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.
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.
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.
Project description:In this study, two multiantibiotic-resistant bacteria, Ochrobactrum intermedium (N1) and Stenotrophomonas acidaminiphila (N2), were isolated from the sludge of a PWWTP in Guangzhou, China. Whole-genome sequencing revealed that N1 and N2 had genome sizes of 0.52 Mb and 0.37 Mb, respectively, and harbored 33 and 24 ARGs, respectively. The main resistance mechanism in the identified ARGs included efflux pumps, enzymatic degradation, and target bypass, with the N1 strain possessing more multidrug-resistant efflux pumps than the N2 strain (22 vs 12). This also accounts for the broader resistance spectrum of N1 than of N2 in antimicrobial susceptibility tests. Additionally, both genomes contain numerous mobile genetic elements (89 and 21 genes, respectively) and virulence factors (276 and 250 factors, respectively), suggesting their potential for horizontal transfer and pathogenicity.
Project description:Incomplete antibiotic removal in pharmaceutical wastewater treatment plants (PWWTPs) could lead to the development and spread of antibiotic-resistant bacteria (ARBs) and genes (ARGs) in the environment, posing a growing public health threat. In this study, two multiantibiotic-resistant bacteria, Ochrobactrum intermedium (N1) and Stenotrophomonas acidaminiphila (N2), were isolated from the sludge of a PWWTP in Guangzhou, China. The N1 strain was highly resistant to ampicillin, cefazolin, chloramphenicol, tetracycline, and norfloxacin, while the N2 strain exhibited high resistance to ampicillin, chloramphenicol, and cefazolin. Whole-genome sequencing revealed that N1 and N2 had genome sizes of 0.52 Mb and 0.37 Mb, respectively, and harbored 33 and 24 ARGs, respectively. The main resistance mechanism in the identified ARGs included efflux pumps, enzymatic degradation, and target bypass, with the N1 strain possessing more multidrug-resistant efflux pumps than the N2 strain (22 vs 12). This also accounts for the broader resistance spectrum of N1 than of N2 in antimicrobial susceptibility tests. Additionally, both genomes contain numerous mobile genetic elements (89 and 21 genes, respectively) and virulence factors (276 and 250 factors, respectively), suggesting their potential for horizontal transfer and pathogenicity. Overall, this research provides insights into the potential risks posed by ARBs in pharmaceutical wastewater and emphasizes the need for further studies on their impact and mitigation strategies.