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871 results for “escherichia coli”
Data from: Peptidoglycan-tethered and free forms of the Braun lipoprotein are in dynamic equilibrium in Escherichia coli
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A look beyond topography: transient phenomena of Escherichia coli cell division captured with high-speed in-line force mapping
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Data from: Dispensability of extrinsic DnaA regulators in Escherichia coli cell-cycle control
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Data from: Cross-feeding constrains the evolution of antibiotic resistance in <em>Escherichia coli</em>
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Data from: Antimicrobial peptide LL37 is potent against non-growing Escherichia coli cells despite a slower action rate
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Environment dependent costs and benefits of recombination in independently evolved populations of Escherichia coli
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The presence and abundance of Escherichia coli in beach sediment following a coastal renourishment project
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Disinfectant efficacy on mixed biofilms comprising Escherichia coli and spoilage microorganisms
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Data from: Antibiotics shift the temperature response curve of Escherichia coli growth
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Divergent evolution of mutation rates and biases in the long-term evolution experiment with Escherichia coli
Abstract All organisms encode enzymes that replicate, maintain, pack, recombine, and repair their genetic material. For this reason, mutation rates and biases also evolve by mutation, variation, and natural selection. By examining metagenomic time series of the Lenski long-term evolution experiment (LTEE) with Escherichia coli (Good, et al. 2017), we find that local mutation rate variation has evolved during the LTEE. Each LTEE population has evolved idiosyncratic differences in their rates of point mutations, indels, and mobile element insertions, due to the fixation of various hypermutator and antimutator alleles. One LTEE population, called Ara+3, shows a strong, symmetric wave pattern in its density of point mutations, radiating from the origin of replication. This pattern is largely missing from the other LTEE populations, most of which evolved missense, indel, or structural mutations in topA, fis, and dusB— loci that all affect DNA topology. The distribution of mutations in those genes over time suggests epistasis and historical contingency in the evolution of DNA topology, which may have in turn affected local mutation rates. Overall, the replicate populations of the LTEE have largely diverged in their mutation rates and biases, even though they have adapted to identical abiotic conditions.
Genomic signatures of UV resistance evolution in Escherichia coli depend on the growth phase during exposure
<p>Physiological states can determine the ability of organisms to handle stress. Does this mean that the same selection pressure will lead to different evolutionary outcomes, depending on the organisms' physiological state? If yes, what will be the genomic signatures of such adaptation(s)? We used experimental evolution in <i>Escherichia coli</i> followed by whole-genome whole-population sequencing to investigate these questions. The sensitivity of <i>Escherichia coli</i> to ultraviolet (UV) radiation depends on the growth phase during which it experiences the radiation. We evolved replicate <i>E. coli</i> populations under two different conditions of UV exposures, namely exposure during the lag and the exponential growth phases. Initially, the UV sensitivity of the ancestor was greater during the exponential phase than the lag phase. However, at the end of 100 cycles of exposure, UV resistance evolved to similar extents in both treatments. Genome analysis showed that mutations in genes involved in DNA repair, cell membrane structure and RNA polymerase were common in both treatments. However, different functional groups were found mutated in populations experiencing lag and exponential UV treatment. In the former, genes involved in transcriptional and translational regulations and cellular transport were mutated, whereas the latter treatment showed mutations in genes involved in signal transduction and cell adhesion. Interestingly, the treatments showed no phenotypic differences in a number of novel environments. Taken together, these results suggest that selection pressures at different physiological stages can lead to differences in the genomic signatures of adaptation, which need not necessarily translate into observable phenotypic differences.</p>
Data from: Core genes evolve rapidly in the long-term evolution experiment with Escherichia coli
Bacteria can evolve rapidly under positive selection owing to their vast numbers, allowing their genes to diversify by adapting to different environments. We asked whether the same genes that evolve rapidly in the long-term evolution experiment with Escherichia coli (LTEE) have also diversified extensively in nature. To make this comparison, we identified ~2000 core genes shared among 60 E. coli strains. During the LTEE, core genes accumulated significantly more nonsynonymous mutations than flexible (i.e., noncore) genes. Furthermore, core genes under positive selection in the LTEE are more conserved in nature than the average core gene. In some cases, adaptive mutations appear to modify protein functions, rather than merely knocking them out. The LTEE conditions are novel for E. coli, at least in relation to its evolutionary history in nature. The constancy and simplicity of the environment likely favor the complete loss of some unused functions and the fine-tuning of others.
Data from: Rapid MALDI-TOF mass spectrometry strain typing during a large outbreak of Shiga-Toxigenic Escherichia coli
Background: In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification. Methods: Specific peaks in the outbreak strain's spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak. Results: Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates. Conclusions: MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.
