Development of electrochemical method to detect bacterial count, Listeria monocytogenes, and somatic cell count in raw milk

Recent Advances in Electrochemical Biosensors for the Detection of Foodborne Pathogens: Current Perspective and Challenges

Foodborne pathogens cause many diseases and significantly impact human health and the economy. Foodborne pathogens mainly include Salmonella spp., Escherichia coli, Staphylococcus aureus, Shigella spp., Campylobacter spp. and Listeria monocytogenes, which are present in agricultural products, dairy products, animal-derived foods and the environment. Various pathogens in many different types of food and water can cause potentially life-threatening diseases and develop resistance to various types of antibiotics. The harm of foodborne pathogens is increasing, necessitating effective and efficient methods for early monitoring and detection. Traditional methods, such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA) and culture plate, are time-consuming, labour-intensive and expensive and cannot satisfy the demands of rapid food testing. Therefore, new fast detection methods are urgently needed. Electrochemical biosensors provide consumer-friendly methods to quickly detect foodborne pathogens in food and the environment and achieve extensive accuracy and reproducible results. In this paper, by focusing on various mechanisms of electrochemical transducers, we present a comprehensive overview of electrochemical biosensors for the detection of foodborne pathogens. Furthermore, the review introduces the hazards of foodborne pathogens, risk analysis methods and measures of control. Finally, the review also emphasizes the recent research progress and solutions regarding the use of electrochemical biosensors to detect foodborne pathogens in food and the environment, evaluates limitations and challenges experienced during the development of biosensors to detect foodborne pathogens and discusses future possibilities.

Recent Advances in Microfluidics-Based Electrochemical Sensors for Foodborne Pathogen Detection

Using pathogen-infected food that can be unhygienic can result in severe diseases and an increase in mortality rate among humans. This may arise as a serious emergency problem if not appropriately restricted at this point of time. Thus, food science researchers are concerned with precaution, prevention, perception, and immunity to pathogenic bacteria. Expensive, elongated assessment time and the need for skilled personnel are some of the shortcomings of the existing conventional methods. Developing and investigating a rapid, low-cost, handy, miniature, and effective detection technology for pathogens is indispensable. In recent times, there has been a significant scope of interest for microfluidics-based three-electrode potentiostat sensing platforms, which have been extensively used for sustainable food safety exploration because of their progressively high selectivity and sensitivity. Meticulously, scholars have made noteworthy revolutions in signal enrichment tactics, measurable devices, and portable tools, which can be used as an allusion to food safety investigation. Additionally, a device for this purpose must incorporate simplistic working conditions, automation, and miniaturization. In order to meet the critical needs of food safety for on-site detection of pathogens, point-of-care testing (POCT) has to be introduced and integrated with microfluidic technology and electrochemical biosensors. This review critically discusses the recent literature, classification, difficulties, applications, and future directions of microfluidics-based electrochemical sensors for screening and detecting foodborne pathogens.

Lactoperoxidase potential in diagnosing subclinical mastitis in cows via image processing

This report describes how image processing harnessed to multivariate analysis techniques can be used as a bio-analytical tool for mastitis screening in cows using milk samples collected from 48 animals (32 from Jersey, 7 from Gir, and 9 from Guzerat cow breeds), totalizing a dataset of 144 sequential images was collected and analyzed. In this context, this methodology was developed based on the lactoperoxidase activity to assess mastitis using recorded images of a cuvette during a simple experiment and subsequent image treatments with an R statistics platform. The color of the sample changed from white to brown upon its exposure to reagents, which is a consequence of lactoperoxidase enzymatic reaction. Data analysis was performed to extract the channels from the RGB (Red-Green-Blue) color system, where the resulting dataset was evaluated with Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Second-Order Regression (SO). Interesting results in terms of enzymatic activity correlation (R² = 0.96 and R² = 0.98 by MLR and SO, respectively) and of somatic cell count (R² = 0.97 and R² = 0.99 by MLR and SO, respectively), important mastitis indicators, were obtained using this simple method. Additionally, potential advantages can be accessed such as quality control of the dairy chain, easier bovine mastitis prognosis, lower cost, analytical frequency, and could serve as an evaluative parameter to verify the health of the mammary gland.

Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection

We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min. Machine learning and robotized bioanalytical platforms require the principles such as hydrogel-based actuators for fast and easy analysis of bioactive analytes. Bacteria are fragile and environmentally sensitive microorganisms that require a special environment to support their lifecycles during analytical tests. Here, we develop a bio-electrochemical platform based on the soft hydrogel/eutectic gallium-indium alloy interface for the detection of Streptococcus thermophilus and Bacillus coagulans bacteria in various mediums. The soft hydrogel-based device is capable to support bacteria' viability during detection time. Current-voltage data are used for multilayer perceptron algorithm training. The multilayer perceptron model is capable of detecting bacterial concentrations in the 10⁴ to 10⁸ cfu/mL range of the culture medium or in the dairy products with high accuracy (94%). Such a fast and easy biodetection is extremely important for food and agriculture industries and biomedical and environmental science.

