Rapid Detection Of Foodborne Pathogens Research Articles

Development of modified enrichment broth for short enrichment and recovery of filter-injured Salmonella Typhimurium

The filter concentration method facilitates the rapid detection of foodborne pathogens. The filter concentration method lowered the limit of detection (LOD) of artificially inoculated cabbage with Salmonella Typhimurium; however, the procedure injured foodborne pathogens during filtering procedure. Thus, to detect injured pathogens under the detection limit, an enrichment broth promoting pathogen resuscitation and growth is required. To rapidly recover, cultivate and lower the time to result (TTR) of S. Typhimurium detection after filter concentration method, a brain heart infusion (BHI) broth-based modified enrichment broth (MEB) was developed. The MEB was developed by fitting growth curves to a modified Gompertz model; 1.00 g/L of sodium pyruvate, 0.20 g/L proline and 2.0 g/L magnesium sulphate additives were optimized as additional components to rapidly grow filter-injured S. Typhimurium. As a result, the rate of filter-injured S. Typhimurium went from 100% to 0.0% using MEB within 3.5 h. In contrast, BHI required 4 h and buffered peptone water (BPW) required more than 4 h to decrease the injury rate to 0.0%. Using MEB, BHI and BPW, filter-injured S. Typhimurium in cabbages were enriched to 4.056 ± 0.026 Log CFU/25 g, 3.571 ± 0.187 Log CFU/25 g and 3.708 ± 0.156 Log CFU/25 g, respectively. Additionally, 1–9 CFU/mL S. Typhimurium in cabbage was detected within 3.0 h, including 1 h enrichment with MEB, whereas 5.0 h was required for BHI and BPW. Thus, the MEB developed in this study showed great potential as a short enrichment broth for the rapid detection of filter-injured S. Typhimurium.

A label-free electrochemical immunosensor for rapid detection of salmonella in milk by using CoFe-MOFs-graphene modified electrode

The presence of Salmonella in food has been a serious threat to human health all over the world. Herein, a novel electrochemical immunosensor based on CoFe-MOFs-graphene nanocomposite was constructed to detect Salmonella in milk. The synergy of the large specific surface area and high porosity of CoFe-MOFs and the good electrical conductivity of graphene materials greatly enhanced the current signal of the nanocomposite. Gold nanoparticles were modified on CoFe-MOFs-graphene hybrids by a simple electrodeposition method. Anti-Salmonella antibody was immobilized onto the surface of the constructed electrode through the formation of a stable Au–NH2 bond. Scanning electron microscopy was employed to reveal the structure of the CoFe-MOFs-graphene nanocomposite, and the elements of the nanocomposite were observed by energy-dispersive X-ray spectroscopy. In addition, Fourier transform infrared (FT-IR) and X-ray powder diffraction (XRD) were used to analyze the structure of related materials. Under optimal experimental parameters, the constructed immunosensor detected a wide linear range of Salmonella from 2.4 × 102 CFU mL−1 to 2.4 × 108 CFU mL−1 with a detection limit of 1.2 × 102 CFU mL−1 (S/N = 3). The immunosensor showed good stability, selectivity, and reproducibility. The designed immunosensor provides a new strategy for the rapid detection of foodborne pathogens.

Emerging Role of Biosensors for Detection of Foodborne Pathogens

Numerous techniques are employed for the detection of various types of pathogens in different foods. Rapid detection of foodborne pathogens is very important by using biosensors. The objectives of this review are to highlight the application of the biosensors in detecting foodborne pathogens, future trends of biosensors technology in foodborne pathogens detection, and limitations of biosensors in the food industry. Biosensors are analytical devices and one of the rapid detection methods that can combat certain limitations of conventional detection techniques, such as portability, time, cost, sensitivity, and others. Biosensors have many applications in different fields. Biosensors in the food industry are used for the detection and identification of foodborne pathogens. The uses of biosensors in food are increasing from day to day due to different factors. In the future, the latest generations, which are autonomous and nanomaterial-based biosensors will emerge. There is also a need to develop a biosensor that is easy to use and has a short detection time.

