Characterization and genomic analysis of novel bacteriophage NK20 to revert colistin resistance and combat pandrug-resistant Klebsiella pneumoniae in a rat respiratory infection model

AIM

We investigated the therapeutic capacity of the isolated Klebsiella bacteriophage NK20 against pandrug-resistant strains. Moreover, we assessed the impact of resistance development on the overall therapeutic outcome both in vitro and in vivo.

MAIN METHODS

The pandrug-resistant K. pneumoniae Kp20 is used as a host strain for the isolation of bacteriophages using sewage samples. Spot assay was then used to compare the spectra of the isolated phages, while kinetic and genomic analysis of the phage with the broadest spectrum was assessed. Antibacterial potential of the phage was assessed using turbidimetric assay and MIC with and without colistin. Finally, the therapeutic efficacy was evaluated in vivo using a rat respiratory infection model.

KEY FINDINGS

The isolated lytic bacteriophage (NK20) showed a relatively broad spectrum and an acceptable genomic profile. In vitro antibacterial assay revealed bacterial resistance development after 12 h. Colistin inhibited bacterial regrowth and reduced pandrug-resistant strains' colistin MICs. Despite the isolation of resistant clones, intranasal administration of NK20 significantly (p < 0.05) reduced the bacterial load in both the pulmonary and blood compartments and rescued 100 % of challenged rats. Histological and immunological analysis of treated animals' lung tissue revealed less inflammation and lower TNF-α and caspase-3 expression.

SIGNIFICANCE

NK20 is a promising candidate that rescued rats from untreatable, pan-drug-resistant K. pneumoniae Kp20. Moreover, it steers the evolution of resistant mutants with higher sensitivity to colistin and less virulence, opening the door for using phages as sensitizing and anti-virulence entities rather than direct killer.

Exploring the potential efficacy of phage therapy for biocontrol of foodborne pathogenic extensively drug-resistant Escherichia coli in gastrointestinal tract of rat model

AIM

The emergence of extensively drug-resistant (XDR) Escherichia coli leaves little or no therapeutic options for the control of these foodborne pathogens. The goal is to isolate, characterize, and assess the potential efficacy of a bacteriophage in the treatment of an induced gastrointestinal tract infection.

MAIN METHODS

Sewage water was used to isolate phage phPE42. Transmission electron microscope was used for the visualization of phage morphology. Lysis profile, growth kinetics, and stability studies were determined. The ability of phage to eradicate biofilms was assessed by crystal violet staining, resazurin assay, compound bright field microscope, and confocal laser scanning microscope (CLSM). Moreover, the efficacy of phage phPE42 as a potential therapy was evaluated in a rat model.

KEY FINDINGS

A newly lytic Myoviridae phage phPE42 was isolated and exhibited broad coverage activity (48.6 %) against E. coli clinical isolates. It demonstrated favorable growth kinetics and relative stability under a variety of challenging conditions. The resazurin colorimetric assay and CLSM provided evidence of phage potential's ability to significantly (P < 0.05) decrease the viability of biofilm-embedded cells. The bacterial burden in animal faeces was effectively eradicated (P < 0.05) by oral administration of phage phPE42. Phage-treated rats exhibited a significant decrease in tissue damage with no signs of inflammation, necrosis, or erosion. Furthermore, phage therapy significantly (P < 0.05) reduced the expression level of the apoptotic marker caspase-3 and the inflammatory cytokine TNF-α.

SIGNIFICANCE

Treatment with phage phPE42 is considered a promising alternative therapy for the control of severe foodborne infections spurred by pathogenic XDR E. coli.

Predictive model for progressive salinization in a coastal aquifer using artificial intelligence and hydrogeochemical techniques: a case study of the Nile Delta aquifer, Egypt

To monitor groundwater salinization due to seawater intrusion (SWI) in the aquifer of the eastern Nile Delta, Egypt, we developed a predictive regression model based on an innovative approach using SWI indicators and artificial intelligence (AI) methodologies. Hydrogeological and hydrogeochemical data of the groundwater wells in three periods (1996, 2007, and 2018) were used as input data for the AI methods. All the studied indicators were enrolled in feature extraction process where the most significant inputs were determined, including the studied year, the distance from the shoreline, the aquifer type, and the hydraulic head. These inputs were used to build four basic AI models to get the optimal prediction results of the used indicators (the base exchange index (BEX), the groundwater quality index for seawater intrusion (GQI_SWI), and water quality). The machine learning models utilized in this study are logistic regression, Gaussian process regression, feedforward backpropagation neural networks (FFBPN), and deep learning-based long-short-term memory. The FFBPN model achieved higher evaluation results than other models in terms of root mean square error (RMSE) and R² values in the testing phase, with R² values of 0.9667, 0.9316, and 0.9259 for BEX, GQI_SWI, and water quality, respectively. Accordingly, the FFBPN was used to build a predictive model for electrical conductivity for the years 2020 and 2030. Reasonable results were attained despite the imbalanced nature of the dataset for different times and sample sizes. The results show that the 1000 μS/cm boundary is expected to move inland ~9.5 km (eastern part) to ~10 km (western part) to ~12.4 km (central part) between 2018 and 2030. This encroachment would be hazardous to water resources and agriculture unless action plans are taken.

A multidisciplinary approach for delineating wastewater flow paths in shallow groundwater aquifers: A case study in the southeastern part of the Nile Delta, Egypt

Groundwater pollution is a global issue in highly populated areas, the Eastern Nile Delta region is a typical example; especially around artificial wastewater drains. In the present work, a multidisciplinary approach using hydrogeochemical, geostatistical, microbiological and geophysical data was applied to determine the vulnerability conditions and to identify potential pathways through which contaminants could potentially percolate to shallow aquifers in the southern boundary of the Eastern Nile Delta. An organized groundwater sampling was conducted for hydrogeochemical investigation in rural areas along the Belbies unlined drain. This drain is known of being heavily polluted by agricultural and municipal wastewater. The hydrogeochemical analysis reveals high pollution levels by Pb, Cd, and Cr for most of the collected shallow groundwater samples nearby the drain. Additionally, NO₃^-, fecal and total coliform bacteria were observed in many samples with high concentrations. Six factors were distinguished on the basis of principal component analysis and varimax rotation, with total variance more than 78%. These factors reflected sewage contamination, lithogenic and anthropogenic effects on the shallow groundwater. Hierarchical cluster analysis revealed two main clusters of groundwater groups. Accordingly, Electrical Resistivity Tomography (ERT) was carried out in the areas of the distinguished clusters to locate potential preferential flow paths and horizons of lateral flow around the drain. The obtained resistivity models illustrate breakthrough behavior in parts of the measured profiles due to the presence of permeable paths close to the drain. The applied integrative approach is valuable for understanding the ambiguities during the interpretation process and for characterizing water quality and the aquifer vulnerability conditions. Additionally, it may guide to understand the surface water-groundwater links in order to supply the growing population with safe water.