Data from: A comparison of methods to measure fitness in Escherichia coli
In order to characterize the dynamics of adaptation, it is important to be able to quantify how a population's mean fitness changes over time. Such measurements are especially important in experimental studies of evolution using microbes. The Long-Term Evolution Experiment (LTEE) with Escherichia coli provides one such system in which mean fitness has been measured by competing derived and ancestral populations. The traditional method used to measure fitness in the LTEE and many similar experiments, though, is subject to a potential limitation. As the relative fitness of the two competitors diverges, the measurement error increases because the less-fit population becomes increasingly small and cannot be enumerated as precisely. Here, we present and employ two alternatives to the traditional method. One is based on reducing the fitness differential between the competitors by using a common reference competitor from an intermediate generation that has intermediate fitness; the other alternative increases the initial population size of the less-fit, ancestral competitor. We performed a total of 480 competitions to compare the statistical properties of estimates obtained using these alternative methods with those obtained using the traditional method for samples taken over 50,000 generations from one of the LTEE populations. On balance, neither alternative method yielded measurements that were more precise than the traditional method.
Data from: Ecological and genetic determinants of plasmid distribution in Escherichia coli
Bacterial plasmids are important carriers of virulence and antibiotic resistance genes. Nevertheless, little is known of the determinants of plasmid distribution in bacterial populations. Here the factors affecting the diversity and distribution of the large plasmids of Escherichia coli were explored in cattle grazing on semi-natural grassland, a set of populations with low frequencies of antibiotic resistance genes. Critically, the population genetic structure of bacterial hosts was chararacterized. This revealed structured E. coli populations with high diversity between sites and individuals but low diversity within cattle hosts. Plasmid profiles, however, varied considerably within the same E. coli genotype. Both ecological and genetic factors affected plasmid distribution: plasmid profiles were affected by site, E. coli diversity, E. coli genotype and the presence of other large plasmids. Notably 3/26 E. coli serotypes accounted for half the observed plasmid-free isolates indicating that within species variation can substantially affect carriage of the major conjugative plasmids. The observed population structure suggest that most of the opportunities for within species plasmid transfer occur between different individuals of the same genotype and support recent experimental work indicating that plasmid–host coevolution, and epistatic interactions on fitness costs are likely to be important in determining occupancy.
Data from: Functional genotypes are associated with commensal Escherichia coli strain abundance within host individuals and populations
The selective pressures that determine genotype abundance and distribution frequently vary between ecological levels. Thus, it is often unclear whether the same functional genotypes will become abundant at different levels and how selection acting at these different scales are linked. In this study, we examined whether particular functional genotypes, defined by the presence or absence of 34 genes, of commensal E. coli strains were associated with within-host abundance and/or host population abundance in a wild population of 54 adult mountain brushtail possums (Trichosurus cunninghami). Our results revealed that there was a positive correlation between a strain's relative abundance within individuals and the strain's abundance in the host population. We also found that strain abundance at both ecological levels was predicted by the same group of functional genes (agn43, focH, micH47, iroN, ygiL, ompT, kspmT2 and K1) that had associated patterns of occurrence. We propose that direct selection on the same functional genes at both levels may in part be responsible for the observed correlation between the ecological levels. However, a potential link between abundance within the host and excretion rate may also contribute.
Data from: Evolution of organismal stoichiometry in a long-term experiment with Escherichia coli
Organismal stoichiometry refers to the relative proportion of chemical elements in the biomass of organisms, and it can have important effects on ecological interactions from population to ecosystem scales. Although stoichiometry has been studied extensively from an ecological perspective, much less is known about the rates and directions of evolutionary changes in elemental composition. We measured carbon, nitrogen and phosphorus content of 12 Escherichia coli populations that evolved under controlled carbon-limited, serial-transfer conditions for 50 000 generations. The bacteria evolved higher relative nitrogen and phosphorus content, consistent with selection for increased use of the more abundant elements. Total carbon assimilated also increased, indicating more efficient use of the limiting element. We also measured stoichiometry in one population repeatedly through time. Stoichiometry changed more rapidly in early generations than later on, similar to the trajectory seen for competitive fitness. Altogether, our study shows that stoichiometry evolved over long time periods, and that it did so in a predictable direction, given the carbon-limited environment.
Tunable force transduction through the Escherichia coli cell envelope
<p>Killing Assays, SDS Assays, Microscopy profiles and segmented cells (.res files for MicrobeJ).</p>
Escherichia coli simulated reads
<p>Collection of reads generated with Badread, with settings "Nanopore 2023", from a collection of <em>Escherichia coli </em>strains.</p>
MATLAB results files of MS-based analysis and raw photometer data - Systematic identification of allosteric effectors in Escherichia coli metabolism
<p>MATLAB result tables from progress curve analysis for each of the 19 enzymes tested with 79 potential effectors metabolites in MS-based approach. Excel tables with labelled photometer data.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.