Rapid detection of food-borne pathogens by using molecular techniques

Utilizing fab fragment-conjugated surface plasmon resonance-based biosensor for detection of Salmonella Enteritidis

Although antibodies, a key element of biorecognition, are frequently used as biosensor probes, the use of these large molecules can lead to adverse effects. Fab fragments can be reduced to allow proper antigen-binding orientation via thiol groups containing Fab sites that can directly penetrate Au sites chemically. In this study, the ability of the surface plasmon resonance (SPR) sensor to detect Salmonella was studied. Tris(2-carboxyethyl)phosphine was used as a reducing agent to obtain half antibody fragments. Sensor surface was immobilized with antibody, and bacteria suspensions were injected from low to high concentrations. Response units were changed by binding first reduced antibody fragments, then bacteria. The biosensor was able to determine the bacterial concentrations between 103 and 108 CFU/mL. Based on these results, the half antibody fragmentation method can be generalized for faster, label-free, sensitive, and selective detection of other bacteria species.

Nanoarchitectonics of photothermal materials to enhance the sensitivity of lateral flow assays

Lateral flow assays (LFAs) are currently the most widely used point-of-care testing technique with remarkable advantages such as simple operation, rapid analysis, portability, and low cost. Traditionally, gold nanoparticles are employed as tracer element in LFAs due to their strong localised surface plasmon resonance. However, this conventional LFA technique based on colorimetric analysis is neither useful to determine critical analytes with desired sensitivity, nor can it quantify the analytes. Various signal amplification strategies have been proposed to improve the sensitivity and the quantitative determination of analytes using LFAs. One of the promising strategies is to enhance the photothermal properties of nanomaterials to generate heat after light irradiation, followed by a temperature measurement to detect and quantify the analyte concentration. Recently, it has been observed that the nanoscale architecture of materials, including size, shape, and nanoscale composition, plays a significant role in enhancing the photothermal properties of nanomaterials. In this review, we discuss the nanoarchitectonics of nanomaterials regarding enhanced photothermal properties and their application in LFAs. Initially, we discuss various important photothermal materials and their classification along with their working principle. Then, we highlight important aspects of the nanoscale architecture (i.e., size, shape, and composition) to enable maximum light-to-heat conversion efficiency. Finally, we discuss some of the recent advances in photothermal LFAs and their application in detecting analytes.

Aptamer-Based Electrochemical Biosensors for the Detection of Salmonella: A Scoping Review

The development of rapid, accurate, and efficient detection methods for Salmonella can significantly control the outbreak of salmonellosis that threatens global public health. Despite the high sensitivity and specificity of the microbiological, nucleic-acid, and immunological-based methods, they are impractical for detecting samples outside of the laboratory due to the requirement for skilled individuals and sophisticated bench-top equipment. Ideally, an electrochemical biosensor could overcome the limitations of these detection methods since it offers simplicity for the detection process, on-site quantitative analysis, rapid detection time, high sensitivity, and portability. The present scoping review aims to assess the current trends in electrochemical aptasensors to detect and quantify Salmonella. This review was conducted according to the latest Preferred Reporting Items for Systematic review and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A literature search was performed using aptamer and Salmonella keywords in three databases: PubMed, Scopus, and Springer. Studies on electrochemical aptasensors for detecting Salmonella published between January 2014 and January 2022 were retrieved. Of the 787 studies recorded in the search, 29 studies were screened for eligibility, and 15 studies that met the inclusion criteria were retrieved for this review. Information on the Salmonella serovars, targets, samples, sensor specification, platform technologies for fabrication, electrochemical detection methods, limit of detection (LoD), and detection time was discussed to evaluate the effectiveness and limitations of the developed electrochemical aptasensor platform for the detection of Salmonella. The reported electrochemical aptasensors were mainly developed to detect Salmonella enterica Typhimurium in chicken meat samples. Most of the developed electrochemical aptasensors were fabricated using conventional electrodes (13 studies) rather than screen-printed electrodes (SPEs) (two studies). The developed aptasensors showed LoD ranges from 550 CFU/mL to as low as 1 CFU/mL within 5 min to 240 min of detection time. The promising detection performance of the electrochemical aptasensor highlights its potential as an excellent alternative to the existing detection methods. Nonetheless, more research is required to determine the sensitivity and specificity of the electrochemical sensing platform for Salmonella detection, particularly in human clinical samples, to enable their future use in clinical practice.

Non-diarrhoeic pigs as source of highly virulent and multidrug-resistant non-typhoidal Salmonella

Food-producing animals act as reservoirs of non-typhoidal Salmonella (NTS) serovars with potential food safety and public health implications. The present cross-sectional study aimed at determining the prevalence of Salmonella serotypes in non-diarrhoeic pigs and characterizing the isolates using molecular tools. Salmonella isolates (n = 22) recovered from faecal samples of 194 randomly selected pigs were characterized for virulence and antimicrobial resistance and subtyped using XbaI-PFGE. The prevalence of Salmonella in apparently healthy non-diarrhoeic pigs was 11.3% (95%CI, 4.3-19.5%), with S. Weltevreden (81.8%) and S. Enteritidis (18.2%) being the serotypes detected. Salmonella isolates harboured virulence genes such as invA (100%), stn (100%), spvR/spvC (86.3%) and fimA (22.7%). Phenotypically, isolates showed sensitivity to chloramphenicol, levofloxacin and ciprofloxacin and resistance to tetracycline and ampicillin (100%), streptomycin (86.4%), amoxicillin-clavulanate (63.6%), cefotaxime (22.7%) and ceftriaxone (9.1%). Notably, 18.2% isolates were multidrug-resistant (≥ 3 antimicrobial class) with multiple antimicrobial resistance (MAR) index of 0.56-0.67 (18.2%), 0.44 (45.5%), 0.33 (31.8%) and 0.22 (4.5%). Genotypically, isolates carried various antibiotic resistance genes: ESBL (bla_TEM and bla_OXA), aminoglycoside (strA, strB and aadA1), sulphonamide (sul1, sul2 and dfrA1), tetracycline (tetA and tetB) and plasmid AmpC beta-lactamase (ACC, FOX, MOX, DHA, CIT and EBC). The present investigation emphasizes the epidemiological significance of PFGE typing in the detection of emerging strains of highly virulent and multidrug-resistant S. Weltevreden and S. Enteritidis in non-diarrhoeic pigs that pose serious public health implications in the pork supply chain environment. More extensive longitudinal study is warranted to provide epidemiological links between environmental reservoirs and animal and human infections in piggery settings.