Advancements in methods to detect and culture medically important anaerobic bacteria

Anaerobic bacteria are one of the most important bacteria, involved in a number of diseases and infections. These are also involved in food borne illness. Due to their fastidious nature, culturing anaerobic bacteria is a bit difficult task. Moreover, anaerobic bacteria can take several days and weeks to grow in laboratories. Apart from this, most bacteria just cannot be cultured in laboratories using standard (anaerobic) cultivation techniques known so far. Difficulties in microbiological detection result in delayed diagnosis of the diseases. Many patients suffer due to these facts, as rapid identification is not only difficult, but in many cases, is almost impossible. Thus, there is a need to develop novel techniques for the cultivation and identification of clinically important anaerobes. Rapid detection of foodborne pathogens is necessary for the prevention of foodborne disease and for the safe supply of food. Present article reviews and discusses advance techniques, both culture-dependent and culture-independent, that allow rapid detection of such important anaerobic bacteria. Advancements in culturing techniques has reduced the time to grow the anaerobic bacteria in laboratories. Whereas advancements in molecular techniques have enabled the rapid detection of medically important anaerobes including Clostridium, Bacteroides, and many others.

A newly developed paper embedded microchip based on LAMP for rapid multiple detections of foodborne pathogens

BackgroundMicrofluidic chip detection technology is considered a potent tool for many bioanalytic applications. Rapid detection of foodborne pathogens in the early stages is imperative to prevent the outbreak of foodborne diseases, known as a severe threat to human health. Conventional bacterial culture methods for detecting foodborne pathogens are time-consuming, laborious, and lacking in pathogen diagnosis. To overcome this problem, we have created an embedded paper-based microchip based on isothermal loop amplification (LAMP), which can rapidly and sensitively detect foodborne pathogens.ResultsWe embed paper impregnated with LAMP reagent and specific primers in multiple reaction chambers of the microchip. The solution containing the target pathogen was injected into the center chamber and uniformly distributed into the reaction chamber by centrifugal force. The purified DNA of Escherichia coli O157:H7, Salmonella spp., Staphylococcus aureus, and Vibrio parahaemolyticus has been successfully amplified and directly detected on the microchip. The E. coli O157:H7 DNA was identified as low as 0.0134 ng μL− 1. Besides, the potential of this microchip in point-of-care testing was further tested by combining the on-chip sample purification module and using milk spiked with Salmonella spp.. The pyrolyzed milk sample was filtered through a polydopamine-coated paper embedded in the inside of the sample chamber. It was transported to the reaction chamber by centrifugal force for LAMP amplification. Then direct chip detection was performed in the reaction chamber embedded with calcein-soaked paper. The detection limit of Salmonella spp. in the sample measured by the microchip was approximately 12 CFU mL− 1.ConclusionThe paper embedded LAMP microchip offers inexpensive, user-friendly, and highly selective pathogen detection capabilities. It is expected to have great potential as a quick, efficient, and cost-effective solution for future foodborne pathogen detection.

Characterization of chicken meat contaminated with Salmonella by fluorescence spectroscopy

Contaminated poultry products as eggs and meat are the primary vehicles of Salmonella infection. Conventional methods for microorganisms detections involve multiple steps, and despite its accuracy, these assays are time‐consuming. Biosensing methods have shown great potential for the rapid detection of foodborne pathogens. Some of the biosensors are based on fluorescence. Various fluorophores such as collagen, elastin, NAD(P)H, and porphyrins can be used to evaluate possible chemical changes in meat. In this manuscript, the fluorescence properties of chicken meat contaminated with Salmonella enterica (ATCC 14028) cell suspensions (500; 5000; 50,000 and 500,000 cells/mL) were obtained and compared with non-contaminated control, for meat kept at 25 °C for 24 and 48 h. The effects of ambient light were also considered. Our results indicated that free NAD(P)H and coproporphyrin emission bands present in contaminated meat, increased over time, and can provide access to valuable information for the detection of Salmonella in chicken meat.

