Sandwich immunoassay based on antimicrobial peptide-mediated nanocomposite pair for determination of Escherichia coli O157:H7 using personal glucose meter as readout

Key steps for improving bacterial SERS signals in complex samples: Separation, recognition, detection, and analysis

Rapid and reliable detection of pathogenic bacteria is absolutely essential for research in environmental science, food quality, and medical diagnostics. Surface-enhanced Raman spectroscopy (SERS), as an emerging spectroscopic technique, has the advantages of high sensitivity, good selectivity, rapid detection speed, and portable operation, which has been broadly used in the detection of pathogenic bacteria in different kinds of complex samples. However, the SERS detection method is also challenging in dealing with the detection difficulties of bacterial samples in complex matrices, such as interference from complex matrices, confusion of similar bacteria, and complexity of data processing. Therefore, researchers have developed some technologies to assist in SERS detection of bacteria, including both the front-end process of obtaining bacterial sample data and the back-end data processing process. The review summarizes the key steps for improving bacterial SERS signals in complex samples: separation, recognition, detection, and analysis, highlighting the principles of each step and the key roles for SERS pathogenic bacteria analysis, and the interconnectivity between each step. In addition, the current challenges in the practical application of SERS technology and the development trends are discussed. The purpose of this review is to deepen researchers' understanding of the various stages of using SERS technology to detect bacteria in complex sample matrices, and help them find new breakthroughs in different stages to facilitate the detection and control of bacteria in complex samples.

pH-Triggered visual detection of Escherichia coli based on the co-assembly of bacitracin and thymolphthalein

A novel probe for bacteria was simply synthesized through the solvent-induced co-assembly of bacitracin (AMP) and thymolphthalein (TP) without complicated modification. Combining with aptamer-Fe3O4, AMP/TP nanoparticles were used for the colorimetric detection of Escherichia coli with good sensitivity through the NaOH-triggered blue color and a smartphone-based App.

Rapid detection of Salmonella in food matrices by photonic PCR based on the photothermal effect of Fe3O4

Salmonella causes most deaths from diarrheal disease worldwide. Therefore, Salmonella must be accurately and quickly detected, even in complex food matrices, which is difficult to achieve using conventional culture methods. Here we propose a novel photonic polymerase chain reaction (PCR) method based on ferroferric oxide (Fe3O4) for the detection of Salmonella typhimurium in complex samples. Owing to the great photothermal conversion performance of Fe3O4, rapid thermal cycling could be accomplished. Our optimized photonic PCR system specifically detected Salmonella typhimurium in complex food matrices within 50 min. Quantitative data showed a limit of detection up to 102 CFU/mL in food samples. This method is suitable for the detection of all pathogenic microorganisms and is universal.

Recent Advances in Personal Glucose Meter-Based Biosensors for Food Safety Hazard Detection

Food safety has emerged as a significant concern for global public health and sustainable development. The development of analytical tools capable of rapidly, conveniently, and sensitively detecting food safety hazards is imperative. Over the past few decades, personal glucose meters (PGMs), characterized by their rapid response, low cost, and high degree of commercialization, have served as portable signal output devices extensively utilized in the construction of biosensors. This paper provides a comprehensive overview of the mechanism underlying the construction of PGM-based biosensors, which consists of three fundamental components: recognition, signal transduction, and signal output. It also detailedly enumerates available recognition and signal transduction elements, and their modes of integration. Then, a multitude of instances is examined to present the latest advancements in the application of PGMs in food safety detection, including targets such as pathogenic bacteria, mycotoxins, agricultural and veterinary drug residues, heavy metal ions, and illegal additives. Finally, the challenges and prospects of PGM-based biosensors are highlighted, aiming to offer valuable references for the iterative refinement of detection techniques and provide a comprehensive framework and inspiration for further investigations.

Point-of-Care Diagnostic Devices for Detection of Escherichia coli O157:H7 Using Microfluidic Systems: A Focused Review

Bacterial infections represent a serious and global threat in modern medicine; thus, it is very important to rapidly detect pathogenic bacteria, such as Escherichia coli (E. coli) O157:H7. Once treatments are delayed after the commencement of symptoms, the patient's health quickly deteriorates. Hence, real-time detection and monitoring of infectious agents are highly critical in early diagnosis for correct treatment and safeguarding public health. To detect these pathogenic bacteria, many approaches have been applied by the biosensors community, for example, widely-used polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), culture-based method, and adenosine triphosphate (ATP) bioluminescence. However, these approaches have drawbacks, such as time-consumption, expensive equipment, and being labor-intensive, making it critical to develop ultra-sensitive and highly selective detection. The microfluidic platform based on surface plasmon resonance (SPR), electrochemical sensing, and rolling circle amplification (RCA) offers proper alternatives capable of supplementing the technological gap for pathogen detection. Note that the microfluidic biochip allows to develop rapid, sensitive, portable, and point-of-care (POC) diagnostic tools. This review focuses on recent studies regarding accurate and rapid detection of E. coli O157:H7, with an emphasis on POC methods and devices that complement microfluidic systems. We also examine the efficient whole-body detection by employing antimicrobial peptides (AMPs), which has attracted growing attention in many applications.

