Application of Engineered Bacteriophage T7 in the Detection of Bacteria in Food Matrices

Detection of Escherichia coli Using Bacteriophage T7 and Analysis of Excitation‑Emission Matrix Fluorescence Spectroscopy

Conventional detection methods require the isolation and enrichment of bacteria, followed by molecular, biochemical, or culture-based analysis. To address some of the limitations of conventional methods, this study develops a machine learning (ML) approach to analyze the excitation-emission matrix (EEM) fluorescence data generated based on bacteriophage T7 and Escherichia coli interactions for in-situ detection of live bacteria in the presence of fresh produce homogenate. We trained classification models using various ML algorithms based on the 3-D EEM data generated with bacteria and their interactions with a T7 phage. These ML algorithms, including linear Support Vector Classifier (SVC) and Random Forest (RF), demonstrate high accuracy (>0.85) for detecting E. coli at 102 CFU/ml concentration within 6 h. Additionally, these ML models can differentiate among different E. coli concentration levels. For example, the Gaussian Process model achieved an accuracy of 92% in detecting different concentration levels of live E. coli. Application of these ML methods to detect E. coli in spinach homogenate yielded an accuracy of 89% using the linear-SVC model. Furthermore, feature selection techniques were employed to reduce the dimensionality of the data, revealing that only six features were necessary for achieving classification accuracy (>0.85) of spinach homogenate samples containing 102 CFU/ml of E. coli. These findings highlight the potential of this novel bacterial detection methodology, offering rapid, specific, and efficient solutions for applications in food safety and environmental monitoring.

Bacteriophages: a potential game changer in food processing industry

In the food industry, despite the widespread use of interventions such as preservatives and thermal and non-thermal processing technologies to improve food safety, incidences of foodborne disease continue to happen worldwide, prompting the search for alternative strategies. Bacteriophages, commonly known as phages, have emerged as a promising alternative for controlling pathogenic bacteria in food. This review emphasizes the potential applications of phages in biological sciences, food processing, and preservation, with a particular focus on their role as biocontrol agents for improving food quality and preservation. By shedding light on recent developments and future possibilities, this review highlights the significance of phages in the food industry. Additionally, it addresses crucial aspects such as regulatory status and safety concerns surrounding the use of bacteriophages. The inclusion of up-to-date literature further underscores the relevance of phage-based strategies in reducing foodborne pathogenic bacteria's presence in both food and the production environment. As we look ahead, new phage products are likely to be targeted against emerging foodborne pathogens. This will further advance the efficacy of approaches that are based on phages in maintaining the safety and security of food.

Phage engineering for development of diagnostic tools

The bacteriophages rely on the host cell to provide energy and resources for their own replication. Antibody-based diagnostic tests rely on the antibody and the biomarker interactions. Since, most of these diagnostic tools employ the use of antibodies; hence, they require intensive storage protocols at cold conditions and incur high time and capital cost due to their production and purification process. Phage-based diagnostics can overcome this limitation. Bacteriophages, have been used as emerging tools for the detection of various pathogens. Rapid phage-mediated detection assays have become commercial diagnostic tools. Conventional method and new cloning approaches have been followed to specifically detect a disease- causing microbial strains. This review discusses use of Phage typing as diagnostic tools, phage-based detection methods, and their usage for signal amplification. Design rules for reporter phage engineering are also discussed followed by different engineering platforms for phage genome editing. We also discuss recent examples of how phage research is influencing the recent advances in the development of phage-based diagnostics for ultra-sensitive detection of various bio-species, outlining the advantages and limitations of detection technology of phage-based assays.

Bio-based antimicrobial compositions and sensing technologies to improve food safety

Microbial contamination of food products is a significant challenge that impacts food safety and quality. This review focuses on bio-based technologies for enhancing the decontamination of raw foods during postharvest processing, preventing cross-contamination, and rapidly detecting microbial risks. The bio-based antimicrobial compositions include bio-based antimicrobial delivery systems and coatings. The antimicrobial delivery systems are developed using cell-based carriers, microbubbles, and lipid-based colloidal particles. The antimicrobial coatings are engineered by incorporating biopolymers with conventional antimicrobials or cell-based antimicrobial carriers. The bio-based sensing approaches focus on replacing antibodies with more stable and cost-effective bio-receptors, including antimicrobial peptides, bacteriophages, DNAzymes, and engineered liposomes. Together, these approaches can reduce microbial contamination risks and enhance the in-situ detection of microbes.

Molecular Targets for Foodborne Pathogenic Bacteria Detection

The detection of foodborne pathogenic bacteria currently relies on their ability to grow on chemically defined liquid and solid media, which is the essence of the classical microbiological approach. Such procedures are time-consuming and the quality of the result is affected by the selectivity of the media employed. Several alternative strategies based on the detection of molecular markers have been proposed. These markers may be cell constituents, may reside on the cell envelope or may be specific metabolites. Each marker provides specific advantages and, at the same time, suffers from specific limitations. The food matrix and chemical composition, as well as the accompanying microbiota, may also severely compromise detection. The aim of the present review article is to present and critically discuss all available information regarding the molecular targets that have been employed as markers for the detection of foodborne pathogens. Their strengths and limitations, as well as the proposed alleviation strategies, are presented, with particular emphasis on their applicability in real food systems and the challenges that are yet to be effectively addressed.

Quantitative Imaging of Bacteriophage Amplification for Rapid Detection of Bacteria in Model Foods

Rapid detection of bacteria in water and food samples is a critical need. The current molecular methods like real-time PCR can provide rapid detection after initial enrichment. However, these methods require significant preparation steps, specialized facilities to reduce contamination, and relatively expensive reagents. This study evaluates a novel approach for detecting bacteria based on imaging of bacteriophage amplification upon infection of the target host bacteria to mitigate some of these constraints and improve the specificity of discriminating live vs. dead bacteria. Thus, this research leverages the natural ability of lytic bacteriophages to rapidly amplify their genetic material and generate progeny phages upon infecting the host bacterium. This study uses a nucleic acid staining dye, a conventional fluorescence microscope, and quantitative image analysis for imaging the amplification of bacteriophages. The sensitivity and assay time for imaging-based quantification of phage amplification for detecting Escherichia coli were compared with RT-PCR and the standard plaque-forming assay for detection phage amplification in model systems, including coconut water and spinach wash water. The results demonstrate that the imaging approach matches both the sensitivity and speed for detecting E. coli using the RT-PCR method without requiring isolation of nucleic acids, expensive reagents, and specialized facilities. The quantitative imaging results demonstrate the detection of 10 CFU/ml of E. coli in coconut water and simulated spinach wash water with a chemical oxygen demand (COD) of 3,000 ppm within 8 h, including initial enrichment of the bacteria. In summary, the results of this study illustrate a novel phage amplification-based approach for detecting target bacteria in complex food and water samples using simple sample preparation methods and low-cost reagents.