31 research outputs found

    Antibiotic resistance mutations generated by wild-type and mutator strains.

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    <p>Growth rate (mean ± SD; <i>n</i> = 3) of mutants bearing the specified mutation. Dark grey bars indicate mutations corresponding to the mutational spectrum of each mutator. Frequency of occurrence of each mutation is shown (right axis). All substitutions observed are described to confer antibiotic resistance. (A) Mutations in <i>rpoB</i>, which confer rifampicin resistance. (B) Mutations in <i>rpsL</i>, which confer streptomycin resistance.</p

    Mutational spectrum effects on generation of antibiotic-resistant mutants of wild-type and mutator <i>E. coli.</i>

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    <p>(A) Characteristic colony size polymorphism generated by each strain in tetracycline (left), rifampicin (centre) and streptomycin (right). Resistance mutations to rifampicin and streptomycin impair bacterial growth to varying degrees, and are produced differentially according to mutational spectra. Tetracycline resistance serves here as a control, as resistance mutations in these strains show little variability for fitness. (B) Fitness distributions for antibiotic-resistant mutants generated by each strain. Histograms represent 42 independent growth rate estimations. Blue bars, <i>ΔmutY</i> (top); pink bars, <i>ΔmutT</i> (bottom). Wild-type reference values (grey bars) are placed behind those of each mutator. The greater diversity observed here compared to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003167#pgen-1003167-g001" target="_blank">Figure 1A</a> is a result of the larger number of independent cultures.</p

    Competition experiments for antibiotic-resistant mutants of wild-type and mutator <i>E. coli</i>.

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    <p>Fitness (mean ± SD; <i>n</i> = 4) of antibiotic-resistant mutants generated by <i>ΔmutY</i> (circles) and <i>ΔmutT</i> (squares). Fitness was calculated relative to the wild-type strain; dashed line indicates equal competitive ability. Note that the relative abundance of competing mutants is anticipated to vary among replications, as mutants were generated stochastically during the growth period prior to competition.</p

    DataSheet1.docx

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    <p>Antibiotic resistance is a major concern in public health worldwide, thus there is much interest in characterizing the mutational pathways through which susceptible bacteria evolve resistance. Here we use experimental evolution to explore the mutational pathways toward aminoglycoside resistance, using gentamicin as a model, under low and high mutation supply rates. Our results show that both normo and hypermutable strains of Escherichia coli are able to develop resistance to drug dosages > 1,000-fold higher than the minimal inhibitory concentration for their ancestors. Interestingly, such level of resistance was often associated with changes in susceptibility to other antibiotics, most prominently with increased resistance to fosfomycin. Whole-genome sequencing revealed that all resistant derivatives presented diverse mutations in five common genetic elements: fhuA, fusA and the atpIBEFHAGDC, cyoABCDE, and potABCD operons. Despite the large number of mutations acquired, hypermutable strains did not pay, apparently, fitness cost. In contrast to recent studies, we found that the mutation supply rate mainly affected the speed (tempo) but not the pattern (mode) of evolution: both backgrounds acquired the mutations in the same order, although the hypermutator strain did it faster. This observation is compatible with the adaptive landscape for high-level gentamicin resistance being relatively smooth, with few local maxima; which might be a common feature among antibiotics for which resistance involves multiple loci.</p

    Fitness under bile salts challenge.

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    <p>Black bars represent the mean results of competition experiments between the NR10831 Δ<i>dinF ara<sup>+</sup></i> (pCA24N) and its parental wild type strain NR10831 <i>ara<sup>−</sup></i> (pCA24N), and viceversa. Grey bars represent the mean results of competition experiment of strain NR10831Δ<i>dinF</i> (pDinF) <i>vs</i> NR10831 (pCA24N) in order to see the effect of the complemented mutant. Error bars represent 95% confidence intervals around the mean.</p

    Sequence alignment of DinF and NorM.

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    <p>Aligment (ClustalW) of sequences from E. coli K12 was done according to Uniprot tools (<a href="http://www.uniprot.org" target="_blank">http://www.uniprot.org</a>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034791#pone.0034791-Julka1" target="_blank">[42]</a>. Predicted transmembrane domains are highlighted in grey.</p

    Protein carbonylation.

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    <p>Bar graph quantitating the protein carbonylation (femtomoles of DNP) in cells harboring the empty vector pCA24N (black) or the <i>dinF</i>-containing plasmid pDinF (gray) in the wild type, Δ<i>dinF</i> and Δ<i>mutT</i> derivative strains, following treatment with 10 mM H<sub>2</sub>O<sub>2</sub> for 15 min. The data are the mean values from four separate experiments and error bars represent the standard deviation.</p

    Effect of <i>dinF</i> expression on spontaneous mutation rate.

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    <p>The upper graph shows the mutation rate (expressed as mutations/cell/generation) of the Lac<sup>−</sup> to Lac<sup>+</sup> reversion for the wild type NR10831 (F′CC101) and its mutant derivatives, Δ<i>dinF</i> and Δ<i>mutT</i> harboring either the empty vector pCA24N (black) or the plasmid expressing <i>dinF,</i> pDinF (gray). The lower plot shows the mutation rate to rifampicin resistance of the wild type BW25113 and its mutant derivatives Δ<i>dinF</i> and Δ<i>mutT</i> harboring the same plasmids. Values were calculated by the MMS-ML method. Error bars represent 95% confidence intervals.</p

    ROS levels in the <i>E. coli</i> wild type, <i>dinF</i> and <i>mutT</i> derivatives.

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    <p>Strains harboring either the empty vector pCA24N (black) or the <i>dinF</i>-containing plasmid pDinF (gray) treated with DHR. Data represent the mean values of three independent measurements of the spontaneous fluorescence of 15,000 cells as measured by flow cytometry. The error bars indicate the standard deviation of three independent replicates.</p
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