A feasibility study for rapid evaluation of emulsion oxidation using synchronous fluorescence spectroscopy coupled with chemometrics

A rapid method based on three-dimensional synchronous fluorescence spectroscopy was developed for emulsion oxidation evaluation. This method was selected because of its high sensitivity to dissolved organic matter typically occurring in the lipid oxidation. Spectral signal and chemical reference measurements were recorded for each emulsion sample as input and output data for the model construction. Characteristic values were extracted from the spectral data by the application of parallel factor (PARAFAC) analysis. Partial least squares regression (PLSR) was then used to construct a regression model for the rapid determination of emulsion oxidation. The correlation coefficient of the calibration and prediction sets were used as the performance parameters for the PLSR models as follows: R = 0.929, 0.973 for emulsion samples stored at 25℃; R = 0.897, 0.903 for emulsion samples stored at 70℃. The overall results demonstrated that the fluorescence spectroscopy, coupled with PARAFAC and PLSR algorithms, could be successfully used as a rapid method for the emulsion oxidation evaluation.

Characterization of virulence factors of Salmonella isolated from human stools and street food in urban areas of Burkina Faso

Background

This study was undertaken to identify and functionally characterize virulence genes from Salmonella isolates in street food and stool cultures. From February 2017 to May 2018, clinical and food Salmonella strains were isolated in three regions in Burkina Faso. Salmonella was serotyped according to the White-Kauffmann-Le Minor method, and polymerase chain reaction (PCR) was used to detec invA, spvR, spvC, fimA and stn virulence genes commonly associated with salmonellosis in Sub-Saharan Africa.

Results

A total of 106 Salmonella isolates (77 human stools; 14 sandwiches) was analyzed using a serological identification with an O-group test reagent. The presence of Salmonella was confirmed in 86% (91/106) of the samples were reactive (OMA-positive/OMB-positive). Salmonella serogroup O:4,5 was the most common serogroup detected (40%; 36/91). Salmonella Enteritidis and Typhimurium represented 5.5% (5/91) and 3.3% (3/91), respectively and were identified only from clinical isolates. Furthermore, 14 serotypes of Salmonella (12/91 human strains and 2/15 sandwich strains) were evocative of Kentucky/Bargny serotype. For the genetic profile, 66% (70/106) of the Salmonella had invA and stn genes; 77.4% (82/106) had the fimA gene. The spvR gene was found in 36.8% (39/106) of the isolates while 48.1% (51/106) had the spvC gene. Among the identified Salmonella Enteritidis and Salmonella Typhimurium isolated from stools, the virulence genes detected were invA (3/5) versus (2/3), fimA (4/5) versus (3/3), stn (3/5) versus (2/3), spvR (4/5) versus (2/3) and spvC (3/5) versus (2/3), respectively.

Conclusion

This study reports the prevalence of Salmonella serotypes and virulence genes in clinical isolates and in street foods. It shows that food could be a significant source of Salmonella transmission to humans. Our results could help decision-making by the Burkina Faso health authority in the fight against street food-related diseases, in particular by training restaurateurs in food hygiene.

Nanomaterials in the Management of Gram-Negative Bacterial Infections

The exploration of multiplexed bacterial virulence factors is a major problem in the early stages of Escherichia coli infection therapy. Traditional methods for detecting Escherichia coli (E. coli), such as serological experiments, immunoassays, polymerase chain reaction, and isothermal microcalorimetry have some drawbacks. As a result, detecting E. coli in a timely, cost-effective, and sensitive manner is critical for various areas of human safety and health. Intelligent devices based on nanotechnology are paving the way for fast and early detection of E. coli at the point of care. Due to their specific optical, magnetic, and electrical capabilities, nanostructures can play an important role in bacterial sensors. Another one of the applications involved use of nanomaterials in fighting microbial infections, including E. coli mediated infections. Various types of nanomaterials, either used directly as an antibacterial agent such as metallic nanoparticles (NPs) (silver, gold, zinc, etc.), or as a nanocarrier to deliver and target the antibiotic to the E. coli and its infected area. Among different types, polymeric NPs, lipidic nanocarriers, metallic nanocarriers, nanomicelles, nanoemulsion/ nanosuspension, dendrimers, graphene, etc. proved to be effective vehicles to deliver the drug in a controlled fashion at the targeted site with lower off-site drug leakage and side effects.

Nucleic acid lateral flow assay for simultaneous detection of hygiene indicator bacteria

A simple and rapid polymerase chain reaction (PCR)-based lateral flow assay (LFA) was developed for multiplex detection of hygiene indicator bacteria. Specifically, new PCR primers were designed for accurately detecting Escherichia coli, coliform bacteria, and total bacteria, and the results obtained as a colorimetric signal (generated by the accumulation of gold nanoparticles at distinct test zones on flow strips) could be identified by the naked eye in <10 min after the completion of PCR. The proposed LFA system did not exhibit any cross-reactivities with 8 distinct bacterial strains and can detect down to 1 colony forming unit (CFU)/mL. Furthermore, three species of cultured bacteria (Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) inoculated onto sterilized ham were successfully analyzed using the LFA system, which demonstrated that this system shows sufficient sensitivity and specificity for food hygiene monitoring. The speed and simplicity of this LFA make it suitable for use in the food industry as part of routine screening analysis.