Ultrafast bacterial cell lysis using a handheld corona treater and loop-mediated isothermal amplification for rapid detection of foodborne pathogens

Bacterial foodborne diseases have become a growing global health concern, and nucleic acid-based analysis is considered as a promising approach for rapid identification of foodborne pathogens. Accordingly, nucleic acid isolation becomes the prerequisite first step for subsequent bioanalysis. However, current nucleic acid extraction suffers from operation time delayed, amplification inhibited by chemicals, or bulky instruments required. Here, we presented an ultrafast bacterial cell lysis induced by corona discharge within 40 s and combined it with loop-mediated isothermal amplification (LAMP) for the first time to achieve rapid and convenient detection of foodborne pathogens. Firstly, the viability and morphological changes revealed that corona discharge could destabilize bacterial cell envelope and eliminate more than 90% of Salmonella enterica (S. enterica) or Staphylococcus aureus (S. aureus) within 40 s. More surprisingly, more DNA were released from 100-103 CFU of electrical lysed S. enterica than equivalent thermal lysed ones, manifesting advantages of corona discharge on shorter preparation time and greater yields of DNA. Furthermore, the advantages of this ultrafast bacterial cell lysis were leveraged when collaborating with colorimetric LAMP. After conducting colorimetric LAMP in a water bath at 63 °C for 1 h, we could visually detect released DNA from 100 CFU of electrical lysed S. enterica and 103 CFU of electrical lysed S. aureus, respectively. Finally, we validated the applicability of the electrical lysis combined with LAMP reaction to detect (viable) S. enterica and S. aureus in artificially spiked pork samples. Therefore, we provided a rapid and convenient bioanalysis platform integrating an ultrafast electrical lysis and LAMP detection, opening up its extensive applications for versatile pathogens in resource-limited settings.

Gold interdigitated micro-immunosensor based on Mn-MOF-74 for the detection of Listeria monocytogens

Accurate and rapid detection of foodborne pathogens is a key to prevent foodborne disease outbreaks. In this study, a novel impedance immunosensor based on a metal-organic framework (Mn-MOF-74) is used to rapidly and sensitively detect Listeria monocytogenes (L. m) in milk. Divalent manganese ions are released by the MOF reduction reaction mediated by hydrogen peroxide. Consequently, the impedance signal was detected by high conductive single-crystalline gold interdigitated microelectrode to achieve quantification of L. m. First, the capture antibodies (Ab1) are modified on the surface of the magnetic beads to generate immunomagnetic beads (MBs@Ab1), which are used specifically to separate L. m cells in the matrices. Later, the immunosensor (Mn-MOF-74@Ab2) is added to the matrices to form a sandwich complex (MBs@Ab1-L. m-Mn-MOF-74@Ab2). Henceforward, Mn2+ is released from the sandwich composite via the action triggered by H2O2. The release of Mn2+ significantly changes the impedance of interdigitated microelectrodes, leading to ultrasensitive detection of L. m. The recoveries for L. m cells at the concentration between 1.0 × 100 and 1.0 × 104 CFU/mL are 90.2%–101.7% in water and 88.5%–96.2% in milk. The detection limit of this approach for L. m cells in water and milk are 7.1 and 9.2 CFU/mL, respectively. This approach can achieve rapid quantification of L. m cells within 60 min, and can also be employed to monitor other foodborne pathogens.

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level

Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure food safety and prevent public health problems. Raman spectroscopy, a label-free, highly sensitive and dependable technology has attracted more and more attention in the field of diagnosing food-borne pathogens in recent years. In the research, 15,890 single-cell Raman spectra of 23 common strains from 7 genera were obtained at the single cell level. Then, the nonlinear features of raw data were extracted by kernel principal component analysis, and the individual bacterial cell was evaluated and discriminated at the serotype level through the decision tree algorithm. The results demonstrated that the average correct rate of prediction on independent test set was 86.23 ± 0.92% when all strains were recognized by only one model, but there were high misjudgment rates for certain strains. Therefore, the four-level classification models were introduced, and the different hierarchies of the identification models achieved accuracies in the range of 87.1%–95.8%, which realized the efficient prediction of strains at the serotype level. In summary, Raman spectroscopy combined with machine learning based on fingerprint difference was a prospective strategy for the rapid diagnosis of pathogenic bacteria.

