TRS-PCR profiles correlate with polymorphisms of the genomic o454-nlpD region, virulence factors repertoire, and phylogenetic groups among uropathogenic Escherichia coli strains isolated from patients from Lodz region, Poland.

Extraintestinal urinary tract infections are mainly caused by uropathogenic strains of E. coli. UPECs are a heterogeneous group of strains possessing various genes associated with virulence traits. It was demonstrated that changes in the composition of the o454-nlpD region and genetic variation in the mutS-rpoS chromosomal region in ExPEC strains are correlated with their virulence, particularly in those with the pattern III o454-nlpD region and belonging to phylogenetic group B2. In this study, we investigated the presence and distribution of the o454-nlpD genomic polymorphism in our collection of 124 uropathogenic E. coli strains, examining the correlation of o454-nlpD region types with the virulence factors studied. Our findings revealed a positive association between certain virulence factors in UPEC strains and the presence of pattern III in the o454-nlpD region. Additionally, all these strains were classified under phylogenetic group B2. We also showed that the highly pathogenic group of E. coli identified by examining the polymorphism of the o454-nlpD region coincides with the highly pathogenic group of uropathogens we identified in the averaged TRS-PCR analysis.

Numerical interpretation of TRS-PCR profiling results for Escherichia coli strains isolated from patients with bacteriuria in Lodz region, Poland.

With the multiplicity of existing methods to track E. coli infections, it still seems necessary to seek new, better and/or complementary ways for epidemiological investigations. Particularly, fast, cheap, effective and reproducible methods providing easily comparable results are needed. Our previous studies showed that the use of TRS-PCR is an effective molecular tool in E. coli epidemiology. In this paper, we have developed a unique classification scheme in which an individual TRS-PCR pattern is assigned a numerical value. This approach allows for rapid interpretation of the results obtained from several similarity dendrograms. Using this approach, based on CAC-PCR, GTG-PCR and CGG-PCR, we obtained 52, 86 and 99 different numerical types for the 124 analyzed uropathogenic E. coli strains, respectively. This allowed for the identification of 121 unique isolates differing in at least one TRS-PCR class. In this approach, we got numerical results, easy to sort and interpret, allowing easier analysis of these strains.

Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling.

The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling. Additionally, we have evaluated the possibility of using the BiSSE model for estimating parameters from genetic data. We analyzed a real dataset (from 251 E. coli strains) and confirmed previous biological observations demonstrating a prevalence of some virulence traits in specific bacterial sub-groups. The method may be used to predict pathogenicity of other bacterial taxa.

A new look at the drug-resistance investigation of uropathogenic E. coli strains.

Bacterial drug resistance and uropathogenic tract infections are among the most important issues of current medicine. Uropathogenic Escherichia coli strains are the primary factor of this issue. This article is the continuation of the previous study, where we used Kohonen relations to predict the direction of drug resistance. The characterized collection of uropathogenic E. coli strains was used for microbiological (the disc diffusion method for antimicrobial susceptibility testing), chemical (ATR/FT-IR) and mathematical (artificial neural networks, Ward's hierarchical clustering method, the analysis of distributions of inhibition zone diameters for antibiotics, Cohen's kappa measure of agreement) analysis. This study presents other potential tools for the epidemiological differentiation of E. coli strains. It is noteworthy that ATR/FT-IR technique has turned out to be useful for the quick and simple identification of MDR strains. Also, diameter zones of resistance of this E. coli population were compared to the population of E. coli strains published by EUCAST. We observed the bacterial behaviors toward particular antibiotics in comparison to EUCAST bacterial collections. Additionally, we used Cohen's kappa to show which antibiotics from the same class are closely related to each other and which are not. The presented associations between antibiotics may be helpful in selecting the proper therapy directions. Here we present an adaptation of interdisciplinary studies of drug resistance of E. coli strains for epidemiological and clinical investigations. The obtained results may be some indication in deciding on antibiotic therapy.

TRS-PCR profiling for discrimination of Escherichia coli strains isolated from children with diarrhea under 5 years of age in Lodz region, Poland.

Escherichia coli is one of the most frequently isolated gram-negative pathogens in cases of foodborne diseases and hospital infections. What is more, diarrheal diseases, including these associated with pathogenic E. coli strains, are leading causes of morbidity and mortality worldwide, especially among children. Improvements of the management of diarrheal diseases caused by these bacteria are in the spotlight of the World Health Organization. Therefore, there is still a need to develop new methods or improve ones that are commonly used to characterize and distinguish E. coli strains more precisely. In this work, TRS-based PCRs were effectively used for discrimination of 123 E. coli strains isolated from children with diarrhea in the Lodz region (Poland). The composite TRS-PCR approach, based on similarity comparisons of GTG-PCR and CGG-PCR fingerprints, enabled us to distinguish strains with very good efficacy. This was confirmed by the high diversity index (0.991) and high reproducibility of the band patterns obtained (95.0 %). These results showed the great variation in strains that may cause infections in children under 38 months. However, the stains were grouped in three separate clusters, which were different in terms of their phylogenetic affiliation and virulence factor repertoire. The obtained results support and are consistent with the need of public health surveillance for searching new and fast assays as far as children's health is concerned. TRS-PCR profiling is an effective tool for genotyping of E. coli strains isolated from children with diarrhea.