Application of a strain-level shotgun metagenomics approach on food samples: resolution of the source of a Salmonella food-borne outbreak

Food-borne outbreak investigation currently relies on the time-consuming and challenging bacterial isolation from food, to be able to link food-derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain-level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food-borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by whole-genome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short-read strain-level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics-derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food-borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame.

Machine Learning Prediction of Foodborne Disease Pathogens: Algorithm Development and Validation Study

Background

Foodborne diseases, as a type of disease with a high global incidence, place a heavy burden on public health and social economy. Foodborne pathogens, as the main factor of foodborne diseases, play an important role in the treatment and prevention of foodborne diseases; however, foodborne diseases caused by different pathogens lack specificity in clinical features, and there is a low proportion of clinically actual pathogen detection in real life.

Objective

We aimed to analyze foodborne disease case data, select appropriate features based on analysis results, and use machine learning methods to classify foodborne disease pathogens to predict foodborne disease pathogens that have not been tested.

Methods

We extracted features such as space, time, and exposed food from foodborne disease case data and analyzed the relationship between these features and the foodborne disease pathogens using a variety of machine learning methods to classify foodborne disease pathogens. We compared the results of 4 models to obtain the pathogen prediction model with the highest accuracy.

Results

The gradient boost decision tree model obtained the highest accuracy, with accuracy approaching 69% in identifying 4 pathogens including Salmonella, Norovirus, Escherichia coli, and Vibrio parahaemolyticus. By evaluating the importance of features such as time of illness, geographical longitude and latitude, and diarrhea frequency, we found that they play important roles in classifying the foodborne disease pathogens.

Conclusions

Data analysis can reflect the distribution of some features of foodborne diseases and the relationship among the features. The classification of pathogens based on the analysis results and machine learning methods can provide beneficial support for clinical auxiliary diagnosis and treatment of foodborne diseases.

Development of an endolysin enzyme and its cell wall-binding domain protein and their applications for biocontrol and rapid detection of Clostridium perfringens in food

Clostridium perfringens is a well-known pathogen that causes food-borne illnesses. Although bacteriophages can be effective natural food preservatives, phage endolysin and cell wall-binding domain (CBD) provide useful materials for lysis of C. perfringens and rapid detection. The genome of phage CPAS-15 consists of 51.8-kb double-stranded circular DNA with 78 open reading frames, including an endolysin gene. The apparent absence of a virulence factor or toxin gene suggests its safety in food applications. C. perfringens endolysin (LysCPAS15) inhibits host cells by up to a 3-log reduction in 2 h, and enhanced green fluorescent protein (EGFP)-fused CBD protein (EGFP-LysCPAS15_CBD1) detects C. perfringens within 5 min. Both exhibit broader host range spectra and higher stabilities than a bacteriophage. Tests in milk show the same host lysis and specific detection activities, with no hindrance effect from food matrices, indicating that endolysin and its CBD can provide food extended protection from C. perfringens contamination.

Prevalence of Salmonella enterica on poultry processing equipment after completion of sanitization procedures

Salmonella is a poultry-borne pathogen that causes illness throughout the world. Consequently, it is critical to control Salmonella during the process of converting broilers to poultry meat. Sanitization of a poultry processing facility, including processing equipment, is a crucial control measure that is utilized by poultry integrators. However, prevalence of Salmonella on equipment after sanitization and its potential risk to food safety has not been evaluated thoroughly. Therefore, the objective of this study was to evaluate the persistence of Salmonella on poultry processing equipment before and following cleaning and sanitization procedure. A total of 15 locations within 6 commercial processing plants were sampled at 3 time points: (A) after processing; (B) after cleaning; and (C) after sanitization, on 3 separate visits for a total of 135 samples per plant. Salmonella-positive isolates were recovered from samples using the United States Department of Agriculture MLG 4.09 conventional method. Presumptive Salmonella colonies were subjected to biochemical tests for confirmation. Salmonella isolates recovered after sanitization were serotyped and tested for the presence of specific virulence genes. A completely randomized design with a 6 × 3 × 15 factorial arrangement was utilized to analyze the results for Salmonella prevalence between processing plants. Means were separated using Fishers protected least significant difference when P ≤ 0.05. For Salmonella prevalence between processing plants, differences (P < 0.0001) were observed in the 6 plants tested where the maximum and minimum prevalence was 29.6 and 7.4%, respectively. As expected, there was a difference (P < 0.0001) in the recovery of Salmonella because of sampling time. Salmonella prevalence at time A (36%) was significantly higher, whereas there was no difference between time B (12%) and C (9%). There was a location effect (P < 0.0001) for the prevalence of Salmonella with the head puller, picker, cropper, and scalder having a significantly higher prevalence when compared with several other locations. At sampling time C, a trend toward a difference (P = 0.0899) was observed for Salmonella prevalence between the 6 plants, whereas significant differences were observed because of location (P = 0.0031). Five prominent Salmonella enterica serovars were identified, including Kentucky, Schwarzengrund, Enteritidis, Liverpool, and Typhimurium with S. Kentucky being the most prevalent. PCR analysis of 8 Salmonella virulence genes showed that the invA, sipB, spiA, sseC, and fimA were detected in all isolates, whereas genes carried on plasmids and/or fimbriae varied remarkably among all isolates. This study established Salmonella prevalence and persistence in poultry processing facilities after antimicrobial application through sanitization procedures which could result in contamination of poultry carcasses and food safety risks because of poultry meat.

