Detection, Identification, and Analysis of Foodborne Pathogens

Fast detection of bacterial contamination in fresh produce using FTIR and spectral classification

Screening for microbial contaminants in fresh produce is a lengthy process relative to their short shelf-life. The aim of this study is to develop a comprehensive assay which employs FTIR and spectral classification algorithm for detection of bacterial contamination of fresh produce. The procedure starts by soaking a sample of the fresh produce in broth for 5 h. Then, magnetic nanoparticles are added to capture bacteria which are then collected and prepared for FTIR scanning. The generated FTIR spectra are compared against an in-house database of different bacterial species (n = 6). The ability of the database to discriminate contaminated and uncontaminated samples and to identify the bacterial species was assessed. The compatibility of the FTIR procedures with subsequent DNA extraction and PCR was tested. The developed procedure was applied for assessment of bacterial contamination in fresh produce samples from the market (n = 78). Results were compared to the conventional culture methods. The generated FTIR database coupled to spectral classification was able to detect bacterial contamination with overall accuracy exceeding 90%. The sample processing did not alter the integrity of the bacterial DNA which was suitable for PCR. On application to fresh produce samples collected from the market, the developed method was able to detect bacterial contamination with 94% concordance with the culture method. In conclusion, the developed procedure can be applied for fast detection of microbial contamination in fresh produce with comparable accuracy to conventional microbiological assays and is compatible with subsequent molecular assays.

Biosensors and Point-of-Care Devices for Bacterial Detection: Rapid Diagnostics Informing Antibiotic Therapy

With an exponential rise in antimicrobial resistance and stagnant antibiotic development pipeline, there is, more than ever, a crucial need to optimize current infection therapy approaches. One of the most important stages in this process requires rapid and effective identification of pathogenic bacteria responsible for diseases. Current gold standard techniques of bacterial detection include culture methods, polymerase chain reactions, and immunoassays. However, their use is fraught with downsides with high turnaround time and low accuracy being the most prominent. This imposes great limitations on their eventual application as point-of-care devices. Over time, innovative detection techniques have been proposed and developed to curb these drawbacks. In this review, a systematic summary of a range of biosensing platforms is provided with a strong focus on technologies conferring high detection sensitivity and specificity. A thorough analysis is performed and the benefits and drawbacks of each type of biosensor are highlighted, the factors influencing their potential as point-of-care devices are discussed, and the authors' insights for their translation from proof-of-concept systems into commercial medical devices are provided.

Culture-free biphasic approach for sensitive detection of Escherichia coli O157:H7 from beef samples

Foodborne illnesses are a major threat to public health also leading to significant mortality and financial and reputational damage to industry. It is very important to detect pathogen presence in food products early, rapidly, and accurately to avoid potential outbreaks and economic loss. However, "gold standard" culture methods, including enrichment of pathogens, can take up to several days. Moreover, the food matrix often interferes with nucleic acid amplification methods of detection, requiring DNA extraction from the sample for successful molecular detection of pathogens. Here, we introduce a "biphasic" amplification method that can achieve high sensitivity detection with background noise from ground beef food samples without culture or other extraction methods in 2.5 h. Homogenized ground beef is dried resulting in an increase in porosity of the dried food matrix to allowing amplification enzymes and primers to access the target DNA and initiate the reaction within the dried food matrix. Using Loop Mediated Isothermal Amplification, we demonstrate the detection of 1-3 cfu of Escherichia coli bacteria in 30 mg of dried food matrix. Our approach significantly lowers the time to result to less than a few hours and have a pronounced impact on reduction of instrumentation complexity and costs.

Aeromonas spp. isolated from ready-to-eat seafood on the Norwegian market: prevalence, putative virulence factors and antimicrobial resistance

AIMS

We aim to investigate the prevalence, putative virulence factors and antimicrobial resistance of mesophilic Aeromonas isolated from ready-to-eat (RTE) seafood available on the Norwegian market, and to assess the potential risks by consuming RTE seafood to consumers.

METHODS AND RESULTS

The prevalence of mesophilic Aeromonas in 148 RTE seafood was investigated and the highest prevalence was found in retail sushi (17%), followed by oysters (10%), fresh salmon loins (10%) and scallops (4%). Among 43 Aeromonas isolates, 75% of them were identified as A. media, 23% as A. salmonicida and 2% as A. bestiarum based on partial gryB gene sequencing. Aeromonas isolates were potentially pathogenic due to the presence of four virulence genes: alt (73%), hylA (22%), aerA (17%) and act (6%). In addition, all isolates were resistant to ampicillin and erythromycin. Most of the isolates (98%) were multidrug resistant.

