Detection of stx1 and stx2 and subtyping of Shiga toxin-producing Escherichia coli using asymmetric PCR combined with lateral flow immunoassay

High-resolution melting real-time PCR assays for subtyping of five diarrheagenic Escherichia coli by a single well in milk

Diarrheagenic Escherichia coli (DEC) is a kind of foodborne pathogen that poses a significant threat to both food safety and human health. To address the current challenges of high prevalence and difficult subtyping of DEC, this study developed a method that combined multiplex polymerase chain reaction (PCR) with high resolution melting (HRM) analysis for subtyping 5 kinds of DEC. The target genes are amplified by multiplex PCR in a single well, and HRM curve analysis was applied for distinct amplicons based on different melting temperature (Tm) values. The method enables discrimination of different DEC types based on characteristic peaks and distinct Tm values in the thermal melting curve. The assay exhibited 100% sensitivity and 100% specificity with a detection limit of 0.5-1 ng/μL. The results showed that different DNA concentrations did not influence the subtyping results, demonstrating this method owed high reliability and stability. In addition, the method was also used for the detection and subtyping of DEC in milk. This method streamlines operational procedures, shorts the detection time, and offers a novel tool for subtyping DEC.

Nucleic acid amplification-based strategy to detect foodborne pathogens in milk: a review

Milk contaminated with trace amounts of foodborne pathogens can considerably threaten food safety and public health. Therefore, rapid and accurate detection techniques for foodborne pathogens in milk are essential. Nucleic acid amplification (NAA)-based strategies are widely used to detect foodborne pathogens in milk. This review article covers the mechanisms of the NAA-based detection of foodborne pathogens in milk, including polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), rolling circle amplification (RCA), and enzyme-free amplification, among others. Key factors affecting detection efficiency and the advantages and disadvantages of the above techniques are analyzed. Potential on-site detection tools based on NAA are outlined. We found that NAA-based strategies were effective in detecting foodborne pathogens in milk. Among them, PCR was the most reliable. LAMP showed high specificity, whereas RPA and RCA were most suitable for on-site and in-situ detection, respectively, and enzyme-free amplification was more economical. However, factors such as sample separation, nucleic acid target conversion, and signal transduction affected efficiency of NAA-based strategies. The lack of simple and effective sample separation methods to reduce the effect of milk matrices on detection efficiency was noteworthy. Further research should focus on simplifying, integrating, and miniaturizing microfluidic on-site detection platforms.

Isothermal Amplification and Lateral Flow Nucleic Acid Test for the Detection of Shiga Toxin-Producing Bacteria for Food Monitoring

Foodborne bacteria have persisted as a significant threat to public health and to the food and agriculture industry. Due to the widespread impact of these pathogens, there has been a push for the development of strategies that can rapidly detect foodborne bacteria on-site. Shiga toxin-producing E. coli strains (such as E. coli O157:H7, E. coli O121, and E. coli O26) from contaminated food have been a major concern. They carry genes stx1 and/or stx2 that produce two toxins, Shiga toxin 1 and Shiga toxin 2, which are virulent proteins. In this work, we demonstrate the development of a rapid test based on an isothermal recombinase polymerase amplification reaction for two Shiga toxin genes in a single reaction. Results of the amplification reaction are visualized simultaneously for both Shiga toxins on a single lateral flow paper strip. This strategy targets the DNA encoding Shiga toxin 1 and 2, allowing for broad detection of any Shiga toxin-producing bacterial species. From sample to answer, this method can achieve results in approximately 35 min with a detection limit of 10 CFU/mL. This strategy is sensitive and selective, detecting only Shiga toxin-producing bacteria. There was no interference observed from non-pathogenic or pathogenic non-Shiga toxin-producing bacteria. A detection limit of 10 CFU/mL for Shiga toxin-producing E. coli was also obtained in a food matrix. This strategy is advantageous as it allows for timely identification of Shiga toxin-related contamination for quick initial food contamination assessments.

A lab-on-a-tube biosensor for automatic detection of foodborne bacteria using rotated Halbach magnetic separation and Raspberry Pi imaging

A lab-on-a-tube biosensor was established to rapidly, sensitively and automatically detect foodborne bacteria through a rotatable Halbach magnet to form and rotate magnetic nanobead (MNB) chains for specific isolation of target bacteria, gold@platinum nanocatalysts (Au@PtNCs) to label target bacteria for efficient amplification of detection signal and Raspberry Pi App to collect and analyze the image of catalysate. First, the glass tube was successively preloaded with the mixture of MNBs, sample and Au@PtNCs, the washing buffer (skim milk) and the substrate (hydrogen peroxide-3,30,5,50-tetramethylbenzidine), and they were separated by air gaps. After the tube was placed on the biosensor, the MNB chains were stably formed and continuously rotated using the Halbach magnet and the mixture was moved back and forth using a programmable peristaltic pump, thus making the formation of MNB-bacteria-Au@PtNCs complexes. After the washing buffer was moved to wash the complexes, the substrate was then moved to resuspend the complexes, resulting in the catalytic reaction that changed the color of the substrate. Finally, the catalysate was moved to the designated area, the image of which was analyzed by the Raspberry Pi App to quantitatively determine the concentration of bacteria in the samples. This biosensor was able to detect Salmonella in spiked chicken samples in 1 h with lower detection limit of 8 CFU/50 μL and a recovery from 88.96% to 99.74%. This biosensor based on a single tube is very promising to automatically detect foodborne bacteria due to its low cost, high integration and simple operation.