Okoh A. Campylobacteriosis Agents in Meat Carcasses Collected from Two District Municipalities in the Eastern Cape Province, South Africa

Raw meats are sometimes contaminated with Campylobacter species from animal faeces, and meats have repeatedly been implicated in foodborne infections. This study evaluated the prevalence, virulence genes, antimicrobial susceptibility patterns, and resistance gene determinants in Campylobacter species isolated from retailed meat carcasses. A total of 248 raw meat samples were collected from butcheries, supermarkets, and open markets; processed for enrichment in Bolton broth; and incubated at 42 °C for 48 h in 10% CO2. Thereafter, the broths were streaked on modified charcoal cefoperazone deoxycholate agar (mCCDA) plates and incubated at the same conditions and for the same amount of time. After incubation, colonies were isolated and confirmed by Polymerase chain reaction using specific oligonucleotide sequences used for the identification of the genus Campylobacter, species, and their virulence markers. The patterns of antimicrobial resistance profiles of the identified isolates were studied by disk diffusion method against 12 antibiotics, and relevant resistance genes were assessed by PCR. From culture, 845 presumptive Campylobacter isolates were obtained, of which 240 (28.4%) were identified as genus Campylobacter. These were then characterised into four species, of which C. coli had the highest prevalence rate (22.08%), followed by C. jejuni (16.66%) and C. fetus (3.73%). The virulence genes detected included iam (43.14%), cadF (37.25%), cdtB (23.53%), flgR (18.63%), and flaA (1.96%), and some of the isolates co-harboured two to four virulence genes. Of the 12 antibiotics tested, the highest phenotypic resistance displayed by Campylobacter isolates was against clindamycin (100%), and the lowest level of resistance was observed against imipenem (23.33%). The frequency of resistance genes detected included catll (91.78%), tetA (68.82%), gyra (61.76%), ampC (55%), aac(3)-IIa (aacC2)a (40.98%), tetM (38.71%), ermB (18.29%), tetB (12.90%), and tetK (2.15%). There is a high incidence of Campylobacter species in meat carcasses, suggesting these to be a reservoir of campylobacteriosis agents in this community, and as such, consumption of undercooked meats in this community is a potential health risk to consumers.

A Label-Free, Non-Intrusive, and Rapid Monitoring of Bacterial Growth on Solid Medium Using Microwave Biosensor

Microwave resonator sensors are attractive for their contactless and label-free capability of monitoring bacterial growth in liquid media. This paper outlines a new label-free microwave biosensor based on a pair of planar split ring resonators for non-invasive monitoring of bacterial growth on a solid agar media. The sensor is comprised of two split ring resonators with slightly different resonant frequencies for differential operation. The transmission coefficient (S₂₁) of the sensor is considered as the sensor's response with a designed and measured quality factor above 200 to ensure a high-resolution operation of the biosensor. Two resonant frequencies of 1.95 and 2.11 GHz represent the sensing signal and the reference signal, respectively. The developed sensor demonstrates high performance in monitoring the growth dynamics of Escherichia coli (E. coli) on Luria-Bertani (LB) agar with 4 mm thickness. The sensor's resonant amplitude response demonstrated 0.5 dB variation corresponding to the bacterial growth over 48 hours when bacteria were spread on LB agar starting with initial OD₆₀₀ = 1.5. Moreover, 0.6 dB change in the sensor's response was observed over 96 hours of bacterial growth starting with an initial OD₆₀₀ = 1.17 spotted on LB agar. The measured results fit well to the curves created using Richards' bacterial growth model, showing the strength of the sensor as a potential candidate for use in predictive food microbiology systems.

Next-generation sequencing as a screening tool for foodborne pathogens in fresh produce

Next generation sequencing (NGS) approaches are increasingly applied to tracing microbial contaminants entering the food chain due to NGS' untargeted nature and ability to investigate non-culturable (and/or difficult to culture) organisms while yielding genomic information about the microbiota. So far, a plethora of microbes has been shown to be associated with fresh produce, but few studies have utilised NGS to identify contamination with human pathogens. This study aims to establish the limit of detection (LoD) for Salmonella and phage MS2 (a Norovirus surrogate) contamination of fresh produce employing NGS approaches on the Illumina MiSeq: 16S amplicon-sequencing, and RNA-seq, using ScriptSeq (Illumina) and NEBNext (New England BioLabs) kits. ScriptSeq proved the most sensitive approach; delivering an LoD of 10⁴ CFU reaction^-1 (Colony Forming Units) for Salmonella and 10⁵ PFU reaction^-1 (Plaque Forming Units) for phage MS2. Use of the NEBNext kit resulted in detection of Salmonella at 10⁶ CFU reaction^-1 and phage MS2 at 10⁷ PFU reaction^-1. 16S amplicon-sequencing yielded a similar LoD of 10⁵ CFU reaction^-1 for Salmonella but could not detect MS2. The tested NGS methodologies, in combination with bioinformatics approaches applied, proved less sensitive than conventional microbial detection approaches.

Seafood spoilage microbiota and associated volatile organic compounds at different storage temperatures and packaging conditions

Seafood comprising of both vertebrate and invertebrate aquatic organisms are nutritious, rich in omega-3 fatty acids, essential vitamins, proteins, minerals and form part of healthy diet. However, despite the health and nutritional benefits, seafood is highly perishable. Spoilage of seafood could be as a result of microbial activity, autolysis or chemical oxidation. Microbial activity constitutes more spoilage than others. Spoilage bacteria are commonly Gram negative and produce off odours and flavours in seafood as a result of their metabolic activities. Storage temperature, handling and packaging conditions affect microbial growth and thus the shelf-life of seafood. Due to the complexity of the microbial communities in seafood, culture dependent methods of detection may not be useful, hence the need for culture independent methods are necessary to understand the diversity of microbiota and spoilage process. Similarly, the volatile organic compounds released by spoilage bacteria are not fully understood in some seafood. This review therefore highlights current knowledge and understanding of seafood spoilage microbiota, volatile organic compounds, effects of storage temperature and packaging conditions on quality of seafood.

