Detection Of Foodborne Pathogens Research Articles

Pathogenic Escherichia coli (E. coli) food borne outbreak: Detection methods and controlling measures

Food-borne illnesses and diseases are major threats to human health. Common food borne pathogens include bacteria such as Escherichia coli Serogroup (O157), Bacillus cereus, Clostridium botulinum, Campylobacter sp., C. perfringens, some Listeria monocytogenes, Salmonella spp., Shigella spp., Staphylococcus aureus, and Vibrio spp. etc. Pathogenic E. coli infection usually causes severe diarrhea. Escherichia coli is the most common cause of acute urinary tract infections as well as urinary tract sepsis. Diarrheagenic E. coli pathotypes can be passed in the feces of humans and other animals. Safeguarding public health during mass gatherings is a big challenge. Despite the recent advances in food preservation techniques and food safety, significant disease outbreaks linked to food borne pathogens such as bacteria, fungi, and viruses still occur worldwide indicating that these pathogens still constitute significant risks to public health. However, at present the conventional method for E. coli detection requires several days, especially in cases where E. coli concentrations are low. Enrichment is a commonly used method for bacterial isolation to increase the cell counts of target bacteria. However, traditional culturing method is also a slow and laborious process requiring a series of steps and may require the use of adjunct methods (e.g. biochemical, serological, nucleic acid-based methods for conclusive identification) and can take up to a week for bacteria. The culture-based approaches coupled with other methods such as PCR, immunoassays, bacteriophages, NGS, Biosensors, and MALDI TOF MS are increasingly being used for the detection and identification of food borne pathogens. Nucleic acid-based methods such as Real-Time PCR and vPCR combined with sequencing approaches are more widely used than immunoassay and NGS-based approaches for pathogen detection. Nanobiotechnology is the latest approach for the detection of pathogens. Bacteriophages are one such unique biological entity that showed excellent host selectivity and have been actively used as recognition probes for pathogen detection. Antibiotics are efficient, powerful, and the most commonly used treatment against pathogenic E. coli. Other ways to treat or prevent E. coli contamination, such as probiotics, antimicrobial nanoparticles, and radiation treatment had been reported.

A machine vision-assisted Argonaute-mediated fluorescence biosensor for the detection of viable Salmonella in food without convoluted DNA extraction and amplification procedures

The precise identification viable pathogens hold paramount significance in the prevention of foodborne diseases outbreaks. In this study, we integrated machine vision and learning with single microsphere to develop a phage and Clostridium butyricum Argonaute (CbAgo)-mediated fluorescence biosensor for detecting viable Salmonella typhimurium (S. typhimurium) without convoluted DNA extraction and amplification procedures. Phage and lysis buffer was utilized to capture and lyse viable S. typhimurium, respectively. Subsequently, CbAgo can cleave the bacterial DNA to obtain target DNA that guides a newly targeted cleavage of fluorescent probes. After that, the resulting fluorescent signal accumulates on the streptavidin-modified single microsphere. The overall detection process is then analyzed and interpreted by machine vision and learning algorithms, achieving highly sensitive detection of S. typhimurium with a limit of detection at 40.5 CFU/mL and a linear range of 50–107 CFU/mL. Furthermore, the proposed biosensor demonstrates standard recovery rates and coefficients of variation at 93.22% − 106.02% and 1.47% − 12.75%, respectively. This biosensor exhibits exceptional sensitivity and selectivity, presenting a promising method for the rapid and effective detection of foodborne pathogens. Environmental ImplicationBacterial pathogens exist widely in the environment and seriously threaten the safety of human life. In this study, we developed a phage and Clostridium butyricum Argonaute-mediated fluorescence biosensor for the detection of viable Salmonella typhimurium in environmental water and food samples. Compared with other Salmonella detection methods, this method does not need complex DNA extraction and amplification steps, which reduces the use of chemical reagents and experimental consumables in classic DNA extraction kit methods.