CONCLUSIONS

The occurrence of potentially pathogenic and multidrug-resistant Aeromonas strains in RTE seafood implies a potential risk to consumers. Our finding suggests that RTE seafood could be a potential vehicle for the transfer of virulent and multidrug-resistant Aeromonas.

SIGNIFICANCE AND IMPACT OF THE STUDY

To our knowledge, this is the first study to report multiple antibiotic resistance in Aeromonas associated with RTE seafood in Norway.

Rapid and Sensitive Detection of Campylobacter jejuni in Poultry Products Using a Nanoparticle-Based Piezoelectric Immunosensor Integrated with Magnetic Immunoseparation

Campylobacter jejuni is one of the leading causes of foodborne human gastrointestinal diseases. Poultry and poultry products have been identified as the major transmission routes to humans for this pathogenic bacterium. The objective of this research was to develop a rapid and sensitive immunosensor for detection of C. jejuni in poultry products on the basis of a quartz crystal microbalance (QCM) using magnetic nanobeads (MNBs) for separation of target pathogen and gold nanoparticles for amplification of the measurement. A QCM sensor in a flow cell was prepared by immobilizing the mouse anti- C. jejuni monoclonal antibody (mAb₁) on the sensor surface to specifically capture C. jejuni. Rabbit anti- C. jejuni polyclonal antibody (pAb₁) was conjugated with MNBs to capture and separate C. jejuni from food matrices. MNB-pAb₁- C. jejuni complexes were injected into the flow cell to bind with the mAb₁ immobilized on the QCM sensor surface. Goat anti-rabbit immunoglobulin G polyclonal antibody conjugated with gold nanoparticles was injected into the flow cell to bind with pAb₁ on MNBs. Finally, resonant frequency was measured with a QCM analyzer, and the change in resonant frequency was correlated to the cell number of C. jejuni. The specificity of this immunosensor was confirmed with different strains of Campylobacter, Salmonella, and other foodborne pathogens commonly colonized in the broiler gastrointestinal tract. Samples of broiler carcass wash and ground turkey were spiked with C. jejuni at different concentrations for use in tests. Results showed that the QCM immunosensor could rapidly detect C. jejuni in poultry products, with a detection limit of 20 to 30 CFU/mL without preenrichment, and a total detection time of less than 30 min. Characteristics of C. jejuni captured by the antibody immobilized on the surface of the QCM sensor were visualized by using atomic force microscopy. This highly adaptive and flexible method could provide the poultry industry a more rapid, sensitive, and effective method for detection of major foodborne pathogens in poultry products.

Culture-free, highly sensitive, quantitative detection of bacteria from minimally processed samples using fluorescence imaging by smartphone

A critical unmet need in the diagnosis of bacterial infections, which remain a major cause of human morbidity and mortality, is the detection of scarce bacterial pathogens in a variety of samples in a rapid and quantitative manner. Herein, we demonstrate smartphone-based detection of Staphylococcus aureus in a culture-free, rapid, quantitative manner from minimally processed liquid samples using aptamer-functionalized fluorescent magnetic nanoparticles. The tagged S. aureus cells were magnetically captured in a detection cassette, and then fluorescence was imaged using a smartphone camera with a light-emitting diode as the excitation source. Our results showed quantitative detection capability with a minimum detectable concentration as low as 10 cfu/ml by counting individual bacteria cells, efficiently capturing S. aureus cells directly from a peanut milk sample within 10 min. When the selectivity of detection was investigated using samples spiked with other pathogenic bacteria, no significant non-specific detection occurred. Furthermore, strains of S. aureus from various origins showed comparable results, ensuring that the approach can be widely adopted. Therefore, the quantitative fluorescence imaging platform on a smartphone could allow on-site detection of bacteria, providing great potential assistance during major infectious disease outbreaks in remote and resource-limited settings.