CE method for analyzing Salmonella typhimurium in water samples

Salmonella typhimurium is commonly described as a food-borne pathogen. However, natural and drinking water are known to be important sources for the transmission of this pathogen in developing and developed countries. The standard method to determine Salmonella is laborious and many false positives are detected. To solve this, the present work was focused on the development of a capillary zone electrophoresis method coupled to ultraviolet detection for determination of Salmonella typhimurium in water (mineral and tap water). Separations were performed in less than 11 minutes using 4.5 mM Tris (hydroxymethyl)-aminomethane, 4.5 mM boric acid and 0.1 mM ethylene diamine tetraacetate (pH 8.4) with 0.1% v/v poly ethylene oxide as separation buffer. The precision of the method was evaluated in terms of repeatability obtaining a relative standard deviation of 10.5%. Using the proposed method Salmonella typhimurium could be separated from other bacteria that could be present in water such as Escherichia coli. Finally, the proposed methodology was applied to determine Salmonella typhimurium in tap and mineral water.

Rapid and Accurate Diagnosis Based on Real-Time PCR Cycle Threshold Value for the Identification of Campylobacter jejuni, astA Gene-Positive Escherichia coli, and eae Gene-Positive E. coli

We previously developed a multiplex real-time PCR assay (Rapid Foodborne Bacterial Screening 24 ver.5, [RFBS24 ver.5]) for simultaneous detection of 24 foodborne bacterial targets. Here, to overcome the discrepancy of the results from RFBS24 ver.5 and bacterial culture methods (BC), we analyzed 246 human clinical samples from 49 gastroenteritis outbreaks using RFBS24 ver.5 and evaluated the correlation between the cycle threshold (CT) value of RFBS24 ver.5 and the BC results. The results showed that the RFBS24 ver.5 was more sensitive than BC for Campylobacter jejuni and Escherichia coli harboring astA or eae, with positive predictive values (PPV) of 45.5-87.0% and a kappa coefficient (KC) of 0.60-0.92, respectively. The CTs were significantly different between BC-positive and -negative samples (p ＜ 0.01). All RFBS24 ver.5-positive samples were BC-positive under the lower confidence interval (CI) limit of 95% or 99% for the CT of the BC-negative samples. We set the 95% or 99% CI lower limit to the determination CT (d-CT) to discriminate for assured BC-positive results (d-CTs: 27.42-30.86), and subsequently the PPVs (94.7%-100.0%) and KCs (0.89-0.95) of the 3 targets were increased. Together, we concluded that the implication of a d-CT-based approach would be a valuable tool for rapid and accurate diagnoses using the RFBS24 ver.5 system.

Analysis of the bacterial microbiome in the small octopus, Octopus variabilis, from South Korea to detect the potential risk of foodborne illness and to improve product management

The small octopus (Octopus variabilis) is a popular seafood in many countries including South Korea. Because it is often consumed uncooked, the microorganisms in it often cause food poisoning. Therefore, analyzing the microbiome of the small octopus can help to understand the risk of food poisoning and manage octopus products better. A total of 40 small octopuses were collected from four sites in November and August. The microbiota was analyzed using Illumina Miseq sequencing, and the amount of bacteria was quantified by real-time PCR. In addition, we analyzed the influence of Vibrio vulnificus infection on the microbiome of the small octopus through artificial infection experiments. Bacteroidetes was the predominant phylum in August, and Proteobacteria was predominant in November. The composition of the microbiota in octopus depended on sampling region and season. The potential risk of foodborne illness from small octopus consumption might be higher in August than in November due to the abundance of potential pathogens. In the infection experiment, the proportion of V. vulnificus increased only at 27°C. The composition and functional gene profiles of the microbiota varied in a similar manner between non-infected and infected samples over time at the same temperature. These results indicated that the indigenous microbiota in small octopus could inhibit colonization by V. vulnificus during storage. Although further studies are necessary to clarify these results, our results could help us better understand food poisoning through octopus ingestion and manage products.

An integrated microfluidic PCR system with immunomagnetic nanoparticles for the detection of bacterial pathogens

There is growing interest in rapid microbial pre-concentration methods to lower the detection limit of bacterial pathogens of low abundance in samples. Here, we report an integrated microfluidic PCR system that enables bacterial cells of interest in samples to be concentrated prior to PCR. It consists of two major compartments: a preconcentration chamber for the immunomagnetic separation of bacterial cells, and a PCR chamber for the DNA amplification of the concentrated cells. We demonstrate the feasibility of the system for the detection of microbial pathogens by preconcentrating the human pathogen Escherichia coli O157:H7, and also amplifying its DNA. The detection limit of E. coli O157:H7 in the PCR system is 1 × 10³ CFU (colony forming unit)/mL. On-chip processing steps, including preconcentration and PCR steps, take less than two hours. Our system can serve as a rapid, specific, and quantitative platform for the detection of microbial pathogens in samples of large volume.

Detection Methodologies for Pathogen and Toxins: A Review

Pathogen and toxin-contaminated foods and beverages are a major source of illnesses, even death, and have a significant economic impact worldwide. Human health is always under a potential threat, including from biological warfare, due to these dangerous pathogens. The agricultural and food production chain consists of many steps such as harvesting, handling, processing, packaging, storage, distribution, preparation, and consumption. Each step is susceptible to threats of environmental contamination or failure to safeguard the processes. The production process can be controlled in the food and agricultural sector, where smart sensors can play a major role, ensuring greater food quality and safety by low cost, fast, reliable, and profitable methods of detection. Techniques for the detection of pathogens and toxins may vary in cost, size, and specificity, speed of response, sensitivity, and precision. Smart sensors can detect, analyse and quantify at molecular levels contents of different biological origin and ensure quality of foods against spiking with pesticides, fertilizers, dioxin, modified organisms, anti-nutrients, allergens, drugs and so on. This paper reviews different methodologies to detect pathogens and toxins in foods and beverages.