Specific detection of Cronobacter sakazakii in powdered infant formula using ssDNA aptamer.

Cronobacter sakazakii (C. sakazakii) is a foodborne pathogen associated with bacterial meningitis, sepsis, and necrotizing enterocolitis in premature and immuno-compromised infants. C. sakazakii is typically acquired by ingesting contaminated powdered infant formula (PIF). The growing demand for a safe food supply requires rapid detection of foodborne pathogens for delivering safe-to-consume food to consumers. In the present study, we isolated C. sakazakii-specific aptamers using a centrifugation-based partitioning method (CBPM) instead of systematic evolution of ligands by exponential enrichment (SELEX) process. Unlike SELEX, the CBPM reduces the evolution-loop time to obtain enriched probes, allowing the isolation of target-specific aptamers in a shorter time. The two aptamers (SC25 and SC45) isolated using the CBPM showed high affinity and specificity for C. sakazakii (Kd: 34 and 66 nM). Among the two aptamers, SC25 aptamer detected efficiently C. sakazakii in PIF with less cross-reactivity. Our results indicate that the isolated aptamers could be used for detecting C. sakazakii in PIF and reducing the overall testing time compared with the conventional C. sakazakii detection method.

"One-step" characterization platform for pathogenic genetics of Staphylococcus aureus.

Staphylococcus aureus (S. aureus) is an important human pathogen causing a variety of life-threatening diseases. In recent years, the health problem caused by S. aureus contaminated food has become a global health problem. S. aureus can express various pathogenic factors, mainly used for adhesion, colonization, invasion and infection of the host. Therefore, rapid and accurate detection of virulence genes in S. aureus is necessary to prevent outbreaks caused by this pathogen. PCR is a useful tool for rapid detection of foodborne pathogens. The objective of this study was to detect the presence of major toxin genes in S. aureus, including sea, seb, sec, see, pvl and tsst, by using a PCR plate. Of the 13 strains tested, 12 (92.3%) were found to be positive for one or more toxin genes. This study realized the one-step detection of main toxin factors in S. aureus.

AquaSparkTM - Rapid Environmental Monitoring of Listeria monocytogenes.

In order to prevent microbial contamination of food, monitoring of the production environment, together with the rapid detection of foodborne pathogens have proven to be of utmost importance for Food Safety. Environmental monitoring should detect harmful pathogens at the earliest point in time in order for the necessary interventions to be taken. However, current detection methods fall short with regards to speed, ease of use, and cost. This article aims to present the idea behind NEMIS Technologies, a startup company making use of the novel AquaSparkTM technology for the development of a new generation of bacterial detection methods. These methods utilize chemiluminescence in order to detect live target bacteria in a short period of time compared to that of conventional methods. We show that dry-stressed Listeria monocytogenes can be detected within 24 hours, using small-molecule chemiluminescent probes, together with a bacteria-specific proprietary enrichment broth containing a cocktail of bacteriophages, which enhance the specificity and sensitivity. This novel platform technology has the potential to extend beyond environmental monitoring towards food analyses as well as veterinary and human health.

Microbial detection and identification methods: Bench top assays to omics approaches.

Rapid detection of foodborne pathogens, spoilage microbes, and other biological contaminants in complex food matrices is essential to maintain food quality and ensure consumer safety. Traditional methods involve culturing microbes using a range of nonselective and selective enrichment methods, followed by biochemical confirmation among others. The time-to-detection is a key limitation when testing foods, particularly those with short shelf lives, such as fresh meat, fish, dairy products, and vegetables. Some recent detection methods developed include the use of spectroscopic techniques, such as matrix-assisted laser desorption ionization-time of flight along with hyperspectral imaging protocols.This review presents a comprehensive overview comparing insights into the principles, characteristics, and applications of newer and emerging techniques methods applied to the detection and identification of microbes in food matrices, to more traditional benchtop approaches. The content has been developed to provide specialist scientists a broad view of bacterial identification methods available in terms of their benefits and limitations, which may be useful in the development of future experimental design. The case is also made for incorporating some of these emerging methods into the mainstream, for example, underutilized potential of spectroscopic techniques and hyperspectral imaging.