Recent advances in electrochemical strategies for bacteria detection

Introduction: Bacterial infections have always been a major threat to public health and humans' life, and fast detection of bacteria in various samples is significant to provide early and effective treatments. Cell-culture protocols, as well-established methods, involve labor-intensive and complicated preparation steps. For overcoming this drawback, electrochemical methods may provide promising alternative tools for fast and reliable detection of bacterial infections. Methods: Therefore, this review study was done to present an overview of different electrochemical strategy based on recognition elements for detection of bacteria in the studies published during 2015-2020. For this purpose, many references in the field were reviewed, and the review covered several issues, including (a) enzymes, (b) receptors, (c) antimicrobial peptides, (d) lectins, (e) redox-active metabolites, (f) aptamer, (g) bacteriophage, (h) antibody, and (i) molecularly imprinted polymers. Results: Different analytical methods have developed are used to bacteria detection. However, most of these methods are highly time, and cost consuming, requiring trained personnel to perform the analysis. Among of these methods, electrochemical based methods are well accepted powerful tools for the detection of various analytes due to the inherent properties. Electrochemical sensors with different recognition elements can be used to design diagnostic system for bacterial infections. Recent studies have shown that electrochemical assay can provide promising reliable method for detection of bacteria. Conclusion: In general, the field of bacterial detection by electrochemical sensors is continuously growing. It is believed that this field will focus on portable devices for detection of bacteria based on electrochemical methods. Development of these devices requires close collaboration of various disciplines, such as biology, electrochemistry, and biomaterial engineering.

A Novel Photoelectrochemical Aptamer Sensor Based on CdTe Quantum Dots Enhancement and Exonuclease I-Assisted Signal Amplification for Listeria monocytogenes Detection

To achieve the rapid detection of Listeria monocytogenes, this study used aptamers for the original identification and built a photoelectrochemical aptamer sensor using exonuclease-assisted amplification. Tungsten trioxide (WO3) was used as a photosensitive material, was modified with gold nanoparticles to immobilize complementary DNA, and amplified the signal by means of the sensitization effect of CdTe quantum dots and the shearing effect of Exonuclease I (Exo I) to achieve high-sensitivity detection. This strategy had a detection limit of 45 CFU/mL in the concentration range of 1.3 × 101-1.3 × 107 CFU/mL. The construction strategy provides a new way to detect Listeria monocytogenes.

PANI/TiO2 nanocomposite-based chemiresistive gas sensor for the detection of E. Coli bacteria

In the modern pace of the world, food safety is a major concern. In this work, a simple chemiresistive type gas sensor was fabricated to detect Escherichia Coli (E. coli) bacteria. Polyaniline (PANI) films were deposited on the indium tin oxide substrate by an electrochemical deposition method. TiO2 nanoparticles were synthesised by facile hydrothermal method. PANI films were modified using hydrothermally prepared TiO2 nanoparticles by a spin coating method. X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR) and ultraviolet-visible spectrophotometer techniques were used to characterise the PANI/TiO2 nanocomposites. The peaks obtained in the XRD pattern confirmed the anatase phase of TiO2 nanoparticles. FESEM analysis showed the nanofibrous structure of the nanocomposite. The FTIR characteristic peaks confirmed the formation of the nanocomposite. The electrical resistance of the sensors was evaluated as a function of the bacterial concentration. The PT2 (TiO2 coated 5 times on PANI) in comparison with PT1 (TiO2 coated 3 times on PANI) exhibited good sensitivity to the gas molecules at room temperature. The p-n junction at PANI/TiO2 interface improved the physical adsorption of gas molecules. Since no specific antibodies or receptors are used, the sensor has the potential for adaptation to real-life applications. Thus low cost, real-time, portable, reusable and sensitive bacteria sensors were fabricated and tested.

Quantitatively determining the total bacterial count of raw goat milk using dielectric spectra

The objective of this study was to evaluate dielectric spectra as a means of quantitatively determining total bacterial count (TBC) of raw goat milk. The dielectric spectra, including dielectric constant (ε') spectra and dielectric loss factor (ε″) spectra, and TBC of 154 raw goat milk samples were measured using network analyzer and plate count methods, respectively. Owing to the poor linear relationship between TBC in logarithm and permittivities at a single frequency, chemometrics was used to reduce noise, identify outliers, select effective variables, and divide sample sets. Several linear models, such as multiple linear regression, ridge regression, and least absolute shrinkage and selection operator, were established to determine TBC based on the effective spectra of ε', ε″, and their combination (ε'+ε″). The results indicated that the models built using the spectra of ε'+ε″ and ε' had excellent TBC prediction performance. The best model was multiple linear regression based on ε'+ε″ spectra with the residual predictive deviation of 3.26. This study shows that the dielectric spectra had great potential to quantitatively and rapidly determine TBC of raw milk.