Evaluation of a novel lysis-based sample processing method to optimize Vibrio vulnificus detecting by loop-mediated isothermal amplification assay

BackgroundVibrio vulnificus exists as one of the most serious foodborne pathogens for humans, and rapid and sensitive detection methods are needed to control its infections. As an emerging method, The Loop-Mediated Isothermal Amplification (LAMP) assay has been applied to the early detection of various foodborne pathogens due to its high efficiency, but sample preprocessing still prolongs the complete detection. To optimize the detection process, our study established a novel sample preprocessing method that was more efficient compared to common methods.ResultUsing V. vulnificus as the detecting pathogen, the water-lysis-based detecting LAMP method shortened the preprocessing time to ≤ 1 min with 100% LAMP specificity; the detection limits of the LAMP assay were decreased to 1.20 × 102 CFU/mL and 1.47 × 103 CFU/g in pure culture and in oyster, respectively. Furthermore, the 100% LAMP specificity and high sensitivity of the water-lysis method were also obtained on detecting V. parahaemolyticus, V. alginolyticus, and P. mirabilis, revealing its excellent LAMP adaption with improvement in sensitivity and efficiency.ConclusionOur study provided a novel LAMP preprocessing method that was more efficient compared to common methods and possessed the practical potential for LAMP application in the future.

Novel enzyme-linked immunoassay based on nanoceria as colorimetric substrate for foodborne pathogen detection

Rapid and reliable detection of foodborne pathogens is a key requirement for food safety. Traditional rapid ELISA methods assessed by the ability of horseradish peroxidase to oxidize a chromogenic substrate such as 3, 3′, 5, 5′-tetramethylbenzidine in the presence of H2O2 may result in the high rate of negative responses because of the instability of H2O2 and product. Here, we report the use of redox active nanoceria as colorimetric indicator in immunoassay taking Staphylococcus aureus as a model. The nanoceria is fully water-soluble and can be stored as least 90 days in the refrigerator while maintaining the same performance. Moreover, it does not require external H2O2, as glucose oxidase used in the immunoassay can catalyze the oxidation of glucose to produce H2O2in situ, which is more robust in signal readout. Taken together, these results demonstrate that nanoceria are potentially suitable as colorimetric substrate in the development of novel enzyme immunoassays.

A portable CRISPR-Cas12a triggered photothermal biosensor for sensitive and visual detection of Staphylococcus aureus and Listeria monocytogenes

The detection of foodborne pathogens is crucial for ensuring the maintenance of food safety. In the present study, a portable CRISPR-Cas12a triggered photothermal biosensor integrating branch hybrid chain reaction (bHCR) and DNA metallization strategy for sensitive and visual detection of foodborne pathogens was proposed. The sheared probes were utilized to block the locker probes, which enabled preventing the assembly of bHCR in the absence of target bacteria, while target bacteria can activate the cleavage of sheared probes through CRISPR-Cas12a. Therefore, the locker probes functioned as initiating chains, triggering the formation of the branching double-stranded DNA consisting of H1, H2, and H3. The silver particles, which were in situ deposited on the DNA structure, functioned as a signal factor for conducting photothermal detection. Staphylococcus aureus and Listeria monocytogenes were selected as the foodborne pathogens to verify the analytical performance of this CRISPR-Cas12a triggered photothermal sensor platform. The sensor exhibited a sensitive detection with a low detection limit of 1 CFU/mL, while the concentration ranged from 100 to 108 CFU/mL. Furthermore, this method could efficiently detect target bacteria in multiple food samples. The findings demonstrate that this strategy can serve as a valuable reference for the development of a portable platform enabling quantitative analysis, visualization, and highly sensitive detection of foodborne bacteria.