Integrated silica membrane-based nucleic acid purification, amplification, and visualization platform for low-cost, rapid detection of foodborne pathogens.

Real-time fluorescence detection of nucleic acid exhibit excellent performance in analytical and diagnostic applications. However, the requirement of laboratory-based instrument and complex nucleic acid extraction greatly limits their application in point-of-care testing (POCT). Herein, a novel integrated silica membrane-based platform incorporating nucleic acid purification, amplification, and detection steps was developed. A universal and portable visualization platform was fabricated by incorporating denaturation bubble-mediated strand exchange amplification (SEA) reaction with silica membrane. The fluorescence signal of SYBR Green I with amplification products was visualized by the naked eye using a simple ultraviolet light on the silica membrane, and significant discrimination between the positive and negative samples could be easily and visually obtained. Besides, chitooligosaccharide-modified silica membrane allows the purification of nucleic acid in a totally aqueous system and enables in situ SEA. With the proposed integrated platform, 102-108cfu/mL Vibrio parahaemolyticus could be successfully detected and excellent performance was also revealed for gram-positive pathogens. The detection limit of the method for artificially spiked oysters was 103cfu/g and reached 100cfu/g after 12h enrichment. This proof-of-concept method could also be applied to a variety of nucleic acid amplification methods. We believe that the proposed silica membrane-based platform has great potential for the rapid and low-cost detection of nucleic acids especially in low-resource settings. Graphical abstract.

Recent Advances in Peptide Nucleic Acids for Rapid Detection of Foodborne Pathogens

Peptide nucleic acids (PNAs) are DNA/RNA analogs in which sugar-phosphate backbone is replaced by N-2-aminoethylglycine repeating units. Since PNA contains a neutral skeleton, there is no electrostatic repulsion, resulting in significant stability of its hybrid structure with complementary oligonucleotides. At present, PNA has taken the place of DNA probe in many studies. There are several disadvantages of cellular uptake of PNA, so modifications in PNA backbone or covalent coupling with cell-penetrating peptides are necessary to improve its delivery inside the cells. In recent years, PNA has been extensively used in the rapid detection of microorganisms, such as fluorescence in situ hybridization, PCR amplification, biosensor, and gene chip. The structure and characteristics of PNA probe, the hybridization method, and the design principle of PNA probes are introduced in this review, and the application progress of PNA probes in the rapid detection of foodborne pathogens is summarized. On this basis, the advantages and disadvantages of PNA probes are analyzed, and the future development trend is prospected.

Application of Biosensors for Detection of Pathogenic Food Bacteria: A Review.

The use of biosensors is considered a novel approach for the rapid detection of foodborne pathogens in food products. Biosensors, which can convert biological, chemical, or biochemical signals into measurable electrical signals, are systems containing a biological detection material combined with a chemical or physical transducer. The objective of this review was to present the effectiveness of various forms of sensing technologies for the detection of foodborne pathogens in food products, as well as the criteria for industrial use of this technology. In this article, the principle components and requirements for an ideal biosensor, types, and their applications in the food industry are summarized. This review also focuses in detail on the application of the most widely used biosensor types in food safety.

Rapid Classification of Single Bacterium Based on Backscattering Microscopic Spectrum—A Pilot Study

Rapid detection of foodborne pathogens is one of the most effective ways to solve food safety problems. To achieve rapid and noninvasive detection and classification of foodborne pathogens, we modified a fiber confocal backscattering micro-spectral system to suit an extremely small biological sample, that is, a bacterium. This system offers single-bacterium level, label-free, convenient, and environmentally friendly characterization. Three categories of common foodborne pathogens (Salmonella typhimurium, Escherichia coli, and Staphylococcus aureus) were measured. The scattering spectrum ranging from 450 to 900 nm was selected, and by the model of principal component analysis (PCA) and error back propagation algorithm of back propagation neural network (BPNN), the backscattering microscopic spectra of three categories of pathogens were dimensionality reduced, identified and classified. The results showed that the identification accuracy of three categories of pathogens was above 90%, under neutral, acidic and alkaline culturing conditions，respectively. The preliminary results demonstrated the feasibility of using confocal backscattering microscopic spectra combined with PCA and BPNN algorithm to identify and classify single bacterium in a rapid, noninvasive, and label-free manner.

