Escherichia coli
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA324681 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3643540_1.fastq.gz | Fastqsanger.gz | |||
| SRR3643540_2.fastq.gz | Fastqsanger.gz | |||
| SRR3643550_1.fastq.gz | Fastqsanger.gz | |||
| SRR3643550_2.fastq.gz | Fastqsanger.gz | |||
| SRR3643541_1.fastq.gz | Fastqsanger.gz |
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Project description:We evolved Escherichia coli cells over 500 generations under five environments that include four abiotic stressors: osmotic, acidic, oxidative, n-butanol, and control The goal of the experiment: Bacterial populations have a remarkable capacity to cope with extreme environmental fluctuations in their natural environments. In certain cases, adaptation to one stressful environment provides a fitness advantage when cells are exposed to a second stressor, a phenomenon that has been coined as cross-stress protection. A tantalizing question in bacterial physiology is how the cross-stress behavior emerges during adaptation and what the genetic basis of acquired stress resistance is.
2013-02-28 | GSE39926 | GEO
Project description:Revealing the genetic basis of natural bacterial phenotypic divergence
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Project description:We evolved Escherichia coli cells over 500 generations under five environments that include four abiotic stressors: osmotic, acidic, oxidative, n-butanol, and control The goal of the experiment: Bacterial populations have a remarkable capacity to cope with extreme environmental fluctuations in their natural environments. In certain cases, adaptation to one stressful environment provides a fitness advantage when cells are exposed to a second stressor, a phenomenon that has been coined as cross-stress protection. A tantalizing question in bacterial physiology is how the cross-stress behavior emerges during adaptation and what the genetic basis of acquired stress resistance is. RNA profiles were obtained for six E. coli strains evolved for 500 generations under abiotic stressors; two technical replicates for each strain where sequenced by Illumina GAII analyzer
2013-02-28 | E-GEOD-39926 | biostudies-arrayexpress
Project description:Evolutionary potential, cross-stress behavior and the genetic basis of acquired stress resistance in Escherichia coli
| PRJNA172115 | ENA
Project description:Urinary tract infections (UTIs) represent a major burden across the population, although key facets of their pathogenesis challenge physicians and investigators alike. Escherichia coli epitomizes these obstacles: this Gram-negative bacterial species is the most prevalent agent of UTIs worldwide and can also colonize the urogenital tract in a phenomenon known as asymptomatic bacteriuria (ASB). Unfortunately, at the level of the organism, the relationship between symptomatic UTI and ASB is poorly defined, confounding our understanding of microbial pathogenesis and strategies for clinical management. Unlike diarrheagenic pathotypes of E. coli, the definition of uropathogenic E. coli (UPEC) remains phenomenologic, without conserved phenotypes and (known) genetic determinants that rigorously distinguish UTI- and ASB-associated strains. This manuscript provides a cross-disciplinary review of the current issues – from interrelated mechanistic and diagnostic perspectives – and describes new opportunities by which clinical resources can be leveraged to overcome molecular challenges. Specifically, we present our work harnessing a large collection of patient-derived isolates to identify features that do (and do not) distinguish UTI- from ASB-associated E. coli strains. Analyses of biofilm formation, previously reported to be higher in ASB strains, revealed extensive phenotypic heterogeneity that did not correlate with symptomatology. However, metabolomic experiments revealed distinct signatures between ASB and cystitis isolates, including species in the purine pathway (previously shown to be critical for intracellular survival during acute infection). Together, these studies demonstrate how large-scale, wild-type approaches can help dissect the physiology of colonization-versus-infection, suggesting that the molecular definition of UPEC may rest at the level of global bacterial metabolism.
2019-08-14 | ST001244 | MetabolomicsWorkbench
Project description:Investigation in bacterial transcriptomics is widely used to investigate gene regulation, bacterial susceptibility to antibiotics, host-pathogen interactions, and pathogenesis. Transcriptomics is crucially dependent on suitable methods to isolate and detect bacterial RNA. Microfluidic approaches offer ways of creating integrated point-of-care systems, analysing a sample from preparation, RNA isolation through to detection. Critical for on-chip diagnostics to deliver on their promise is that mRNA expression is not altered through the use microfluidic sample processing. Here, we investigate the impact on the use of a microfluidic sample processing system based on hydrodynamic separation upon RNA expression of bacteria isolated from blood to prove its suitability for further microfluidic test development.
