Rapid quantification of coliforms in ready‐to‐eat foods using lateral‐flow immunochromatographic assay

Review of Detection Limits for Various Techniques for Bacterial Detection in Food Samples

Foodborne illnesses can be infectious and dangerous, and most of them are caused by bacteria. Some common food-related bacteria species exist widely in nature and pose a serious threat to both humans and animals; they can cause poisoning, diseases, disabilities and even death. Rapid, reliable and cost-effective methods for bacterial detection are of paramount importance in food safety and environmental monitoring. Polymerase chain reaction (PCR), lateral flow immunochromatographic assay (LFIA) and electrochemical methods have been widely used in food safety and environmental monitoring. In this paper, the recent developments (2013-2023) covering PCR, LFIA and electrochemical methods for various bacterial species (Salmonella, Listeria, Campylobacter, Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli)), considering different food sample types, analytical performances and the reported limit of detection (LOD), are discussed. It was found that the bacteria species and food sample type contributed significantly to the analytical performance and LOD. Detection via LFIA has a higher average LOD (24 CFU/mL) than detection via electrochemical methods (12 CFU/mL) and PCR (6 CFU/mL). Salmonella and E. coli in the Pseudomonadota domain usually have low LODs. LODs are usually lower for detection in fish and eggs. Gold and iron nanoparticles were the most studied in the reported articles for LFIA, and average LODs were 26 CFU/mL and 12 CFU/mL, respectively. The electrochemical method revealed that the average LOD was highest for cyclic voltammetry (CV) at 18 CFU/mL, followed by electrochemical impedance spectroscopy (EIS) at 12 CFU/mL and differential pulse voltammetry (DPV) at 8 CFU/mL. LOD usually decreases when the sample number increases until it remains unchanged. Exponential relations (R2 > 0.95) between LODs of Listeria in milk via LFIA and via the electrochemical method with sample numbers have been obtained. Finally, the review discusses challenges and future perspectives (including the role of nanomaterials/advanced materials) to improve analytical performance for bacterial detection.

Fluorescence immunoassay for the targeted determination of trace Listeria monocytogenes based on immunomagnetic separation and CdZnTe quantum dot indication

Infections from invasive Listeria monocytogenes (L. monocytogenes) frequently occur in food and can cause high morbidity and death. Thus, the sensitive, specific, and rapid detection of L. monocytogenes is critical for ensuring food safety and public health. Herein, a fluorescence immunoassay for trace L. monocytogenes detection was designed based on guinea pig antibody-functionalized magnetic nanoparticles (Fe₃O₄ NPs/pAb1) and rabbit antibody-anchored CdZnTe quantum dots (CdZnTe QDs/pAb2). Because of the antibody-directed magnetic separation and long-wave fluorescent emission for CdZnTe QD indication, the constructed immunoassay strategy presented excellent anti-interference performance toward a biological matrix. The immunosensor exhibited a wide detection range of 1 to 10⁹ CFU mL^-1 for L. monocytogenes and a low limit of detection (LOD) of 1 CFU mL^-1, achieving an exceptionally sensitive detection of trace L. monocytogenes. Meanwhile, the immunosensor showed good specificity and had a short time-consumption of 60 min to realize the accurate determination of trace Listeria monocytogenes in spiked tap water and pasteurized milk samples.

Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review

Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. This review summarizes available biological fecal indicators focusing on host specificity, degree of association with fecal pollution, environmental persistence, and quantification methods in fecal pollution assessment. The development of practical tools is a crucial requirement for the implementation of mitigation strategies that may help confine the types of host-specific pathogens and determine the source control point, such as sourcing fecal wastes from point sources and nonpoint sources. Emerging multidisciplinary bacterial enumeration platforms are also discussed, including individual working mechanisms, applications, advantages, and limitations.

Rapid detection of total bacteria in foods using a poly-l-lysine-based lateral-flow assay

Food safety and freshness are evaluated according to microbiological load. To analyze this load rapidly, a poly-_l-lysine-based lateral-flow assay (PLFA) was developed. A total of 90 strains of bacteria that are often detected in spoiled foods, including Enterobacteriaceae, lactic acid bacteria, Pseudomonas, and Bacillus were detected using the PLFA. A positive signal was obtained when the bacterial concentration was ≥6 log₁₀ (cfu/test). A total of 36 fresh foods (meats, pastries, lettuces, cabbages, radishes, and sprouts) and corresponding spoiled foods were cultured for 0, 3, 6, and 9 h to investigate how many hours were required for microbial detection using PLFA. The higher the number of bacteria in a food, the shorter was the culture time required for PLFA-positive results to be obtained, so the distinction between fresh and spoiled food could be made based on the time taken for the culture to become PLFA-positive. The coefficient of determination of the least squares regression between the time to become PLFA-positive and the initial log₁₀ (cfu/g) bacterial count for the food was 0.9888. The test time for the PLFA, including pretreatment, was approximately 15-30 min. This novel method will enable the detection of total bacteria on the food processing site.