Work

A Sample-to-Detection (S2D) Nano-Biosensing System to Rapidly Detect Salmonella in Poultry Processing Samples

Year: 2026

Type: article

Abstract: • There is an urgent need for rapid Salmonella monitoring systems in poultry processing plants to complement the lengthy standard detection methods and aid in decision-making. • This study presents a sample-to-detection system that utilizes magnetic nanoparticles and gold nanoparticles to detect Salmonella directly from poultry rinsate, carcass swab, and ground meat. • The detection can be achieved within four hours from sample processing to detection, without the need for a DNA extraction kit and without amplifying DNA. • Results of the nano-biosensing system are validated against the culture method and PCR. Salmonella is one of the most infectious foodborne pathogens, often associated with poultry. The speed of current detection methods is inadequate to address the growing global demand for poultry product safety. In this study, a sample-to-detection (S2D) nano-biosensing system was developed using glycan-coated magnetic nanoparticles (MNP) to concentrate cells from poultry processing plant samples, and gold nanoparticles (GNP) to detect Salmonella genomic DNA. More colonies were observed after MNP-aided preparation of poultry swabs, rinsate, and ground poultry meat samples, indicating a successful Salmonella concentration. The GNP-based DNA detection was selective towards the invA gene of Salmonella , with a detection limit of 2.5 ng/µL of dsDNA, translating to detecting 10 3 CFU/mL in the samples. The results of the S2D system were comparable with those of culture- and PCR-based detection methods, which served as standards. The S2D analysis time was less than four hours, significantly shorter than conventional methods. This study demonstrates the potential of the S2D system as a rapid screening tool to complement standard procedures for timely foodborne pathogen monitoring in poultry processing plants, leading to the protection of public health.

Source: Journal of Food Protection

DOI: 10.1016/j.jfp.2026.100712

Authors: Anthony James Franco, Woubit Abebe, Tina Conklin, Roger Stearns, Mollie Woods, Evangelyn Alocilja

Institutions: Michigan State University, Tuskegee University

Language: English

Topic: Biosensors and Analytical Detection

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Zero hunger, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,300