Lysobacteraceae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA344031 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Zoonotically transmitted species of Lysobacteraceae : Genome sequencing and assembly
| PRJNA400634 | ENA
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:Lysobacteraceae bacterium CU05-9 Genome sequencing and assembly
| PRJNA533999 | ENA
Project description:Copper is essential for both innate and adaptive immune function and copper resistance has emerged as an important determinant of virulence of microbial pathogens. In the human pathogen Streptococcus pneumoniae (Spn), cytoplasmic copper resistance is mediated by an operon encoding the copper-responsive repressor CopY, CupA, of unknown function, and CopA, a copper effluxing P1B-type ATPase. We show that CupA is a novel cell membrane-anchored Cu(I) chaperone for CopA, and that a Cu(I)-binding competent, membrane-localized CupA, like CopA, is obligatory for copper resistance.
2013-05-24 | GSE39176 | GEO
Project description:Thermomacidophilic archaea, such as Metallosphaera sedula, are lithoautotrophs that occupy metal-rich environments. In previous studies, a M. sedula mutant lacking the primary copper efflux transporter, CopA, became copper sensitive. In contrast, the basis for supra-normal copper resistance remained unclear in the spontaneous M. sedula mutant, CuR1. Here, transcriptomic analysis of copper-shocked cultures indicated that CuR1 had a unique regulatory response to metal challenge corresponding to up-regulation of 55 genes. Genome re-sequencing identified 17 confirmed mutations unique to CuR1 that were likely to change gene function. Of these, 12 mapped to genes with annotated function associated with transcription, metabolism or transport. These mutations included 7 non-synonymous substitutions, 4 insertions and 1 deletion. One of the insertion mutations mapped to pseudogene, Msed_1517, and extended its reading frame an additional 209 amino acids. The extended mutant allele was identified as a homolog of Pho4, a family of phosphate symporters that include the bacterial PitA proteins. Orthologs of this allele were apparent in related extremely thermoacidophilic species, suggesting M. sedula was naturally lacking this gene. Phosphate transport studies combined with physiologic analysis demonstrated M. sedula PitA was a low affinity high velocity secondary transporter implicated in copper resistance and arsenate sensitivity. Genetic analysis demonstrated spontaneous arsenate resistant mutants derived from CuR1 all underwent mutation in pitA and non-selectively became copper resistant. Taken together, these results point to archaeal PitA as a key requirement for the increased metal resistance of strain CuR1 and its accelerated capacity for copper bioleaching. The study comprises 5 samples, described in detail below. WT_CuR1: Differential transcriptional response of Metallosphaera sedula DSM 5348, WT, to the supra-normal copper resistant spontaneous Metallosphaera sedula mutant, CuR1 under normal growth conditions. This experiment was done to analyze the differential transcription of WT cells compared with CuR1 cells at mid log phase. WT-15_CuR1-15: Differential transcription of Metallosphaera cells under sub-inhibitory copper challenge (2.0 mM). This experiment was done to analyze the differential transcription of Metallosphaera sedula WT and CuR1 15 minutes post copper challenge. The copper cultures were harvested 15 minutes after the shock. WT-60_CuR1-60: Differential transcription of Metallosphaera cells under sub-inhibitory copper challenge (2.0 mM). This experiment was done to analyze the differential transcription of Metallosphaera sedula WT and CuR1 60 minutes post copper challenge. The copper cultures were harvested 60 minutes after the shock. WT-15_WT-60: Differential transcription of Metallosphaera cells under sub-inhibitory copper challenge (2.0 mM). This experiment was done to analyze the differential transcription of Metallosphaera sedula WT 15 and 60 minutes post copper challenge. The copper cultures were harvested 15 and 60 minutes after the shock, respectively. CuR1-15_CuR1-60: Differential transcription of Metallosphaera cells under sub-inhibitory copper challenge (2.0 mM). This experiment was done to analyze the differential transcription of Metallosphaera sedula CuR1 15 and 60 minutes post copper challenge. The copper cultures were harvested 15 and 60 minutes after the shock, respectively.
2014-07-10 | E-GEOD-59253 | biostudies-arrayexpress
Project description:The skin commensal yeast Malassezia is associated with several skin disorders. To establish a reference resource, we sought to determine the complete genome sequence of Malassezia sympodialis and identify its protein-coding genes. A novel genome annotation workflow combining RNA sequencing, proteomics, and manual curation was developed to determine gene structures with high accuracy.
2016-12-20 | PXD003773 | Pride
Project description:AbuOun2009 - Genome-scale metabolic network
of Salmonella typhimurium (iMA945)
This model is described in the article:
Genome scale reconstruction
of a Salmonella metabolic model: comparison of similarity and
differences with a commensal Escherichia coli strain.
AbuOun M, Suthers PF, Jones GI,
Carter BR, Saunders MP, Maranas CD, Woodward MJ, Anjum MF.
J. Biol. Chem. 2009 Oct; 284(43):
29480-29488
Abstract:
Salmonella are closely related to commensal Escherichia coli
but have gained virulence factors enabling them to behave as
enteric pathogens. Less well studied are the similarities and
differences that exist between the metabolic properties of
these organisms that may contribute toward niche adaptation of
Salmonella pathogens. To address this, we have constructed a
genome scale Salmonella metabolic model (iMA945). The model
comprises 945 open reading frames or genes, 1964 reactions, and
1036 metabolites. There was significant overlap with genes
present in E. coli MG1655 model iAF1260. In silico growth
predictions were simulated using the model on different carbon,
nitrogen, phosphorous, and sulfur sources. These were compared
with substrate utilization data gathered from high throughput
phenotyping microarrays revealing good agreement. Of the
compounds tested, the majority were utilizable by both
Salmonella and E. coli. Nevertheless a number of differences
were identified both between Salmonella and E. coli and also
within the Salmonella strains included. These differences
provide valuable insight into differences between a commensal
and a closely related pathogen and within different pathogenic
strains opening new avenues for future explorations.
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2015-07-30 | MODEL1507180009 | BioModels