Project description:Whole genome sequencing of SYBARIS Aspergillus spp. known to be multi-drug resistant and difficult to treat. Aim of this experiment is to investigate the genetic basis of susceptibility to disease and elucidate molecular mechanisms of drug resistance in these 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: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:An important, but rarely performed, test of Koch’s molecular postulates involves evaluating the capacity of candidate virulence genes to confer pathogenicity in otherwise non-virulent species. Unbiased genomic surveys of avirulent natural isolates might reveal rare variants possessing specific virulence features, which might prove useful in testing their functional sufficiency. Using a custom pan-genome array, we analyzed a panel of avirulent Burkholderia thailandensis (Bt) isolates related to Burkholderia pseudomallei (Bp), the causative agent of the often fatal human and animal disease melioidosis. We report the discovery of variant Bt isolates exhibiting isolated acquisition of a capsular polysaccharide biosynthesis gene cluster (BpCPS), long regarded as an critical species-specific virulence factor essential for Bp mammalian virulence. BpCPS-expressing Bt strains exhibited certain pathogen-related phenotypes including resistance to human complement binding, but did not exhibit enhanced virulence when assessed in two different in vivo animal infection models. Phylogenetic analysis revealed that the BpCPS-expressing Bt strains likely reside within an evolutionary subgroup distinct from the majority of previously-described Bt strains. Our findings suggest that BpCPS acquisition alone is unlikely to fully explain the ability of Bp to colonize humans and animals, highlighting the importance of other collaborating factors in the pathogenesis of mammalian melioidosis.
Project description:Burkholderia cepacia complex (Bcc) comprises opportunistic bacteria infecting hosts such as cystic fibrosis (CF) patients. Bcc long-term infection of CF patient airways has been associated with emergence of phenotypic variation. Here we studied two Burkholderia multivorans clonal isolates (D2095 and D2214) displaying different morphotypes from a chronically infected CF patient in order to evaluate traits development during lung infection. Since the custom array described in platform GPL13356 was based on Burkholderia multivorans ATCC 17616 genome, here we performed a DNA-DNA hybridization to determine which probes of the array hybridize with our test genomes
Project description:B. pseudomallei strain K96243 is sensitive to the drug ceftazidime (CAZ), but has been shown to exhibit transient CAZ tolerance when in a biofilm form. To investigate an observed shift in gene expression profile during ceftazidime (CAZ) tolerance and to better understand the mechanistic aspects of this transient tolerance, RNA-sequencing was performed on B. pseudomallei K96243 from the following three growth states: planktonic-free, biofilm, and planktonic shedding cells. Results indicated that the expression of 651 genes (10.97%) were significantly changed in both biofilm (resistant) and planktonic shedding (sensitive) cells in comparison to the planktonic state. Burkholderia biofilm shifts its transcriptome in response to ceftazidime exposure by regulating iron-sulfur stabilizing and metabolic-related genes.