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. 2022 May 17:12:904531.
doi: 10.3389/fcimb.2022.904531. eCollection 2022.

An Anti-MRSA Phage From Raw Fish Rinse: Stability Evaluation and Production Optimization

Affiliations

An Anti-MRSA Phage From Raw Fish Rinse: Stability Evaluation and Production Optimization

Israa M Abd-Allah et al. Front Cell Infect Microbiol. .

Abstract

Accumulating evidence has denoted the danger of resistance in tenacious organisms like methicillin-resistant Staphylococcus aureus (MRSA). MRSA, a supple bacterium that adopts a variety of antibiotic resistance mechanisms, is the cause of multiple life-threatening conditions. Approaching a post-antibiotic era, bacteria-specific natural predators, bacteriophages, are now given the chance to prove eligible for joining the antibacterial weaponry. Considering the foregoing, this study aimed at isolating bacteriophages with promising anti-MRSA lytic activity, followed by characterization and optimization of the production of the bacteriophage with the broadest host range. Five phages were isolated from different environmental sources including the rinse of raw chicken egg, raw milk, and, remarkably, the raw meat rinses of chicken and fish. Examined for lytic activity against a set of 23 MRSA isolates collected from various clinical specimens, all five phages showed relatively broad host ranges with the bacteriophage originally isolated from raw fish rinse showing lytic activity against all the isolates tested. This phage is suggested to be a member of Siphoviridae family, order Caudovirales, as revealed by electron microscopy. It also exhibited good thermal stability and viability at different pH grades. Moreover, it showed reasonable stability against UV light and all viricidal organic solvents tested. Optimization using D-optimal design by response surface methodology was carried out to enhance the phage yield. The optimum conditions suggested by the generated model were a pH value of 7, a carbon source of 0.5% w/v sucrose, and a nitrogen source of 0.1% w/v peptone, at a temperature of 28°C and a bacterial inoculum size of 107 CFU/ml, resulting in a 2 log-fold increase in the produced bacteriophage titer. Overall, the above findings indicate the lytic ability inflicted by this virus on MRSA. Apparently, its stability under some of the extreme conditions tested implies its potential to be a candidate for pharmaceutical formulation as an anti-MRSA therapeutic tool. We hope that bacteriophages could tip the balance in favor of the human front in their battle against multidrug-resistant pathogens.

Keywords: MRSA; bacteriophage; resistance; response surface methodology; stability.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Susceptibility patterns of the collected MRSA isolates (n=23) towards some antimicrobial agents. Each result is the mean of three replicates.
Figure 2
Figure 2
Spot tests of the five harvested lysates against MRSA, showing clear spots and proving their lytic abilities.
Figure 3
Figure 3
Plaque assay results of phage F2 at different dilutions.
Figure 4
Figure 4
Plaque morphology as presented by phage F2. Plaques are clear, regularly circular, small in size (diameter of 3–5 mm), and halos are shown around the plaques.
Figure 5
Figure 5
Electron micrograph of bacteriophage F2. The head diameter is 34 nm, and the tail length is 100 nm.
Figure 6
Figure 6
Effect of different factors on the phage production titers using one-factor-at-a-time (OFAT) method, and the optimum level of each that led to maximum phage production (A, carbon source; B, nitrogen source; C, inoculum size; D, temperature). Results are the mean of the three replicates.
Figure 7
Figure 7
Three-dimensional (3D) response surface plot representing the effect of three parameters on bacteriophage production. pH and sucrose were plotted, and peptone was set at central level. The plots were obtained from Design Expert software® v. 7.0.
Figure 8
Figure 8
Model diagnostic plots for Model F2. (A) Actual vs. predicted plot, (B) Box–Cox plot, and (C) residuals versus run order plot. The plots were obtained from Design Expert software ® v. 7.0.

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