An eco-friendly and ultrasensitive micro-orifice resistance assay for the detection of Listeria monocytogenes based on calcium carbonate signal probes harvested from discarded eggshells

The development of eco-friendly analytical methods for the detection of foodborne pathogens is of great importance for protecting human health and alleviating environmental pressure. Here, we demonstrate that a material (CaCO3 microparticles) prepared from discarded eggshells can be used as signal probes for micro-orifice resistance assay (MORA) and can be combined with ligation-mediated branching hybridization chain reaction (LB-HCR)-based signal-amplification technique (e-LMORA) for high sensitivity detection of Listeria monocytogenes. This strategy used LB-HCR-induced aggregation of streptavidin-modified CaCO3 microparticles, which were recognized by the particle counter for quantitative analysis of the target DNA. Compared with traditional MORA using polystyrene microspheres as signal probes, CaCO3 microparticles prepared from waste eggshells are more environmentally friendly. The combination of DNA-recognition probe, signal probes, and enzyme-free signal-amplification strategy not only reduces the cost synergistically, but also enables the biosensor to attain high sensitivity (limit of detection = 21 CFU/mL) due to its efficient signal amplification.

FBPP: software to design PCR primers and probes for nucleic acid base detection of foodborne pathogens

Foodborne pathogens can be found in various foods, and it is important to detect foodborne pathogens to provide a safe food supply and to prevent foodborne diseases. The nucleic acid base detection method is one of the most rapid and widely used methods in the detection of foodborne pathogens; it depends on hybridizing the target nucleic acid sequence to a synthetic oligonucleotide (probes or primers) that is complementary to the target sequence. Designing primers and probes for this method is a preliminary and critical step. However, new bioinformatics tools are needed to automate, specific and improve the design sets to be used in the nucleic acid‒base method. Thus, we developed foodborne pathogen primer probe design (FBPP), an open-source, user-friendly graphical interface Python-based application supported by the SQL database for foodborne pathogen virulence factors, for (i) designing primers/probes for detection purposes, (ii) PCR and gel electrophoresis photo simulation, and (iii) checking the specificity of primers/probes.

Enhanced sandwich immunoassay based on bivalent nanobody as an efficient immobilization approach for foodborne pathogens detection

BackgroundNanobodies (Nbs), which consist of only antigen-binding domains of heavy chain antibodies, have been used in a various range of applications due to their excellent properties. Nevertheless, the size of Nbs is so small that their antigen binding sites may be sterically hindered after random fixation as capture antibodies, thus leading to poor detection performance in immunoassays. To address this problem, we have focused on the multivalent modification of Nbs, wanted to retain the advantage of good stability through enlarging the size of Nbs to a certain extent, while improve its affinity and reduce its influence by spatial orientation. ResultsHere, we designed homo- and heterodimeric Nbs based on Nb413 and Nb422 which recognize different epitopes of Salmonella. The affinity of engineered bivalent nanobodies for S. Enteritidis were 2 orders of magnitude higher compared to monovalent Nbs and low to sub-nM KD, as calculated by Scatchard analysis. To further explore the potential of bivalent Nbs for the detection of Salmonella, we established a sandwich ELISA based on bivalent and phage-displayed Nbs (BNb-ELISA) for multiplex Salmonella determination. Compared with monovalent Nb-based ELISA, the limit of detection (LOD) of the BNb-ELISA was shown to increase 7.5-fold to 2.364 × 103 CFU mL−1 for S. Enteritidis. In addition, the feasibility of this approach for S. Enteritidis detection in real samples was evaluated, with recoveries ranging from 73.0 % to 125.6 % and coefficients of variation (CV) below 7.68 %. Significance and noveltyIn this study, we developed for the first time bivalent Nbs against Salmonella and examined their improved affinity and impact on the performance of ELISA assay. It confirmed the high binding affinity and good ability of dimeric Nbs to reduce the occupation of the binding sites of immobilized antibodies. Thus, the multivalent modification of Nbs was demonstrated to be a promising means to enhance the performance of Nbs-based immunoassays for foodborne pathogens.

