Phenotypic and genomic characterization of Pseudomonas aeruginosa isolates recovered from catheter-associated urinary tract infections in an Egyptian hospital.

Catheter-associated urinary tract infections (CAUTIs) represent one of the major healthcare-associated infections, and Pseudomonas aeruginosa is a common Gram-negative bacterium associated with catheter infections in Egyptian clinical settings. The present study describes the phenotypic and genotypic characteristics of 31 P. aeruginosa isolates recovered from CAUTIs in an Egyptian hospital over a 3 month period. Genomes of isolates were of good quality and were confirmed to be P. aeruginosa by comparison to the type strain (average nucleotide identity, phylogenetic analysis). Clonal diversity among the isolates was determined; eight different sequence types were found (STs 244, 357, 381, 621, 773, 1430, 1667 and 3765), of which ST357 and ST773 are considered to be high-risk clones. Antimicrobial resistance (AMR) testing according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines showed that the isolates were highly resistant to quinolones [ciprofloxacin (12/31, 38.7 %) and levofloxacin (9/31, 29 %) followed by tobramycin (10/31, 32.5 %)] and cephalosporins (7/31, 22.5 %). Genotypic analysis of resistance determinants predicted all isolates to encode a range of AMR genes, including those conferring resistance to aminoglycosides, ß-lactamases, fluoroquinolones, fosfomycin, sulfonamides, tetracyclines and chloramphenicol. One isolate was found to carry a 422 938 bp pBT2436-like megaplasmid encoding OXA-520, the first report from Egypt of this emerging family of clinically important mobile genetic elements. All isolates were able to form biofilms and were predicted to encode virulence genes associated with adherence, antimicrobial activity, anti-phagocytosis, phospholipase enzymes, iron uptake, proteases, secretion systems and toxins. The present study shows how phenotypic analysis alongside genomic analysis may help us understand the AMR and virulence profiles of P. aeruginosa contributing to CAUTIs in Egypt.

Lytic bacteriophage vB_KmiS-Kmi2C disrupts biofilms formed by members of the Klebsiella oxytoca complex, and represents a novel virus family and genus.

AIMS: This study aimed to characterize the lytic phage vB_KmiS-Kmi2C, isolated from sewage water on a GES-positive strain of Klebsiella michiganensis. METHODS AND RESULTS: Comparative phylogenetic and network-based analyses were used to characterize the genome of phage vB_KmiS-Kmi2C (circular genome of 42 234 bp predicted to encode 55 genes), demonstrating it shared little similarity with other known phages. The phage was lytic on clinical strains of K. oxytoca (n = 2) and K. michiganensis (n = 4), and was found to both prevent biofilm formation and disrupt established biofilms produced by these strains. CONCLUSIONS: We have identified a phage capable of killing clinically relevant members of the K. oxytoca complex (KoC). The phage represents a novel virus family (proposed name Dilsviridae) and genus (proposed name Dilsvirus).

Antimicrobial resistance and virulence characteristics in ERIC-PCR typed biofilm forming isolates of P. aeruginosa.

Pseudomonas aeruginosa is a serious pathogen particularly in immunocompromised patients. In this work, 103 clinical isolates of P. aeruginosa were collected and classified into weak, moderate, and strong biofilm producers according to their biofilm forming abilities via tissue culture plate method. The antimicrobial resistance and the presence of different virulence genes were investigated via disc diffusion method and polymerase chain reaction respectively. Moreover, ERIC-PCR typing was performed to investigate the genetic diversity among the clinical isolates. No significant correlation was observed between biofilm formation and resistance to each antimicrobial agent. Similar observation was detected concerning the multidrug resistance and biofilm formation. Regarding virulence genes, algD gene was harbored by all isolates (100%). Only pelA and phzM were significantly prevalent in strong biofilm producers. Additionally, the mean virulence score was higher in strong biofilm producers (9.33) than moderate (8.62) and weak (7) biofilm producers. Moreover, there was a significant correlation between the overall virulence score of the isolates and its ability to form biofilm. ERIC-PCR genotyping revealed the presence of 99 different ERIC patterns based on 70% similarity, and the different ERIC patterns were categorized into 8 clusters. 100% similarity indicates the possibility of cross-colonization in P. aeruginosa infections.

Effects of Lysozyme, Proteinase K, and Cephalosporins on Biofilm Formation by Clinical Isolates of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic pathogen that can form biofilms, which confer resistance to immune clearance and antibacterial treatment. Therefore, effective strategies to prevent biofilm formation are warranted. Here, 103 P. aeruginosa clinical isolates were quantitatively screened for biofilm formation ability via the tissue culture plate method. The effects of lysozyme (hydrolytic enzyme) and proteinase K (protease) on biofilm formation were evaluated at different concentrations. Lysozyme (30 µg/mL), but not proteinase K, significantly inhibited biofilm formation (19% inhibition). Treatment of 24-hour-old biofilms of P. aeruginosa isolates with 50 times the minimum inhibitory concentrations (MICs) of ceftazidime and cefepime significantly decreased the biofilm mass by 32.8% and 44%, respectively. Moreover, the exposure of 24-hour-old biofilms of P. aeruginosa isolates to lysozyme (30 µg/mL) and 50 times MICs of ceftazidime or cefepime resulted in a significant reduction in biofilm mass as compared with the exposure to lysozyme or either antibacterial agent alone. The best antibiofilm effect (49.3%) was observed with the combination of lysozyme (30 µg/mL) and 50 times MIC of cefepime. The promising antibiofilm activity observed after treatment with 50 times MIC of ceftazidime or cefepime alone or in combination with lysozyme (30 µg/mL) is indicative of a novel strategy to eradicate pseudomonal biofilms in intravascular devices and contact lenses.

Comparison of Machine Learning Approaches for Prediction of Advanced Liver Fibrosis in Chronic Hepatitis C Patients.

BACKGROUND/AIM: Using machine learning approaches as non-invasive methods have been used recently as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy. This study aims to evaluate different machine learning techniques in prediction of advanced fibrosis by combining the serum bio-markers and clinical information to develop the classification models. METHODS: A prospective cohort of 39,567 patients with chronic hepatitis C was divided into two sets-one categorized as mild to moderate fibrosis (F0-F2), and the other categorized as advanced fibrosis (F3-F4) according to METAVIR score. Decision tree, genetic algorithm, particle swarm optimization, and multi-linear regression models for advanced fibrosis risk prediction were developed. Receiver operating characteristic curve analysis was performed to evaluate the performance of the proposed models. RESULTS: Age, platelet count, AST, and albumin were found to be statistically significant to advanced fibrosis. The machine learning algorithms under study were able to predict advanced fibrosis in patients with HCC with AUROC ranging between 0.73 and 0.76 and accuracy between 66.3 and 84.4 percent. CONCLUSIONS: Machine-learning approaches could be used as alternative methods in prediction of the risk of advanced liver fibrosis due to chronic hepatitis C.