A review on detection methods used for foodborne pathogens

Foodborne pathogens have been a cause of a large number of diseases worldwide and more so in developing countries. This has a major economic impact. It is important to contain them, and to do so, early detection is very crucial. Detection and diagnostics relied on culture-based methods to begin with and have developed in the recent past parallel to the developments towards immunological methods such as enzyme-linked immunosorbent assays (ELISA) and molecular biology-based methods such as polymerase chain reaction (PCR). The aim has always been to find a rapid, sensitive, specific and cost-effective method. Ranging from culturing of microbes to the futuristic biosensor technology, the methods have had this common goal. This review summarizes the recent trends and brings together methods that have been developed over the years.

Advanced molecular diagnostic techniques for detection of food-borne pathogens: Current applications and future challenges

The elimination of disease-causing microbes from the food supply is a primary goal and this review deals with the overall techniques available for detection of food-borne pathogens. Now-a-days conventional methods are replaced by advanced methods like Biosensors, Nucleic Acid-based Tests (NAT), and different PCR-based techniques used in molecular biology to identify specific pathogens. Bacillus cereus, Staphylococcus aureus, Proteus vulgaris, Escherichia coli, Campylobacter, Listeria monocytogenes, Salmonella spp., Aspergillus spp., Fusarium spp., Penicillium spp., and pathogens are detected in contaminated food items that cause always diseases in human in any one or the other way. Identification of food-borne pathogens in a short period of time is still a challenge to the scientific field in general and food technology in particular. The low level of food contamination by major pathogens requires specific sensitive detection platforms and the present area of hot research looking forward to new nanomolecular techniques for nanomaterials, make them suitable for the development of assays with high sensitivity, response time, and portability. With the sound of these, we attempt to highlight a comprehensive overview about food-borne pathogen detection by rapid, sensitive, accurate, and cost affordable in situ analytical methods from conventional methods to recent molecular approaches for advanced food and microbiology research.

Comparison of Upgraded Methods for Detecting Pathogenic Escherichia coli in Foods Using Centrifugation or Filtration

In the present study, centrifugation and filtration pretreatments were evaluated to decrease sample preparation time and to improve the sensitivity and specificity of multiplex polymerase chain reaction (PCR) for the detection of low levels of pathogenic Escherichia coli in various foods. Pathogenic E. coli (E. coli NCCP11142, E. coli NCCP14037, E. coli NCCP 14038, E. coli NCCP14039, and E. coli NCCP15661) was inoculated into pork, beef, and baby leafy vegetables at 1, 2, and 3 Log CFU/g. The samples were shaken 30 times (control), then centrifuged or filtered. DNA extracts from the samples were subjected to PCR using the Powerchek^TM Diarrheal E. coli 8-plex Detection Kit. In the pork samples, no E. coli was detected in the control samples, while E. coli were detected in 100% of 3-Log CFU/g inoculated and centrifuged samples, and in 100% of 2 and 3-Log CFU/g inoculated, and filtered samples. In the beef samples, all control samples appeared to be E. coli-negative, while E. coli was detected in 50-75% of centrifuged samples, regardless of inoculated level, and in 100% of 2 and 3-Log CFU/g inoculated, and filtered samples. In baby leafy vegetables, E. coli were not detected in 25-50% of the control samples, while E. coli were detected in 0-25% of the centrifuged samples, and 75-100% of the filtered samples, depending on the inoculum amount. In conclusion, filtration pretreatment can be used to minimize sample preparation time, and improve the sensitivity and specificity of rapid detection of pathogenic E. coli in various foods.

Pathology and Molecular Characterization of Escherichia Coli Associated With the Avian Salpingitis-Peritonitis Disease Syndrome

Outbreaks of salpingitis and peritonitis cause major economic losses due to high mortality, reduced egg-production, and culling. The aim of the present study was to characterize, in detail, lesions associated with increased mortality in layers due to avianpathogenic Escherichia coli (APEC) and to investigate the population structure of the E. coli involved, which is important for selection of optimal treatment and prophylactic strategies. Among 322 layers received from eight farms with increased mortality due to E. coli, three lesion types were observed; sepsis-like lesions, chronic salpingitis and peritonitis, and chronic salpingitis and peritonitis associated with sepsis-like lesions. One hundred isolates of E. coli obtained in pure culture from the different lesion types were selected for genetic characterization. Six out of 10 submissions (two farms with two submissions) were considered clonal as defined by more than 85% of the typed isolates of E. coli belonging to the same sequence-type (ST). B2 was the most-prevalent phylogroup, including the clonal complex of ST95. The most-important virulence genes of E. coli were demonstrated from both clonal and nonclonal outbreaks, and major differences as to phylogeny and virulence genes were not observed between the lesion types. Cannibalism was more-often observed during polyclonal outbreaks. A new pathotype of APEC is suggested based upon lesions and route of infection, high similarity of virulence genes including plasmid-associated genes, and high frequency of ST95 and other isolates belonging to phylogroup B2. Compared to the best-known pathotypes of E. coli, this needs further investigations, including infection experiments to show if single virulence factors can be pointed out that are specific for the salpingitis-peritonitis pathotype and possibly not found in other pathotypes of E. coli.

A rapid method for isolation of genomic DNA from food-borne fungal pathogens

Food contaminated with fungal pathogens can cause extremely harmful effects to human even when present in low concentrations. Researchers now pay more attention towards rapid DNA extraction for the quick screening, which is highly demanded in diverse research field. Molecular description of many fungal species is identified by different molecular characteristics. Hence, the efficient isolation of genomic DNA and amplification using PCR is a prerequisite for molecular characterization. Here, we used an improved Sodium dodecyl sulfate-Cetyltrimethyl ammonium bromide-Chloroform-isoamyl alcohol method by combining Sodium dodecyl sulfate with cetyl methylammonium bromide without addition of proteinase K, RNase K, and β-mercaptoethanol. To analyze the quality of recovered DNA, this method was compared with the other four routine methods. The present method has been chosen in the study as a preferred method because of easy adaptation to routine laboratories/food industries considering its rapid, sensitivit,y and cost effectiveness involved in the method.

