Ontology highlight
ABSTRACT:
PROVIDER: PRJNA415102 | ENA |
REPOSITORIES: ENA
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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 | MODEL2007110001 | 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.
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.
2022-02-16 | MODEL2007150002 | BioModels
Project description:Antibiotic use can lead to expansion of multi-drug resistant pathobionts within the gut microbiome that can cause life-threatening infections. Selective alternatives to conventional antibiotics are in dire need. Here, we describe a Klebsiella PhageBank that enables the rapid design of antimicrobial bacteriophage cocktails to treat multi-drug resistant Klebsiella pneumoniae. Using a transposon library in carbapenem-resistant K. pneumoniae, we identified host factors required for phage infection in major Klebsiella phage families. Leveraging the diversity of the PhageBank and experimental evolution strategies, we formulated combinations of phages that minimize the occurrence of phage resistance in vitro. Optimized bacteriophage cocktails selectively suppressed the burden of multi-drug resistant K. pneumoniae in the mouse gut microbiome and drove bacterial populations to lose key virulence factors that act as phage receptors. Further, phage-mediated diversification of bacterial populations in the gut enabled co-evolution of phage variants with higher virulence and a broader host range. Altogether, the Klebsiella PhageBank represents a roadmap for both phage researchers and clinicians to enable phage therapy against a critical multidrug-resistant human pathogen.
2024-10-01 | GSE272297 | GEO
Project description:The emergence of multi-drug resistant pathogens is a major public health problem, leading to rethink and innovate in our bacterial control strategies. Here, we explore the anti-biofilm and anti-virulence activities of nineteen 6-polyaminosterol derivatives (squalamine-based), presenting a modulation of their polyamine side chain, on 4 major pathogens, i.e. carbapenem-resistant A. baumannii (CRAB) and P. aeruginosa (CRPA), a methicillin-resistant S. aureus (MRSA) and a vancomycin-resistant E. faecium (VRE) strains. We screened the effect of these derivatives on biofilm formation and eradication. 4e (for CRAB, VRE and MRSA) and 4f (for all the strains) were the most potent one and displayed activities as good as conventional antibiotics. We also identified 11 compounds able to decrease by more than 40% the production of pyocyanin, a major virulence factor of P. aeruginosa. We demonstrated that 4f treatment acts against bacterial infections in Galleria mellonella and significantly prolonged the larvae survival (from 50% to 80%) after 24 h of CRAB, VRE and MRSA infections. As shown by proteomic studies, 4f triggered distinct cellular responses depending on the bacterial species, but essentially related to the cell envelop. Its interesting anti-biofilm and anti-virulence properties make it promising candidate for use in therapeutics.
2024-05-22 | PXD047333 | Pride
Project description:Multi drug resistant Pseudomonas aeruginosa
| PRJNA869185 | ENA