Development of duplex PCR-ELISA for simultaneous detection of Salmonella spp. and Escherichia coli O157: H7 in food

Pathogen detection via inductively coupled plasma mass spectrometry analysis with nanoparticles

Infections caused by viruses and bacteria pose a significant threat to global public health, emphasizing the critical importance of timely and precise detection methods. Inductively coupled plasma mass spectrometry (ICP-MS), a contemporary approach for pathogen detection, offers distinct advantages such as high sensitivity, a wide linear range, and multi-index capabilities. This review elucidates the underexplored application of ICP-MS in conjunction with functional nanoparticles (NPs) for the identification of viruses and bacteria. The review commences with an elucidation of the underlying principles, procedures, target pathogens, and NP requirements for this innovative approach. Subsequently, a thorough analysis of the advantages and limitations associated with these techniques is provided. Furthermore, the review delves into a comprehensive examination of the challenges encountered when utilizing NPs and ICP-MS for pathogen detection, culminating in a forward-looking assessment of the potential pathways for advancement in this domain. Thus, this review contributes novel perspectives to the field of pathogen detection in biomedicine by showcasing the promising synergy of ICP-MS and NPs.

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.

Ultra-sensitive fluorescent biosensor for multiple bacteria detection based on CDs/QDs@ZIF-8 and microfluidic fluidized bed

An ultra-sensitive fluorescent biosensor based on CDs/QDs@ZIF-8 and microfluidic fluidized bed was developed for rapid and ultra-sensitive detection of multiple target bacteria. The zeolitic imidazolate frameworks (ZIF-8) act as the carrier to encapsulate three kinds of fluorescence signal molecules from the CDs/QDs@ZIF-8 signal amplification system. Besides, three kinds of target pathogenic bacteria were automatically, continuously, and circularly captured by the magnetic nanoparticles (MNPs) in the microfluidic fluidized bed. The neutral Na2EDTA solution was the first time reported to not only dissolve the ZIF-8 frameworks from the MNPs-bacteria-CDs/QDs@ZIF-8 sandwich complexes, but also release the CDs/QDs from sandwich complexes with no loss of fluorescence signal. Due to the advantages of signal amplification and automated sample pretreatment, the proposed fluorescent biosensor can simultaneously detect Escherichia coli O157:H7, Salmonella paratyphi A, and Salmonella paratyphi B as low as 101 CFU/mL within 1.5 h, respectively. The mean recovery in spiked milk samples can reach 99.18%, verifying the applicability of this biosensor in detecting multiple bacteria in real samples.

Advanced diagnostic methods for identification of bacterial foodborne pathogens: contemporary and upcoming challenges

It is a public health imperative to have safe food and water across the population. Foodborne infections are one of the primary causes of sickness and mortality in both developed and developing countries. An estimated 100 million foodborne diseases and 120 000 foodborne illness-related fatalities occur each year in India. Several factors affect foodborne illness, such as improper farming methods, poor sanitary and hygienic conditions at all levels of the food supply chain, the lack of preventative measures in the food processing industry, the misuse of food additives, as well as improper storage and handling. In addition, chemical and microbiological combinations also play a key role in disease development. But recent disease outbreaks indicated that microbial pathogens played a major role in the development of foodborne diseases. Therefore, prompt, rapid, and accurate detection of high-risk food pathogens is extremely vital to warrant the safety of the food items. Conventional approaches for identifying foodborne pathogens are labor-intensive and cumbersome. As a result, a range of technologies for the rapid detection of foodborne bacterial pathogens have been developed. Presently, many methods are available for the instantaneous detection, identification, and monitoring of foodborne pathogens, such as nucleic acid-based methods, biosensor-based methods, and immunological-based methods. The goal of this review is to provide a complete evaluation of several existing and emerging strategies for detecting food-borne pathogens. Furthermore, this review outlines innovative methodologies and their uses in food testing, along with their existing limits and future possibilities in the detection of live pathogens in food.

Recent trends and developments of PCR-based methods for the detection of food-borne Salmonella bacteria and Norovirus

In recent years, rapid detection methods such as polymerase chain reaction (PCR) and quantitative real-time PCR (qPCR) have been continuously developed to improve the detection of food-borne pathogens in food samples. The recent developments of PCR and qPCR in the detection and identification of these food-borne pathogens are described and elaborated throughout this review. Specifically, further developments and improvements of qPCR are discussed in detecting Salmonella and norovirus. Promising advances in these molecular detection methods have been widely used to prevent human food-borne illnesses and death caused by the food-borne pathogens. In addition, this review presents the limitations and challenges of the detection methods which include conventional culture method and conventional PCR method in detecting Salmonella and norovirus. Furthermore, several advances of qPCR such as viability PCR (vPCR) and digital PCR (dPCR) have been discussed in the detection of Salmonella and norovirus. Good practice of analysis of the food-borne pathogens and other contaminants in the food industry as well as the advancement of molecular detection methods will help improve and ensure food safety and food quality.