Simultaneous Identification of 13 Foodborne Pathogens by Using Capillary Electrophoresis-Single Strand Conformation Polymorphism Coupled with Multiplex Ligation-Dependent Probe Amplification and Its Application in Foods

Capillary electrophoresis-single strand conformation polymorphism (CE-SSCP) coupled with stuffer-free multiplex ligation-dependent probe amplification (MLPA) was developed to identify 13 species of foodborne pathogens simultaneously. Species-specific MLPA probes were designed for nine of these species. These probes were targeted to the groEL, glyA, MMS, tuf, inv, ipaH, nuc, vvh, and 16S rRNA genes, which corresponded to Bacillus cereus, Campylobacter coli, Cronobacter sakazakii, Enterococcus spp., Salmonella spp., Shigella spp., Staphylococcus aureus, Vibrio vulnificus, and Yersinia enterocolitica, respectively. MLPA probes that had been previously developed by our laboratory were used for the other four species (Campylobacter jejuni, Clostridium perfringens, Escherichia coli O157:H7, and Listeria monocytogenes). The CE-SSCP method was optimized to identify all 13 foodborne microbes simultaneously in a single electrogram, in which 50-500 pg genomic DNA was detected per microbe. Twelve species were detected from animal-derived food samples (specifically, milk and sliced ham) that had been artificially inoculated with 12 of the foodborne pathogens, excluding V. vulnificus, which is not usually associated with animal foods. The method developed here could be used as an early warning system for outbreaks of foodborne diseases associated with animal-derived foods in the food industry.

Analysis of microbiota on abalone (Haliotis discus hannai) in South Korea for improved product management

Abalone is a popular seafood in South Korea; however, because it contains various microorganisms, its ingestion can cause food poisoning. Therefore, analysis of the microbiota on abalone can improve understanding of outbreaks and causes of food poisoning and help to better manage seafood products. In this study, we collected a total of 40 abalones from four different regions in March and July, which are known as the maximum abalone production areas in Korea. The microbiota were analyzed using high-throughput sequencing, and bacterial loads on abalone were quantified by real-time PCR. Over 2700 species were detected in the samples, and Alpha- and Gammaproteobacteria were the predominant classes. The differences in microbiota among regions and at each sampling time were also investigated. Although Psychrobacter was the dominant genus detected on abalone in both March and July, the species compositions were different between the two sampling times. Five potential pathogens (Lactococcus garvieae, Yersinia kristensenii, Staphylococcus saprophyticus, Staphylococcus warneri, and Staphylococcus epidermidis) were detected among the abalone microbiota. In addition, we analyzed the influence of Vibrio parahaemolyticus infection on shifts in abalone microbiota during storage at different temperatures. Although the proportion of Vibrio increased over time in infected and non-infected abalone, the shifts of microbiota were more dynamic in infected abalone. These results can be used to better understand the potential of food poisoning caused by abalone consumption and manage abalone products according to the microbiota composition.

Cationized Magnetoferritin Enables Rapid Labeling and Concentration of Gram-Positive and Gram-Negative Bacteria in Magnetic Cell Separation Columns

In order to identify pathogens rapidly and reliably, bacterial capture and concentration from large sample volumes into smaller ones are often required. Magnetic labeling and capture of bacteria using a magnetic field hold great promise for achieving this goal, but the current protocols have poor capture efficiency. Here, we present a rapid and highly efficient approach to magnetic labeling and capture of both Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria using cationized magnetoferritin (cat-MF). Magnetic labeling was achieved within a 1-min incubation period with cat-MF, and 99.97% of the labeled bacteria were immobilized in commercially available magnetic cell separation (MACS) columns. Longer incubation times led to more efficient capture, with S. aureus being immobilized to a greater extent than E. coli. Finally, low numbers of magnetically labeled E. coli bacteria (<100 CFU per ml) were immobilized with 100% efficiency and concentrated 7-fold within 15 min. Therefore, our study provides a novel protocol for rapid and highly efficient magnetic labeling, capture, and concentration of both Gram-positive and Gram-negative bacteria.

IMPORTANCE Antimicrobial resistance (AMR) is a significant global challenge. Rapid identification of pathogens will retard the spread of AMR by enabling targeted treatment with suitable agents and by reducing inappropriate antimicrobial use. Rapid detection methods based on microfluidic devices require that bacteria are concentrated from large volumes into much smaller ones. Concentration of bacteria is also important to detect low numbers of pathogens with confidence. Here, we demonstrate that magnetic separation columns capture small amounts of bacteria with 100% efficiency. Rapid magnetization was achieved by exposing bacteria to cationic magnetic nanoparticles, and magnetized bacteria were concentrated 7-fold inside the column. Thus, bacterial capture and concentration were achieved within 15 min. This approach could be extended to encompass the capture and concentration of specific pathogens, for example, by functionalizing magnetic nanoparticles with antibodies or small molecule probes.

