Escherichia coli
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA756839 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR16588249.fastq.gz | Fastqsanger.gz | |||
| SRR16588250.fastq.gz | Fastqsanger.gz | |||
| SRR16588251.fastq.gz | Fastqsanger.gz |
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Project description:Antibiotic resistance is increasingly becoming a serious challenge to public health. The regulation of metabolism by post-translational modifications (PTMs) has been widely studied; however, the comprehensive mechanism underlying the regulation of acetylation in bacterial resistance against antibiotics is unknown. Herein, with Escherichia coli as the model, we performed quantitative analysis of the acetylated proteome of wild-type sensitive strain (WT) and ampicillin- (Re-Amp), kanamycin- (Re-Kan), and polymyxin B-resistant (Re-Pol) strains. Based on bioinformatics analysis combined with biochemical validations, we found that a common regulatory mechanism exists between the different resistant strains. Acetylation negatively regulates bacterial metabolism to maintain antibiotic resistance, but positively regulates bacterial motility. Further analyses revealed that key enzymes in various metabolic pathways were differentially acetylated. Particularly, pyruvate kinase (PykF), a key glycolytic enzyme regulating bacterial metabolism, and its acetylated form were highly expressed in the three resistant types and were identified as reversibly acetylated by the deacetylase CobB and the acetyl-transferase PatZ, and also could be acetylated by non-enzyme AcP in vitro. Further, the deacetylation of Lys413 of PykF increased the enzyme activity by changing the conformation of ATP binding site of PykF, resulting in an increase in energy production, which in turn increased the sensitivity of drug-resistant strains to antibiotics. This study provides novel insights for understanding bacterial resistance and lays the foundation for future research on regulation of acetylation in antibiotic-resistant strains.
2022-10-14 | PXD030283 | Pride
Project description:Background: This study aimed to explore potential tobramycin-resistant mutagenesis of Escherichia coli (E. coli) strains after spaceflight. Methods: A spaceflight-induced mutagenesis of multi-drug resistant E.coli strain (T1_13) on the outer space for 64 days (ST5), and a ground laboratory with the same conditions (GT5) were conducted. Both whole-genome sequencing and RNA-sequencing were performed. Results: A total of 75 SNPs and 20 InDels were found to be associated with the resistance mechanism. Compared to T1_13, 1242 genes were differentially expressed in more than 20 of 38 tobramycin-resistant E. coli isolates while not in GT5. Function annotation of these SNPs/InDels related genes and differentially expressed genes was performed. Conclusion: This study provided clues for potential tobramycin-resistant spaceflight-induced mutagenesis of E. coli.
2019-12-13 | GSE123795 | GEO
Project description:RNA sequencing was performed on multiple E. coli strains grown on glucose minimal media
2019-12-17 | GSE122296 | GEO
Project description:<p>The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens.</p> <p>We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.</p>
| phs001260 | dbGaP
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: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:Escherichia coli laboratory strains remain instrumental to the discovery and development of biomarkers as drugs and diagnostic analytes in the post genomic era. The transcriptional regulator SlyA is a member of the multiple antibiotic resistance regulator family of transcription factors, which is associated with bacterial responses to host-derived oxidative stress, antibiotics resistance and virulence, and homologues exist in other Enterobacteriaceae. Here, we announce a transcriptome RNA sequencing data set detailing global gene expression in the wild type E. coli BW25113 and the slyA mutant. Results reveal heterogeneous functionality of SlyA that may vary between pathovars of E. coli. but which require further annotations of differentially expressed tRNAs
2021-03-16 | GSE168963 | GEO
Project description:The complex reservoir of metabolite-producing bacteria in the gastrointestinal tract contributes tremendously to human health and disease. Bacterial composition, and by extension gut metabolomic composition, is undoubtably influenced by the use of modern antibiotics. Herein, we demonstrate that polymyxin B, a last resort antibiotic used for chronic multidrug resistant infections infections, influences the production of the genotoxic metabolite colibactin from adherent-invasive Escherichia coli (AIEC) NC101. Colibactin can augment colorectal cancer (CRC) through DNA double stranded breaks and interstrand crosslinks. While the structure and biosynthesis of colibactin has been elucidated, chemical-induced regulation of its biosynthetic gene cluster and subsequent production of the genotoxin by pathogenic E. coli are largely unexplored. This research highlights the regulation of the colibactin-producing biosynthetic gene cluster under polymyxin stress. Using a multi-omic approach, we have identified that polymyxin stress enhances the abundance of colibactin biosynthesis proteins (Clb’s) in multiple pks+ E. coli strains, including pro-carcinogenic AIEC: NC101, the probiotic strain: E. coli Nissle 1917, and the antibiotic testing strain: E. coli ATCC 25922. Expression analysis via qPCR revealed that increased transcription of clb genes likely contributes to elevated Clb protein levels in NC101. Enhanced production of Clb’s by NC101 under polymyxin stress matched an increased production of the colibactin prodrug motif, a proxy for the mature genotoxic metabolite. Furthermore, E. coli with heightened tolerance for polymyxin antibiotics induced greater DNA damage, assessed by quantification of γH2AX staining in cultured intestinal epithelial cells. This study establishes a key link between the polymyxin B stress response and colibactin production in pks+ E. coli. Ultimately, our findings will inform future studies investigating colibactin regulation, the microbial response to antibiotics in the gut, and the ability of seemingly innocuous commensal microbes to induce host disease.
2021-07-15 | PXD025088 | Pride
Project description:fluoroquinolones resistant Escherichia coli strains
| PRJNA908892 | ENA