen recognition TLR2 pathway and cell migration), signal transduction, cell proliferation and apoptosis. Close biological connection between most of differentially expressed genes into Ingenuity Pathway Analysis networks further indicated consistency between the genes that were differentially-expressed between resistant and susceptible animals. Gene profiling in high and low SCS sheep provided strong candidates for biological pathway and gene underlying genetically determined resistance and susceptibility towards Staphylococci infections opening new fields for further investigation. Keywords: Staphylococcus epidermidis, Staphylococcus aureus, milk somatic cells, mammalian, transcriptome, immunity, mastitis 22 samples in a two-colour dye-swap experimental design
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Project description:Staphylococci are major pathogens in humans and animals and emerging antibiotic-resistant strains have further increased the importance of this health issue. The existence of a genetic basis of host response to bacterial infections has been widely documented but the underlying mechanisms and genes are still largely unknown. Previously, two divergent lines of sheep selected on their milk somatic cell count called high and low SCS lines, have been showed to be respectively more and less susceptible to intra mammary infections (IMI). Transcriptional profiling of milk somatic cells (MSC) of high and low SCS sheep infected successively by S. epidermidis and S. aureus was performed to provide enhanced knowledge about the genetic basis of differential host response to IMI with Staphylococci. Gene expression in MSC of high and low SCS sheep collected 12h post-challenge was performed on a 15K gene ovine oligoarray (Agilent). MSC were mainly neutrophils. The high number of differentially expressed genes between the two bacterial strains indicated, among others, increased number of T-cells in MSC after S. aureus, compared to S. epidermidis challenge. Differential regulation of 366 genes between resistant and susceptible animals was largely associated with immune and inflammatory response (including pathogen recognition TLR2 pathway and cell migration), signal transduction, cell proliferation and apoptosis. Close biological connection between most of differentially expressed genes into Ingenuity Pathway Analysis networks further indicated consistency between the genes that were differentially-expressed between resistant and susceptible animals. Gene profiling in high and low SCS sheep provided strong candidates for biological pathway and gene underlying genetically determined resistance and susceptibility towards Staphylococci infections opening new fields for further investigation. Keywords: Staphylococcus epidermidis, Staphylococcus aureus, milk somatic cells, mammalian, transcriptome, immunity, mastitis
2011-10-01 | GSE24925 | GEO