Epidemiology of Streptococcus pyogenes upper respiratory tract infections in Poland (2003-2017).

Streptococcus pyogenes (group A Streptococcus, GAS) is a major human pathogen and causes every year over 600 millions upper respiratory tract onfections worldwide. Untreated or repeated infections may lead to post-infectional sequelae such as rheumatic heart disease, a major cause of GAS-mediated mortality. There is no comprehensive, longitudinal analysis of the M type distribution of upper respiratory tract strains isolated in Poland. Single reports describe rather their antibiotic resistance patterns or focus on the invasive isolates. Our goal was to analyse the clonal structure of the upper respiratory tract GAS isolated over multiple years in Poland. Our analysis revealed a clonal structure similar to the ones observed in high-income countries, with M1, M12, M89, M28, and M77 serotypes constituting over 80% of GAS strains. The M77 serotype is a major carrier of erythromycin resistance and is more often correlated with upper respiratory tract infections than other serotypes.

Glutathione S-Transferase P1 Genetic Variant's Influence on the HbA1c Level in Type Two Diabetic Patients.

GST (glutathione S-transferases) are capable of influencing glucose homeostasis, probably through regulation of the response to oxidant stress. The aim of our study was to investigate the relationship between GSTP1 gene polymorphism and glycated hemoglobin (HbA1c) levels in type two diabetic (T2D) patients. A total of 307 T2D patients were included. Analysis of the GSTP1 gene polymorphism (rs1695) was conducted using the TaqMan qPCR method endpoint genotyping. HbA1c was determined using a COBAS 6000 autoanalyzer. A univariable linear regression and multivariable linear regression model were used to investigate the association between mean HbA1c level and GSTP1 gene polymorphism, age at T2D diagnosis, T2D duration, therapy with insulin, gender, BMI, smoking status. GSTP1 Val/Val genotype, age at T2D diagnosis, T2D duration and therapy with insulin were statistically significant contributors to HbA1c levels (p < 0.05). Multivariable regression analysis revealed that GSTP1 (Val/Val vs. Ile/Ile) was associated with higher HbA1c even after adjustment for variables that showed a statistically significant relationship with HbA1c in univariable analyses (p = 0.024). The results suggest that GSTP polymorphism may be one of the risk factors for higher HbA1c in T2D patients. Our study is limited by the relatively small sample size, cross-sectional design, and lack of inclusion of other oxidative stress-related genetic variants.

Pathogenic Factors Correlate With Antimicrobial Resistance Among Clinical Proteus mirabilis Strains.

Proteus mirabilis is the third most common etiological factor of urinary tract infection. It produces urease, which contributes to the formation of a crystalline biofilm, considered to be one of the most important virulence factors of P. mirabilis strains, along with their ability to swarm on a solid surface. The aim of this study was to analyze the pathogenic properties of two selected groups of clinical P. mirabilis isolates, antimicrobial susceptible and multidrug resistant (MDR), collected from hospitals in different regions in Poland. The strains were examined based on virulence gene profiles, urease and hemolysin production, biofilm formation, and swarming properties. Additionally, the strains were characterized based on the Dienes test and antibiotic susceptibility patterns. It turned out that the MDR strains exhibited kinship more often than the susceptible ones. The strains which were able to form a stronger biofilm had broader antimicrobial resistance profiles. It was also found that the strongest swarming motility correlated with susceptibility to most antibiotics. The correlations described in this work encourage further investigation of the mechanisms of pathogenicity of P. mirabilis.

Mathematical Analysis of Induced Antibiotic Resistance Among Uropathogenic Escherichia coli Strains.

The aim of the study was a profound insight into the antibiotic resistance development in uropathogenic Escherichia coli strains with the use of some mathematical and statistical methods. During the previous study some antibiotics (amoxicillin, ciprofloxacin, gentamycin, and tobramycin) were applied to induce the resistance of E. coli strains, which led to the generation of ∼120 derivative strains with changed antibiotic susceptibility profiles. In this work, quantitative analysis was performed based on the strains defined as values of vectors of susceptibility for all the antibiotics' use. The Pearson correlation coefficient was used to define the correlation dissimilarity (distance) of the strains, which was further applied to hierarchical clustering. Analogously, the antibiotics were presented as vectors of susceptibility values of all the investigated strains. Correlation and cluster analysis were performed for antibiotics. The hclust method from the R system with the Ward method was used as a class agglomeration method. Mathematical analysis revealed two types of statistically relevant interactions-between antibiotics and derivative strains, as well as between the effect of individual antibiotics on the bacterial strains. These observed correlations can play a potential role for modeling uropathogenic E. coli (UPEC) resistant changes, based on the particular antibiotic used to initiate resistance development, or a model helping to predict drug resistance interactions in various UPEC strains. The obtained results can lead to development of much more sophisticated mathematical models, which, in turn, can be a potentially useful tool as a drug resistance trend predictor, both for clinicians and epidemiologists.

Ciprofloxacin, amoxicillin, and aminoglycosides stimulate genetic and phenotypic changes in uropathogenic Escherichia coli strains.

Antibiotic therapy and its consequences in bacterial and human aspects are widely investigated. Despite this, the emergence of new multidrug resistant bacteria is still a current problem. The scope of our work included the observation of changes among uropathogenic Escherichia coli strains after the treatment with a subinhibitory concentration of different antibiotics. The sensitive strains with or without virulence factors were incubated with amoxicillin, ciprofloxacin, gentamycin, or tobramycin. After each passage, the E. coli derivatives were compared to their wild types based on their susceptibility profiles, virulence genes, biofilm formations and the fingerprint profiles of PCR products amplified with using the (N)(6)(CGG)(4) primer. It turned out that antibiotics caused significant changes in the repertoire of bacterial virulence and biofilm formation, corresponding to acquired cross-resistance. The genomic changes among the studied bacteria were reflected in the changed profiles of the CGG-PCR products. In conclusion, the inappropriate application of antibiotics may cause a rapid rise of Multidrug Resistant (MDR) strains and give bacteria a chance to modulate their own pathogenicity. This phenomenon has been easily observed among uropathogenic E. coli strains and it is one of the main reasons for recurrent infections of the urinary tract.

The genetic background of antibiotic resistance among clinical uropathogenic Escherichia coli strains.

The spreading mechanisms of antibiotic resistance are related to many bacterial and environment factors. The overuse of antibiotics is leading to an unceasing emergence of new multidrug resistant strains. This problem also concerns uropathogenic Escherichia coli strains, which is the most common pathogen causing urinary tract infections. The aim of this study was the genetic analysis of antibiotic resistance in comparison to the phenotypic background of E. coli strains. The characterized collection of E. coli strains isolated 10 years ago from the urine samples of patients with urinary tract infections was used for antimicrobial susceptibility testing (the disc diffusion method) and analysis of antibiotic resistance genes (PCR reaction, sequencing). Additionally, the presence of ESBL strains was analyzed. Fourteen genes were associated with resistance to beta-lactams, aminoglycosides, sulfonamides and quinolones. The genetic analysis revealed that blaTEM-1 and sul2 were present in almost all of the studied strains. Other drug-resistance genes were very rare or non-existent. Otherwise, the phenotypic resistance to fluoroquinolones was well correlated with the genotypic background of the studied bacteria. The presence of particular genes and specific mutations indicate a high bacterial potential to multidrug resistance. On the other hand, it needs to be emphasized that the standard disk diffusion test for the routine antimicrobial susceptibility analysis is still the best way to estimate the current situation of bacterial drug-resistance.

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.