Target-triggered dual signal amplification based on HCR-enhanced nanozyme activity for the sensitive visual detection of Escherichia coli.

The detection of foodborne pathogens is crucial for food hygiene regulation and disease diagnosis. Colorimetry has become one of the main analytical methods in studying foodborne pathogens due to its advantages of visualization, low cost, simple operation, and no complex instrument. However, the low sensitivity limits its applications in early identification and on-site detection for trace analytes. In order to overcome such a limitation, herein we propose a joint strategy featuring dual signal amplification based on the hybridization chain reaction (HCR) and DNA-enhanced peroxidase-like activity of gold nanoparticles (AuNPs) for the sensitive visual detection of Escherichia coli. Target bacteria bound specifically to the aptamer domain in the capture hairpin probe, exposing the trigger domain for HCR and forming the extended double-stranded DNA (dsDNA) structures. The peroxidase-like catalytic capacity of AuNPs can be enhanced significantly by dsDNAs with the sticky ends of dsDNAs being adsorbed on AuNPs and the rigidity of dsDNAs causing the spatial regulation of AuNP concentration. The intensity of the enhancement was linearly related to the number of target bacteria. With the above strategy, the detection limit of our colorimetric method for Escherichia coli was down to 28 CFU mL-1 within a short analytical time (50 min). This study provides a new perspective for the sensitive and visual detection of early bacterial contamination in foods.

CRISPR/Cas-based colorimetric biosensors: a promising tool for the diagnosis of bacterial foodborne pathogens in food products.

Some physical phenomena and various chemical substances newly introduced in nanotechnology have allowed scientists to develop valuable devices in the field of food sciences. Regarding such progress, the identification of foodborne pathogenic microorganisms is an imperative subject nowadays. These bacterial species have been found to cause severe health impacts after food ingestion and can result in high mortality in acute cases. The rapid detection of foodborne bacterial species at low concentrations is in high demand in recent diagnostics. CRISPR/Cas-mediated biosensors possess the potential to overcome several challenges in classical assays such as complex pretreatments, long turnaround time, and insensitivity. Among them, colorimetric nanoprobes based on the CRISPR strategy afford promising devices for POCT (point-of-care testing) since they can be visualized with the naked eye and do not require diagnostic apparatus. In this study, we briefly classify and discuss the working principles of the different CRISPR/Cas protein agents that have been employed in biosensors so far. We assess the current status of the CRISPR system, specifically focusing on colorimetric biosensing platforms. We discuss the utilization of each Cas effector in the detection of foodborne pathogens and examine the restrictions of the existing technology. The challenges and future opportunities are also indicated and addressed.

A sequential liquid dispensing method in a centrifugal microfluidic device operating at a constant rotational speed for the multiplexed genetic detection of foodborne pathogens.

This study proposes a sequential liquid dispensing method using a centrifugal microfluidic device operating at a constant rotational speed for the multiplexed genetic detection of nucleic acid targets across multiple samples in a single operation. A pair of passive valves integrated into each microchamber enabled the liquid to fill towards the center of rotation against the centrifugal force, facilitating the complete removal of air inside the microchamber. Liquid manipulation can be achievable without any surface coating of the device by exploiting the inherent hydrophobicity of the polymer. Furthermore, design guidelines for the optimization of microfluidic devices are clarified. Consequently, our proposed method allows direct liquid dispensing into the reaction chambers without cross-contamination while simultaneously metering the sample/reagent volume for the colorimetric loop-mediated isothermal amplification (LAMP) reaction. In addition, we demonstrated the simultaneous detection of four foodborne pathogens (Salmonella spp., Vibrio parahaemolyticus, Campylobacter spp., and norovirus genogroup II (GII)) across four samples in a centrifugal microfluidic device within 60 min. Furthermore, the device exhibited high quantitation (R 2 > 0.98) of the DNA concentration in the sample. Our proposed method enables a more compact design by eliminating the need for metering chambers and offers a point-of-care testing platform with high simplicity as it operates at a constant rotational speed.