2016-04-01 | GSE68064 | GEO
Project description:Despite the characterization of many aetiologic genetic changes. The specific causative factors in the development of sporadic colorectal cancer remain unclear. This study was performed to detect the possible role of Enteropathogenic Escherichia coli (EPEC) in developing colorectal carcinoma.
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Project description:Shimoni2009 - Escherichia Coli SOS
Simple model, involving only the basic components of the circuit, sufficient to explain the peaks in the promoter activities of recA and lexA.
This model is described in the article:
Stochastic analysis of the SOS response in Escherichia coli.
Shimoni Y, Altuvia S, Margalit H, Biham O
PloS one. 2009; 4(5):e5363
Abstract:
BACKGROUND: DNA damage in Escherichia coli evokes a response mechanism called the SOS response. The genetic circuit of this mechanism includes the genes recA and lexA, which regulate each other via a mixed feedback loop involving transcriptional regulation and protein-protein interaction. Under normal conditions, recA is transcriptionally repressed by LexA, which also functions as an auto-repressor. In presence of DNA damage, RecA proteins recognize stalled replication forks and participate in the DNA repair process. Under these conditions, RecA marks LexA for fast degradation. Generally, such mixed feedback loops are known to exhibit either bi-stability or a single steady state. However, when the dynamics of the SOS system following DNA damage was recently studied in single cells, ordered peaks were observed in the promoter activity of both genes (Friedman et al., 2005, PLoS Biol. 3(7):e238). This surprising phenomenon was masked in previous studies of cell populations. Previous attempts to explain these results harnessed additional genes to the system and deployed complex deterministic mathematical models that were only partially successful in explaining the results.
PRINCIPAL FINDINGS: Here we apply stochastic methods, which are better suited for dynamic simulations of single cells. We show that a simple model, involving only the basic components of the circuit, is sufficient to explain the peaks in the promoter activities of recA and lexA. Notably, deterministic simulations of the same model do not produce peaks in the promoter activities.
SIGNIFICANCE: We conclude that the double negative mixed feedback loop with auto-repression accounts for the experimentally observed peaks in the promoter activities. In addition to explaining the experimental results, this result shows that including additional regulations in a mixed feedback loop may dramatically change the dynamic functionality of this regulatory module. Furthermore, our results suggests that stochastic fluctuations strongly affect the qualitative behavior of important regulatory modules even under biologically relevant conditions, thus emphasizing the importance of stochastic analysis of regulatory circuits.
This model is hosted on BioModels Database and identified by: MODEL2937159804.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.
2005-01-01 | MODEL2937159804 | BioModels
Project description:Escherichia coli OP50 adaptation to C. elegans growth conditions - Genetic basis
| PRJNA594537 | ENA
Project description:Bacterial behavior has been observed to change during spaceflight. Higher final cell counts, enhanced biofilm formation, increased virulence, and reduced susceptibility to antibiotics have been reported to occur for cells cultured in space . Most of these phenomena are theorized as being an indirect effect of an altered extracellular environment, where the carbon source uptake is inhibited and excreted acidic byproducts buildup around the cell due to the lack of gravity-driven transport forces. However, to date neither spaceflight results, ground-based studies, physical measurement techniques nor computational approaches have provided sufficient evidence needed to confirm this model. Gene expression data from the Antibiotic Effectiveness in Space (AES-1) experiment, however, have now allowed us to look into the biomolecular processes behind these observations and showed a systematic activation of glucose starvation and acid resistance genes. These results corroborate the reduced mass transport model proposed to govern bacterial responses to spaceflight. Furthermore, the gene expression data suggests that metabolism was stimulated in space, which could play a role in causing the observed increase in bacterial cell concentrations in microgravity. Similarly, the decrease in extracellular pH may also be involved with the reported increase in virulence in space.
2016-11-15 | GSE82341 | GEO