Personal Glucose Meters Coupled with Signal Amplification Technologies for Quantitative Detection of Non-Glucose Targets: Recent Progress and Challenges in Food Safety Hazards Analysis

Ensuring food safety is paramount worldwide. Developing effective detection methods to ensure food safety can be challenging owing to trace hazards, long detection time, and resource-poor sites, in addition to the matrix effects of food. Personal glucose meter (PGM), a classic point-of-care testing device, possesses unique application advantages, demonstrating promise in food safety. Currently, many studies have used PGM-based biosensors and signal amplification technologies to achieve sensitive and specific detection of food hazards. Signal amplification technologies have the potential to greatly improve the analytical performance and integration of PGMs with biosensors, which is crucial for solving the challenges associated with the use of PGMs for food safety analysis. This review introduces the basic detection principle of a PGM-based sensing strategy, which consists of three key factors: target recognition, signal transduction, and signal output. Representative studies of existing PGM-based sensing strategies combined with various signal amplification technologies (nanomaterial-loaded multienzyme labeling, nucleic acid reaction, DNAzyme catalysis, responsive nanomaterial encapsulation, and others) in the field of food safety detection are reviewed. Future perspectives and potential opportunities and challenges associated with PGMs in the field of food safety are discussed. Despite the need for complex sample preparation and the lack of standardization in the field, using PGMs in combination with signal amplification technology shows promise as a rapid and cost-effective method for food safety hazard analysis.

Nucleic acid amplification-based strategy to detect foodborne pathogens in milk: a review

Milk contaminated with trace amounts of foodborne pathogens can considerably threaten food safety and public health. Therefore, rapid and accurate detection techniques for foodborne pathogens in milk are essential. Nucleic acid amplification (NAA)-based strategies are widely used to detect foodborne pathogens in milk. This review article covers the mechanisms of the NAA-based detection of foodborne pathogens in milk, including polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), rolling circle amplification (RCA), and enzyme-free amplification, among others. Key factors affecting detection efficiency and the advantages and disadvantages of the above techniques are analyzed. Potential on-site detection tools based on NAA are outlined. We found that NAA-based strategies were effective in detecting foodborne pathogens in milk. Among them, PCR was the most reliable. LAMP showed high specificity, whereas RPA and RCA were most suitable for on-site and in-situ detection, respectively, and enzyme-free amplification was more economical. However, factors such as sample separation, nucleic acid target conversion, and signal transduction affected efficiency of NAA-based strategies. The lack of simple and effective sample separation methods to reduce the effect of milk matrices on detection efficiency was noteworthy. Further research should focus on simplifying, integrating, and miniaturizing microfluidic on-site detection platforms.

Electrochemical Affinity Assays/Sensors: Brief History and Current Status

The advent of electrochemical affinity assays and sensors evolved from pioneering efforts in the 1970s to broaden the field of analytes accessible to the selective and sensitive performance of electrochemical detection. The foundation of electrochemical affinity assays/sensors is the specific capture of an analyte by an affinity element and the subsequent transduction of this event into a measurable signal. This review briefly covers the early development of affinity assays and then focuses on advances in the past decade. During this time, progress on electroactive labels, including the use of nanoparticles, quantum dots, organic and organometallic redox compounds, and enzymes with amplification schemes, has led to significant improvements in sensitivity. The emergence of nanomaterials along with microfabrication and microfluidics technology enabled research pathways that couple the ease of use of electrochemical detection for the development of devices that are more user friendly, disposable, and employable, such as lab-on-a-chip, paper, and wearable sensors.

A sensitive biosensor for determination of pathogenic bacteria using aldehyde dehydrogenase signaling system

Aldehyde dehydrogenase (ALDH) was first developed as an enzymatic signaling system of a biosensor for sensitive point-of-care detection of pathogenic bacteria. ALDH and specific aptamers to Salmonella typhimurium (S. typhimurium), as organic components, were embedded in organic-inorganic nanocomposites as a biosensor signal label, integrating the functions of signal amplification and target recognition. The biosensing mechanism is based on the fact that ALDH can catalyze rapid oxidation of acetaldehyde into acetic acid, resulting in pH change with portable pH meter readout. The altered pH exhibited a linear relationship with the logarithm of S. typhimurium from 10² to 10⁸ CFU/mL and detection limit of 46 CFU/mL. Thus, the proposed biosensor has potential application in the diagnosis of pathogenic bacteria.