Boron nitride nanoplate-based strand exchange amplification with enhanced sensitivity and rapidity for quantitative detection of Staphylococcus aureus in food samples.

Staphylococcus aureus is one of the most common foodborne pathogens that can cause serious food poisoning and infectious diseases in humans. Standard identification approaches include nucleic acid amplification, but current amplification tools suffer from low amplification efficiency, resulting in the risk of low sensitivity and long detection time. Herein, boron nitride nanoplates (BNNPs) were chosen as an additive for enhancing the sensitivity and rapidity of strand exchange amplification (SEA), thereby successfully expanding the application of nucleic acid detection for detecting Staphylococcus aureus in food samples. As a result, SEA based on boron nitride nanoplates (BNNP-SEA) was employed for sensitive and rapid detection of foodborne pathogen Staphylococcus aureus. Compared with classical SEA, the BNNP-based SEA assay was more than 10-fold sensitive, and the detection time was reduced by 15 minutes. The optimized BNNP-based SEA shows a wide linear range from 40 pg to 50 ng in a diluted solution of the target DNA with a low detection limit of 40 pg. Moreover, the BNNP-based SEA achieves the quantitative detection of Staphylococcus aureus in different food samples (pork, beef, mutton, duck, milk and shrimp). In contrast to the classical SEA, the BNNP-based SEA method enabled sensitive and rapid detection of Staphylococcus aureus in the above food samples at concentrations as low as 5 × 103 CFU mL-1. The BNNP-based SEA assay is specific, sensitive and reliable, offering a valuable diagnostic technology for routine analysis in food safety research.

Machine learning-enabled colorimetric sensors for foodborne pathogen detection.

In the past decade, there have been various advancements to colorimetric sensors to improve their potential applications in food and agriculture. One application of growing interest is sensing foodborne pathogens. There are unique considerations for sensing in the food industry, including food sample destruction, specificity amidst a complex food matrix, and high sensitivity requirements. Incorporating novel technology, such as nanotechnology, microfluidics, and smartphone app development, into colorimetric sensing methodology can enhance sensor performance. Nonetheless, there remain challenges to integrating sensors with existing food safety infrastructure. Recently, increasingly advanced machine learning techniques have been employed to facilitate nondestructive, multiplex detection for feasible assimilation of sensors into the food industry. With its ability to analyze and make predictions from highly complex data, machine learning holds potential for advanced yet practical colorimetric sensing of foodborne pathogens. This article summarizes recent developments and hurdles of machine learning-enabled colorimetric foodborne pathogen sensing. These advancements underscore the potential of interdisciplinary, cutting-edge technology in providing safer and more efficient food systems.

Automated centrifugal microfluidic system for the preparation of adaptor-ligated sequencing libraries.

The intensive workload associated with the preparation of high-quality DNA libraries remains a key obstacle toward widespread deployment of sequencing technologies in remote and resource-limited areas. We describe the development of single-use microfluidic devices driven by an advanced pneumatic centrifugal microfluidic platform, the PowerBlade, to automate the preparation of Illumina-compatible libraries based on adaptor ligation methodology. The developed on-chip workflow includes enzymatic DNA fragmentation coupled to end-repair, adaptor ligation, first DNA cleanup, PCR amplification, and second DNA cleanup. This complex workflow was successfully integrated into simple thermoplastic microfluidic devices that are amenable to mass production with injection molding. The system was validated by preparing, on chip, libraries from a mixture of genomic DNA extracted from three common foodborne pathogens (Listeria monocytogenes, Escherichia coli and Salmonella enterica serovar Typhimurium) and comparing them with libraries made via a manual procedure. The two types of libraries were found to exhibit similar quality control metrics (including genome coverage, assembly, and relative abundances) and led to nearly uniform coverage independent of GC content. This microfluidic technology offers a time-saving and cost-effective alternative to manual procedures and robotic-based automation, making it suitable for deployment in remote environments where technical expertise and resources might be scarce. Specifically, it facilitates field practices that involve mid- to low-throughput sequencing, such as tasks related to foodborne pathogen detection, characterization, and microbial profiling.