Single-cell classification of foodborne pathogens using hyperspectral microscope imaging coupled with deep learning frameworks

A high-throughput hyperspectral microscope imaging (HMI) technology with hybrid deep learning (DL) framework defined as “Fusion-Net” was proposed for rapid classification of foodborne bacteria at single-cell level. HMI technology is useful in single-cell characterization, providing spatial, spectral and combined spatial-spectral profiles with high resolution. However, direct analysis of these high-dimensional HMI data is challenging. In this work, HMI data were decomposed into three parts as morphological features, intensity images, and spectral profiles. Multiple advanced DL frameworks including long-short term memory (LSTM) network, deep residual network (ResNet), and one-dimensional convolutional neural network (1D-CNN) were utilized, achieving classification accuracies of 92.2 %, 93.8 %, and 96.2 %, respectively. Taking advantage of fusion strategy, individual DL framework was stacked to form “Fusion-Net” that processed these features simultaneously with improved classification accuracy of up to 98.4 %. Our study demonstrated the ability of DL frameworks to assist HMI technology in single-cell classification as a diagnostic tool for rapid detection of foodborne pathogens.

An in situ-Synthesized Gene Chip for the Detection of Food-Borne Pathogens on Fresh-Cut Cantaloupe and Lettuce.

Fresh foods are vulnerable to foodborne pathogens which cause foodborne illness and endanger people’s life and safety. The rapid detection of foodborne pathogens is crucial for food safety surveillance. An in situ-synthesized gene chip for the detection of foodborne pathogens on fresh-cut fruits and vegetables was developed. The target genes were identified and screened by comparing the specific sequences of Salmonella Typhimurium, Vibrio parahemolyticus, Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli O157:H7 from the National Center for Biotechnology Information database. Tiling array probes were designed to target selected genes in an optimized hybridization system. A total of 141 specific probes were selected from 3,227 hybridization probes, comprising 26 L. monocytogenes, 24 S. aureus, 25 E. coli O157:H7, 20 Salmonella Typhimurium, and 46 V. parahemolyticus probes that are unique to this study. The optimized assay had strong amplification signals and high accuracy. The detection limit for the five target pathogens on fresh-cut cantaloupe and lettuce was approximately 3 log cfu/g without culturing and with a detection time of 24 h. The detection technology established in this study can rapidly detect and monitor the foodborne pathogens on fresh-cut fruits and vegetables throughout the logistical distribution chain, i.e., processing, cleaning, fresh-cutting, packaging, storage, transport, and sale, and represents a valuable technology that support the safety of fresh agricultural products.

Electrical DNA Biosensor Using Aluminium Interdigitated Electrode for Salmonella Detection

Nowadays there are many alternative methods that have been discovered and developed for the rapid detection of foodborne pathogens that can cause food poisoning. Unfortunately, majority of them still requires improvement in sensitivity and selectivity issues to be of any practical use daily. In this research, biosensors was prepared from 5 µm gap Aluminium interdigitated electrode (Al IDE) to detect Salmonella enterica typhi (S. typhi). The IDE sensors in the biosensor field is extremely interest in these days due to the high number of finger electrodes as comb structure which can gain high sensitivity through electrical measurements. S. typhi is a serious food borne pathogen, makes typhoid disease which causes many deaths annually in worldwide. Functionalization steps of the Al IDE to create biosensor was based on silanization by APTES, immobilization with carboxylic functionalized S. typhi ssDNA probes and blocking agent with tween-20 were the major functionalization steps. The functionalized steps were electrically characterized using current voltage measurements. The selectivity measurement was performed with specific target was identified electrically using complementary, non-complementary and single base mismatch ssDNA target.