Mutation rate is reduced by increased dosage ofmutL gene in Escherichia coli K-12

This work was supported by the grants BIO2005-04278, LSHM-CT-2005-018705 and LSHM-CT-2005-518152.Peer reviewe

Mutation rate is reduced by increased dosage ofmutL gene in Escherichia coli K-12

This work was supported by the grants BIO2005-04278, LSHM-CT-2005-018705 and LSHM-CT-2005-518152.Peer reviewe

Increased Mutation Frequencies in Escherichia coli Isolates Harboring Extended-Spectrum β-Lactamases

Hypermutable (mutation frequency [f], ≥4 × 10(−8)) Escherichia coli strains were more frequently found (43%) in a collection of 89 extended-spectrum β-lactamase (ESBL)-producing isolates from different patients (77 pulsed-field gel electrophoresis clones, 12 ESBL types) than in non-ESBL E. coli (26%) strains (P = 0.03). Among urinary tract isolates, the frequency of hypermutation was 40% in ESBL versus 26% in non-ESBL isolates (P = 0.03)

Polymorphic Mutation Frequencies of Clinical and Environmental Stenotrophomonas maltophilia Populations▿

Mutation frequencies were studied in 174 Stenotrophomonas maltophilia isolates from clinical and nonclinical environments by detecting spontaneous rifampin-resistant mutants in otherwise-susceptible populations. The distribution of mutation frequencies followed a pattern similar to that found for other bacterial species, with a modal value of 1 × 10−8. Nevertheless, the proportion of isolates showing mutation frequencies below the modal value (hypomutators) was significantly higher for S. maltophilia than those so far reported in other organisms. Low mutation frequencies were particularly frequent among environmental S. maltophilia strains (58.3%), whereas strong mutators were found only among isolates with a clinical origin. These results indicate that clinical environments might select bacterial populations with high mutation frequencies, likely by second-order selection processes. In several of the strong-mutator isolates, functional-complementation assays with a wild-type allele of the mutS gene demonstrated that the mutator phenotype was due to the impairment of MutS activity. In silico analysis of the amino acid changes present in the MutS proteins of these hypermutator strains in comparison with the normomutator isolates suggests that the cause of the defect in MutS might be a H683P amino acid change

Phylogenetic tree based on concatenated MLST-genes (Con-MLST) using BEAST v1.5.4 program.

<p>Phylogroups were established with posterior probability >0.95. Discrepancies between multiplex PCR and phylogeny are shown as *(discrepancies using Clermont's protocol) and # (discrepancies using Doumith's protocol). The discrepancies affecting members belonging to non-detected phylogroups (C, F and E) using multiplex PCRs are shown close to the character defining the phylogroup. Forty-eight sequences of reference strains downloaded from GenBank were used in the analysis, but one strain for each phylogroup is shown.</p

Recombination Blurs Phylogenetic Groups Routine Assignment in <i>Escherichia coli</i>: Setting the Record Straight

<div><p>The characterization of population structures plays a main role for understanding outbreaks and the dynamics of bacterial spreading. In <i>Escherichia coli</i>, the widely used combination of multiplex-PCR scheme together with goeBURST has some limitations. The purpose of this study is to show that the combination of different phylogenetic approaches based on concatenated sequences of MLST genes results in a more precise assignment of <i>E. coli</i> phylogenetic groups, complete understanding of population structure and reconstruction of ancestral clones. A collection of 80 <i>Escherichia coli</i> strains of different origins was analyzed following the Clermont and Doumith's multiplex-PCR schemes. Doumith's multiplex-PCR showed only 1.7% of misassignment, whereas Clermont's-2000 protocol reached 14.0%, although the discrepancies reached 30% and 38.7% respectively when recombinant C, F and E phylogroups were considered. Therefore, correct phylogroup attribution is highly variable and depends on the clonal composition of the sample. As far as population structure of these <i>E. coli</i> strains, including 48 <i>E. coli</i> genomes from GenBank, goeBURST provides a quite dispersed population structure; whereas NeighborNet approach reveals a complex population structure. MLST-based eBURST can infer different founder genotypes, for instance ST23/ST88 could be detected as the founder genotypes for STC23; however, phylogenetic reconstructions might suggest ST410 as the ancestor clone and several evolutionary trajectories with different founders. To improve our routine understanding of <i>E. coli</i> molecular epidemiology, we propose a strategy based on three successive steps; first, to discriminate three main groups A/B1/C, D/F/E and B2 following Doumith's protocol; second, visualization of population structure based on MLST genes according to goeBURST, using NeighborNet to establish more complex relationships among STs; and third, to perform, a cost-free characterization of evolutionary trajectories in variants emerging along the clonal expansion using parsimony methods of phylogenetic analysis.</p></div

Network phylogenetic analysis based on Con-MLST obtained with NeighborNet algorithm in SplitsTree v.4.

<p>This representation allows inferring more complex interactions among the strains than goeBURST. The main phylogroups are differentiated in coloured circles. Members belonging to phylogroup C are located in two positions in the tree as two different patterns of recombination between B1 and A phylogroups were observed (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105395#pone-0105395-g005" target="_blank">Figure 5</a>).</p