Graphene-based label-free electrochemical aptasensor for rapid and sensitive detection of foodborne pathogen

Reduced graphene oxide (rGO) has emerged as a promising nanomaterial for reliable detection of pathogenic bacteria due to its exceptional properties such as ultrahigh electron transfer ability, large surface to volume ratio, biocompatibility, and its unique interactions with DNA bases of the aptamer. In this study, rGO-azophloxine (AP) nanocomposite aptasensor was developed for a sensitive, rapid, and robust detection of foodborne pathogens. Besides providing an excellent conductive and soluble rGO nanocomposite, the AP dye also acts as an electroactive indicator for redox reactions. The interaction of the label-free single-stranded deoxyribonucleic acid (ssDNA) aptamer with the test organism, Salmonella enterica serovar Typhimurium (S. Typhimurium), was monitored by differential pulse voltammetry analysis, and this aptasensor showed high sensitivity and selectivity for whole-cell bacteria detection. Under optimum conditions, this aptasensor exhibited a linear range of detection from 10⁸ to 10¹ cfu mL^-1 with good linearity (R ² = 0.98) and a detection limit of 10¹ cfu mL^-1. Furthermore, the developed aptasensor was evaluated with non-Salmonella bacteria and artificially spiked chicken food sample with S. Typhimurium. The results demonstrated that the rGO-AP aptasensor possesses high potential to be adapted for the effective and rapid detection of a specific foodborne pathogen by an electrochemical approach. Graphical abstract Fabrication of graphene-based nanocomposite aptasensor for detection of foodborne pathogen.

Pathogens of Food Animals: Sources, Characteristics, Human Risk, and Methods of Detection

Pathogens associated with food production (livestock) animals come in many forms causing a multitude of disease for humans. For the purpose of this review, these infectious agents can be divided into three broad categories: those that are associated with bacterial disease, those that are associated with viruses, and those that are parasitic in nature. The goal of this chapter is to provide the reader with an overview of the most common pathogens that cause disease in humans through exposure via the food chain and the consequence of this exposure as well as risk and detection methods. We have also included a collection of unusual pathogens that although rare have still caused disease, and their recognition is warranted in light of emerging and reemerging diseases. These provide the reader an understanding of where the next big outbreak could occur. The influence of the global economy, the movement of people, and food makes understanding production animal-associated disease paramount to being able to address new diseases as they arise.

Multiplex 16S rRNA-derived geno-biochip for detection of 16 bacterial pathogens from contaminated foods

Foodborne diseases caused by various pathogenic bacteria occur worldwide. To prevent foodborne diseases and minimize their impacts, it is important to inspect contaminated foods and specifically detect many types of pathogenic bacteria. Several DNA oligonucleotide biochips based on 16S rRNA have been investigated to detect bacteria; however, a mode of detection that can be used to detect diverse pathogenic strains and to examine the safety of food matrixes is still needed. In the present work, a 16S rRNA gene-derived geno-biochip detection system was developed after screening DNA oligonucleotide specific capture probes, and it was validated for multiple detection of 16 pathogenic strains that frequently occur with a signature pattern. rRNAs were also used as detection targets directly obtained from cell lysates without any purification and amplification steps in the bacterial cells separated from 8 food matrixes by simple pretreatments. Thus, the developed 16S rRNA-derived geno-biochip can be successfully used for the rapid and multiple detection of the 16 pathogenic bacteria frequently isolated from contaminated foods that are important for food safety.

Label-Free Detection and Discrimination of Bacterial Pathogens Based on Hemin Recognition

Hemin linked to hexa(ethylene glycol)bishydrazide was patterned by inkjet printing into periodic microarrays, and evaluated for their ability to capture bacterial pathogens expressing various hemin receptors. Bacterial adhesion was imaged under darkfield conditions with Fourier analysis, supporting a label-free method of pathogen detection. Hemin microarrays were screened against a panel of 16 bacteria and found capable of capturing multiple species, some with limits of detection as low as 10(3) cfu/mL. Several Gram-positive strains including Staphylococcus aureus and Bacillus anthracis also exhibited rapid adhesion, enabling pattern recognition within minutes of exposure. This can be attributed to differences in hemin acquisition systems: aggressively adherent bacteria express cell-surface hemin receptors (CSHRs) that enable direct hemin binding and uptake, whereas other types of bacteria including most Gram-negative strains rely on the secretion and recapture of soluble proteins (hemophores) for hemin acquisition, with consequently longer times for ligand binding and detection.