A quantitative prevalence of Escherichia coliO157 in different food samples using real-time qPCR method

Escherichia coli serogroup O157 is the main causative agent of several intestinal and extra-intestinal foodborne diseases in humans through consumption of low-dose contaminated foods such as milk, beef, and vegetables. To date, studies regarding the quantitative prevalence of E. coli O157 in foods are so limited. Therefore, this study aimed to evaluate the quantitative prevalence rate of E. coli serogroup O157 in raw milk (n = 144), vegetable salad (n = 174), and minced beef samples (n = 108) using the real-time qPCR SYBR green melting curve method targeting the rfbA gene. First, we evaluated the method and found a sensitive and specific qPCR assay with 1 log of CFU/ml detection limit to detect E. coli O157 (Tm = 80.3 ± 0.1°C). About 2.77%, 10.18%, and 9.19% of raw milk, minced beef, and vegetable salad samples, respectively, were contaminated with E. coli O157. Minced beef and vegetable salad samples were significantly more contaminated than raw milk samples. Population average of E. coli O157 in raw milk, minced beef, and vegetable salad samples were 2.22 ± 0.57, 3.30 ± 0.40, and 1.65 ± 0.44 log CFU/ml or gr, respectively. Significantly higher levels of population of E. coli O157 were observed in minced beef samples. Minced beef can be regarded as the main food in the transmission of this foodborne pathogen. Routine quantitative rapid monitoring is strongly suggested to be carried out to prevent foodborne diseases caused by E. coli O157.

Colorimetric method for Salmonella spp. detection based on peroxidase-like activity of Cu(II)-rGO nanoparticles and PCR

Development of a rapid and sensitive method for Salmonella spp. detection is of great importance for ensuring food product safety due to its low infective dose. In this study, a colorimetric method based on the peroxidase-like activity of Cu(II)-modified reduced graphene oxide nanoparticles (Cu²⁺-rGO NPs) and PCR was successfully developed to detect Salmonella spp. in milk. Under optimal conditions, the developed colorimetric method exhibited high sensitivity and strong specificity for Salmonella spp. detection. The limit of detection was 0.51 CFU/mL with a linear range from 1.93 × 10¹ to 1.93 × 10⁵ CFU/mL. A specificity study demonstrated that this method can specifically distinguish Salmonella typhimurium and Salmonella enteritidis from other foodborne pathogens. The application of the proposed method for milk sample detection was also validated, and the recovery rates of S. typhimurium in spiked milk sample ranged from 102.84% to 112.25%. This colorimetric sensor exhibits enormous potential for highly sensitive detection of bacteria in milk sample.

Development of Metal Nanoparticle-immobilized Microplate for High-throughput and Highly Sensitive Fluorescence Analysis

Enzyme-linked immunosorbent assay (ELISA) is a widespread analytical biochemistry assay. In this work, a direct ELISA method using a metallic nanoparticle (NP)-immobilized 96-well plate was developed for high-throughput, highly sensitive fluorescence analysis. Immobilization of metallic NPs on a 96-well plate effectively amplified fluorescence signals of the assay. The silver (Ag) NP-immobilized plate showed the best fluorescence enhancement effect of all the metal-immobilized plates tested. We used the Ag NP-immobilized plate to detect biomolecules and bacteria and found that both the fluorescence intensity and the limit of detection (LOD) were strongly enhanced by more than 100 times compared with those of the unmodified 96-well plates. Quantitative and qualitative considerations for target bacteria regarding the impact of autofluorescence on detection were successfully obtained for several strains. Our results demonstrate the potential of applying Ag NPs for enhancing the efficiency of direct and indirect ELISA assays.

Rapid analysis of Escherichia coli O157:H7 using isothermal recombinase polymerase amplification combined with triple-labeled nucleotide probes

Rapid analytical methods are urgently needed to evaluate Escherichia coli (E. coli) O157:H7 in food. In this work, a novel recombinase polymerase amplification (RPA)-based lateral flow dipstick (LFD) method was developed to detect E. coli. Briefly, suitable primers and probes were designed and screened. Then, RPA reaction parameters, including volume, time, and temperature, were optimized. The specificity and sensitivity of RPA-LFD were analyzed, and a contaminated milk sample was used to test the detection performance of the proposed method. The optimal RPA reaction conditions included a minimum volume of 10 μL, incubation time of 10 min, temperature range of 39-42 °C, the primer pair EOF4/EOR3, and the probe EOProb. RPA-LFD was highly sensitive, it could detect as little as 1 fg of the genomic DNA of E. coli O157:H7, and 19 nontarget DNA of foodborne bacteria did not yield amplification products. Finally, the limit of detection of RPA-LFD for E. coli O157:H7 in artificially contaminated raw milk was 4.4 CFU/mL. In summary, the RPA-LFD assay developed in this study is an effective tool for the rapid investigation of E. coli O157:H7 contamination in raw milk samples.

Instrument-Free and Visual Detection of Salmonella Based on Magnetic Nanoparticles and an Antibody Probe Immunosensor

Salmonella, a common foodborne pathogen, causes many cases of foodborne illness and poses a threat to public health worldwide. Immunological detection systems can be combined with nanoparticles to develop sensitive and portable detection technologies for timely screening of Salmonella infections. Here, we developed an antibody-probe-based immuno-N-hydroxysuccinimide (NHS) bead (AIB) system to detect Salmonella. After adding the antibody probe, Salmonella accumulated in the samples on the surfaces of the immuno-NHS beads (INBs), forming a sandwich structure (INB–Salmonella–probes). We demonstrated the utility of our AIB diagnostic system for detecting Salmonella in water, milk, and eggs, with a sensitivity of 9 CFU mL⁻¹ in less than 50 min. The AIB diagnostic system exhibits highly specific detection and no cross-reaction with other similar microbial strains. With no specialized equipment or technical requirements, the AIB diagnostic method can be used for visual, rapid, and point-of-care detection of Salmonella.