Pyrosequencing analysis of microbial community and food-borne bacteria on restaurant cutting boards collected in Seri Kembangan, Malaysia, and their correlation with grades of food premises

This study adopts the pyrosequencing technique to identify bacteria present on 26 kitchen cutting boards collected from different grades of food premises around Seri Kembangan, a city in Malaysia. Pyrosequencing generated 452,401 of total reads of OTUs with an average of 1.4×10(7) bacterial cells/cm(2). Proteobacteria, Firmicutes and Bacteroides were identified as the most abundant phyla in the samples. Taxonomic richness was generally high with >1000 operational taxonomic units (OTUs) observed across all samples. The highest appearance frequencies (100%) were OTUs closely related to Enterobacter sp., Enterobacter aerogenes, Pseudomonas sp. and Pseudomonas putida. Several OTUs were identified most closely related to known food-borne pathogens, including Bacillus cereus, Cronobacter sakazaki, Cronobacter turisensis, Escherichia coli, E. coli O157:H7, Hafnia alvei, Kurthia gibsonii, Salmonella bongori, Salmonella enterica, Salmonella paratyphi, Salmonella tyhpi, Salmonella typhimurium and Yersinia enterocolitica ranging from 0.005% to 0.68% relative abundance. The condition and grade of the food premises on a three point cleanliness scale did not correlate with the bacterial abundance and type. Regardless of the status and grades, all food premises have the same likelihood to introduce food-borne bacteria from cutting boards to their foods and must always prioritize the correct food handling procedure in order to avoid unwanted outbreak of food-borne illnesses.

Virulence genes detection of Salmonella serovars isolated from pork and slaughterhouse environment in Ahmedabad, Gujarat

Aim:

The aim was to detect virulence gene associated with the Salmonella serovars isolated from pork and Slaughterhouse environment.

Materials and Methods:

Salmonella isolates (n=37) used in this study were isolated from 270 pork and slaughter house environmental samples collected from the Ahmedabad Municipal Corporation Slaughter House, Ahmedabad, Gujarat, India. Salmonella serovars were isolated and identified as per BAM USFDA method and serotyped at National Salmonella and Escherichia Centre, Central Research Institute, Kasauli (Himachal Pradesh, India). Polymerase chain reaction technique was used for detection of five genes, namely invA, spvR, spvC, fimA and stn among different serovars of Salmonella.

Results:

Out of a total of 270 samples, 37 (13.70%) Salmonella were isolated with two serovars, namely Enteritidis and Typhimurium. All Salmonella serovars produced 284 bp invA gene, 84 bp fimA and 260 bp amplicon for enterotoxin (stn) gene whereas 30 isolates possessed 310 bp spvR gene, but no isolate possessed spvC gene.

Conclusion:

Presence of invA, fimA and stn gene in all isolates shows that they are the specific targets for Salmonella identification and are capable of producing gastroenteric illness to humans, whereas 20 Typhimurium serovars and 10 Enteritidis serovars can able to produce systemic infection.

Molecular methods for microbiological quality control of meat and meat products: a review

Achieving food safety is a global health goal and the food-borne diseases take a major check on global health. Therefore, detection of microbial pathogens in food is the solution to the prevention and recognition of problems related to health and safety. Conventional and standard bacterial detection methods such as culture and colony counting methods and immunology-based methods may take up to several hours or even a few days to yield a result. Obviously, this is inadequate, and recently many researchers are focusing towards the progress of rapid diagnostic methods. The advent of molecular techniques has led to the development of a diverse array of assay for quality control of meat and meat products. Rapid analysis using DNA hybridization and amplification techniques offer more sensitivity and specificity to get results than culture based methods as well as dramatic reduction in the time to get results. Many methods have also achieved the high level automation, facilitating their application as routine sample screening assays. This review is intended to provide an overview of the molecular methods for microbiological quality control of meat and meat products.

High-throughput detection of food-borne pathogenic bacteria using oligonucleotide microarray with quantum dots as fluorescent labels

Bacterial pathogens are mostly responsible for food-borne diseases, and there is still substantial room for improvement in the effective detection of these organisms. In the present study, we explored a new method to detect target pathogens easily and rapidly with high sensitivity and specificity. This method uses an oligonucleotide microarray combined with quantum dots as fluorescent labels. Oligonucleotide probes targeting the 16SrRNA gene were synthesized to create an oligonucleotide microarray. The PCR products labeled with biotin were subsequently hybridized using an oligonucleotide microarray. Following incubation with CdSe/ZnS quantum dots coated with streptavidin, fluorescent signals were detected with a PerkinElmer Gx Microarray Scanner. The results clearly showed specific hybridization profiles corresponding to the bacterial species assessed. Two hundred and sixteen strains of food-borne bacterial pathogens, including standard strains and isolated strains from food samples, were used to test the specificity, stability, and sensitivity of the microarray system. We found that the oligonucleotide microarray combined with quantum dots used as fluorescent labels can successfully discriminate the bacterial organisms at the genera or species level, with high specificity and stability as well as a sensitivity of 10 colony forming units (CFU)/mL of pure culture. We further tested 105 mock-contaminated food samples and achieved consistent results as those obtained from traditional biochemical methods. Together, these results indicate that the quantum dot-based oligonucleotide microarray has the potential to be a powerful tool in the detection and identification of pathogenic bacteria in foods.

Rapid differentiation of Listeria monocytogenes epidemic clones III and IV and their intact compared with heat-killed populations using Fourier transform infrared spectroscopy and chemometrics

The objectives of this study were to determine if Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat-killed populations. FT-IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1-101 and R2-499; ECIV: J1-129 and J1-220), and also from intact and heat-killed cell populations of each EC strain using 250 scans at a resolution of 4 cm(-1) in the mid-infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm(-1) separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat-killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT-IR spectral wavenumbers 1650 to 1390 cm(-1) were used to separate heat-killed and intact populations of L. monocytogenes. The FT-IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT-IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism.

PRACTICAL APPLICATION

Fourier transform infrared (FT-IR) spectroscopy and multivariate statistical analysis can be used for L. monocytogenes source tracking and for clinical case isolate comparison during epidemiological investigations since the method is capable of differentiating epidemic clones and it uses a library of well-characterized strains. The FT-IR method is potentially less expensive and more rapid compared to genetic subtyping methods, and can be used for L. monocytogenes strain typing by food industries and public health agencies to enable faster response and intervention to listeriosis outbreaks. FT-IR can also be applied for routine monitoring of the pathogen in food processing plants and for investigating postprocessing contamination because it is capable of differentiating heat-killed and viable L. monocytogenes populations.