Resilient sustainable current and emerging technologies for foodborne pathogen detection.

Foodborne pathogens such as Salmonella, Escherichia coli and Listeria pose significant risks to human health. The World Health Organization estimates that 2.2 million deaths per year are directly caused by foodborne and waterborne bacterial diseases worldwide. Accordingly, detecting pathogens in food is essential to ensure that our food is safe. This review explores the critical role of novel technologies in enhancing food safety practices whilst delving into adopting and integrating innovative, resilient and sustainable approaches in the food supply chain. Further, applying novel, emerging advanced analytical techniques such as Raman spectroscopy and nanotechnology based biosensors in food contamination detection is discussed. These advanced technologies show the promise of real-time monitoring, traceability, and predictive analytics to identify and mitigate potential hazards before they reach consumers. They can provide rapid and accurate results and ensure the integrity of food products. Furthermore, the herein-highlighted synergistic integration of these technologies offers a promising path toward a safer and more transparent food system, thereby addressing the challenges of today's globalised food market and laying the platform for developing multimodal technologies for affordable, sensitive and rapid pathogen detection along the different stages of the food chain, from "farm to fork".

Isothermal amplification-based microfluidic devices for detecting foodborne pathogens: a review.

The gold standard for nucleic acid amplification-based diagnosis is the polymerase chain reaction (PCR). The PCR recognizes the targets such as foodborne pathogens by amplifying their specific genes. The integration of nucleic acid amplification-based assays on microfluidic platforms represents a highly promising solution for convenient, cheap, and effective control of foodborne pathogens. However, the application of the PCR is limited to on-site detection because the method requires sophisticated equipment for temperature control, which makes it complicated for microfluidic integration. Alternatively, isothermal amplification methods are promising tools for integrating microfluidic platforms for on-site detection of foodborne pathogens. This review summarized advances in isothermal amplification-based microfluidic devices for detecting foodborne pathogens. Different nucleic acid extraction approaches and the integration of these approaches in microfluidic platforms were first reviewed. Microfluidic platforms integrated with three common isothermal amplification methods including loop-mediated isothermal amplification, recombinase polymerase amplification, and recombinase-aided amplification were then described and discussed.

Rapid detection of Salmonella in milk by labeling-free electrochemical immunosensor based on an Fe3O4–ionic liquid-modified electrode

Electrochemical sensors show distinct advantages over other types of sensors in the rapid detection of microorganisms. Here, we attempted to construct a label-free electrochemical immunosensor based on an Fe3O4–ionic liquid (IL)-modified electrode to rapidly detect Salmonella in milk. The excellent ionic conductivity of the IL facilitated sensor construction, and the large surface area of nano-Fe3O4 provided numerous sites for subsequent experiments. An antibody was fixed on the Fe3O4–IL complex with polyglutamic acid modification by a simple infusion method. The microstructure of the Fe3O4–IL composites was investigated by scanning electron microscopy, and the elements and structures of the composites were analyzed by energy dispersive X-ray and Fourier transform infrared spectroscopy. Under optimized experimental conditions, the detection range of the constructed sensor was 3.65 × 102–3.65 × 108 CFU mL−1, and the LOD was 1.12 × 102 CFU mL−1 (S/N = 3). In addition, the prepared electrochemical immunosensor is convenient for detecting foodborne pathogens because of its outstanding stability, good selectivity, and repeatability.

Evaluation of Long-Read Sequencing Simulators to Assess Real-World Applications for Food Safety.

Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes are routinely responsible for severe foodborne illnesses in the United States. Current identification methods utilized by the U.S. Food Safety Inspection Service require at least four days to identify STEC and six days for L. monocytogenes. Adoption of long-read, whole genome sequencing for food safety testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, L. monocytogenes, and a 1:1 combination of STEC and Bos taurus genomes using NanoSim-H. At least 2500 simulated reads were needed to identify the seven genes of interest targeted in STEC, and at least 500 reads were needed to detect the gene targeted in L. monocytogenes. Genome coverage of 30x was estimated at 21,521, and 11,802 reads for STEC and L. monocytogenes, respectively. Approximately 5-6% of reads simulated from both bacteria did not align with their respective reference genomes due to the introduction of errors. For the STEC and B. taurus 1:1 genome mixture, all genes of interest were detected with 1,000,000 reads, but less than 1x coverage was obtained. The results suggested sample enrichment would be necessary to detect foodborne pathogens with long-read sequencing, but this would still decrease the time needed from current methods. Additionally, simulation data will be useful for reducing the time and expense associated with laboratory experimentation.

SERS detection of foodborne pathogens in beverage with Au nanostars.

The aim of this study is to develop a simple but rapid method for the determination of foodborne pathogens in complex matrices (beverages) by surface enhanced Raman spectroscopy (SERS) combined with Au nanostar solid-phase substrates. The star-shaped singlet Au nanostructure was formed on the surface of astainless steel sheetby chemical replacement reaction. Rhodamine 6G verified the sensitivity and reproducibility of this substrate, and the relative standard deviations of the SERS intensity at 1312 cm-1, 1364 cm-1, and 1510 cm-1 displacements were 3.40%, 5.64%, and 3.48%, respectively. By detecting four pathogens in beverage samples on Au nanostar substrates, the utility of the SERS assay was demonstrated, while the combination of principal component analysis (PCA) and hierarchical cluster analysis (HCA) further enabled the isolation and identification of pathogens. The results of spiked beverages were validated in conventional culture identification and Vitek 2 Compact biochemical identification system experiments. Thus, this research demonstrated that Au nanostar substrates can be effectively utilized for the recognition of pathogenic bacteria and have immense promise to advance the progress of quick detection of foodborne pathogens and food safety.

Specific separation and sensitive detection of foodborne pathogens by phage-derived bacterial-binding protein-nano magnetic beads coupled with smartphone-assisted paper sensor

Foodborne pathogen infection poses a significant threat to public health and is considered as one of the most serious hazards in global food safety. Herein, a sensitive and efficient method for on-site monitoring of foodborne pathogens was developed by using a smartphone-assisted paper-sensor combined with phage-derived bacterial-binding proteins-nano magnetic beads (PBPs-MBs). PBPs including tail fiber protein (TFP:gp13), cell-wall binding domain (CBD) of endolysin and tailspike protein (TSP) coated on the surface of MBs were applied for rapid separation and enrichment of targeted bacteria (Escherichia coli O157:H7, Staphylococcus aureus and Salmonella typhimurium, respectively) from food samples in 20 min before detection on paper-based sensors. The paper-based sensor was loaded with the lytic agent (polymyxin B) to induce bacterial lysis and release specific endogenous enzymes. Subsequently, three distinct chromogenic substrates were hydrolyzed by their corresponding enzymes, resulting in characteristic color changes on the paper, respectively. In addition, a smartphone APP for red-green-blue (RGB) color analysis of paper was able to directly detect three foodborne pathogens. As a result, the limit of detection (LOD) values for three foodborne pathogens were found to be 2.44 × 102, 2.68 × 104 and 4.62 × 103 CFU/mL, respectively, which were much lower than other studies (106–108 CFU/mL) based on enzymes. Moreover, the feasibility of this approach was further assessed through the successful detection of targeted bacteria in real samples with satisfactory recovery rates. In conclusion, this smartphone-assisted biosensor offers promising application potential for point-of-care testing (POCT) of foodborne pathogens in resource-scarce areas.