Applications of Nanotechnology in Sensor-Based Detection of Foodborne Pathogens.

The intake of microbial-contaminated food poses severe health issues due to the outbreaks of stern food-borne diseases. Therefore, there is a need for precise detection and identification of pathogenic microbes and toxins in food to prevent these concerns. Thus, understanding the concept of biosensing has enabled researchers to develop nanobiosensors with different nanomaterials and composites to improve the sensitivity as well as the specificity of pathogen detection. The application of nanomaterials has enabled researchers to use advanced technologies in biosensors for the transfer of signals to enhance their efficiency and sensitivity. Nanomaterials like carbon nanotubes, magnetic and gold, dendrimers, graphene nanomaterials and quantum dots are predominantly used for developing biosensors with improved specificity and sensitivity of detection due to their exclusive chemical, magnetic, mechanical, optical and physical properties. All nanoparticles and new composites used in biosensors need to be classified and categorized for their enhanced performance, quick detection, and unobtrusive and effective use in foodborne analysis. Hence, this review intends to summarize the different sensing methods used in foodborne pathogen detection, their design, working principle and advances in sensing systems.

PlcA-based nanofabricated electrochemical DNA biosensor for the detection of Listeria monocytogenes in raw milk samples.

The electrochemical DNA biosensor has been developed for the detection of Listeria monocytogenes in raw milk samples. The electrochemical studies of the developed biosensor was recorded by cyclic voltammetry (CV) and electrochemical impedance (EI) using methylene blue (MB) and potassium ferricyanide K3Fe(CN)- 6 as redox indicators. The selectivity of the developed biosensor was demonstrated using complementary and mismatch oligonucleotide sequences. The sensitivity (S) of the developed sensor was recorded as 3461 (µA/cm2)/ng and limit of detection (LOD) was found to be 82 fg/6 µl with the regression coefficient (R 2) 0.941 using CV. The sensor was characterized by field emission scanning electron microscopy (FE-SEM). The electrode was found to be stable for six months, with only 10% loss in the initial CV current.

Rapid detection of Salmonella enterica in raw milk samples using Stn gene-based biosensor.

In this study, a DNA-based nanosensor using specific NH2 labeled single standard probe was developed against stn gene of Salmonella enterica in milk samples. The single-stranded DNA probe was immobilized on carboxylated multiwalled carbon nanotube and gold nanoparticle (c-MWCNT/AuNP) electrode using 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC): N-hydroxy succinimide-based cross-linking chemistry. Electrochemical characterization was performed using cyclic voltammetry (CV) and Differential Pulse Voltammetry (DPV) techniques. The electrode surface at each step of fabrication was characterized using scanning electron microscopy. The sensitivity and lower limit of detection were found to be 728.42 (µA/cm2)/ng and 1.8 pg/6 µl (0.3 pg/ml), respectively, with regression coefficient (R 2) of 0.843 using DPV. The sensor was further validated using raw and artificial milk samples, and results were compared with conventional methods of detection. The developed sensor was found to be highly sensitive and stable up to 6 months, with only 10% loss of initial peak current in CV analysis on storage at 4 °C.