Multi-technique characterization of gold nanoparticle-based DNA biosensor with smartphone-enabled photometry for accelerated detection of Campylobacter jejuni

Campylobacter is one of the most infectious foodborne pathogens, often associated with consuming contaminated poultry products. Many Campylobacter infections are not reported until the symptoms become severe, making it necessary to detect them rapidly in food production systems as part of a preventative intervention strategy. In this study, a gold nanoparticle (GNP)-based DNA biosensor that utilizes digital photometric signals from smartphone images was developed to rapidly detect Campylobacter jejuni in drainage water and poultry rinse samples. Spectrophotometric measurements, hydrodynamic size, zeta potential, and dark-field microscopy confirm that hybrids were successfully formed between GNP, oligonucleotide probe, and C. jejuni DNA using an in-situ approach. Triggering GNP aggregation upon hybridization, the nano-biosensor signals obtained through smartphone-enabled digital photometry were strongly correlated with spectrophotometry. Based on the smartphone-enabled signal, the nano-biosensor demonstrated a high degree of selectivity for C. jejuni and detected 103 and 106 colony-forming units (CFU)/mL in unenriched drainage water and poultry rinse samples, respectively. This work demonstrates a GNP-based DNA biosensor employing cadF-targeted hybridization and smartphone-enabled digital photometry for the detection of Campylobacter jejuni in real samples. Diffusion-limited aggregation of unhybridized GNPs yields distinct optical responses, enabling the detection of target DNA in drainage water and poultry rinse. These findings provide a foundation for future validation studies in samples critical to monitoring foodborne pathogens across various food production and processing systems. Moreover, they highlight the potential of the smartphone-aided nano-biosensing system as a cost-effective, field-deployable means of pathogen surveillance.

Authors

Institutions

Publication Details

Journal
Journal of Biological Engineering
Published
2026-04-11
DOI
https://doi.org/10.1186/s13036-026-00677-2
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-technique characterization of gold nanoparticle-based DNA biosensor with smartphone-enabled photometry for accelerated detection of Campylobacter jejuni

Mollie Woods, Anthony James DM. Franco, Tina Conklin, Woubit Abebe et al.
Journal of Biological Engineering
Biosensors and Analytical Detection
article

Multi-technique characterization of gold nanoparticle-based DNA biosensor with smartphone-enabled photometry for accelerated detection of Campylobacter jejuni

Mollie Woods, Anthony James DM. Franco, Tina Conklin, Woubit Abebe, Roger Stearns, Evangelyn Alocilja, Finnian James
article en

Abstract

Campylobacter is one of the most infectious foodborne pathogens, often associated with consuming contaminated poultry products. Many Campylobacter infections are not reported until the symptoms become severe, making it necessary to detect them rapidly in food production systems as part of a preventative intervention strategy. In this study, a gold nanoparticle (GNP)-based DNA biosensor that utilizes digital photometric signals from smartphone images was developed to rapidly detect Campylobacter jejuni in drainage water and poultry rinse samples. Spectrophotometric measurements, hydrodynamic size, zeta potential, and dark-field microscopy confirm that hybrids were successfully formed between GNP, oligonucleotide probe, and C. jejuni DNA using an in-situ approach. Triggering GNP aggregation upon hybridization, the nano-biosensor signals obtained through smartphone-enabled digital photometry were strongly correlated with spectrophotometry. Based on the smartphone-enabled signal, the nano-biosensor demonstrated a high degree of selectivity for C. jejuni and detected 103 and 106 colony-forming units (CFU)/mL in unenriched drainage water and poultry rinse samples, respectively. This work demonstrates a GNP-based DNA biosensor employing cadF-targeted hybridization and smartphone-enabled digital photometry for the detection of Campylobacter jejuni in real samples. Diffusion-limited aggregation of unhybridized GNPs yields distinct optical responses, enabling the detection of target DNA in drainage water and poultry rinse. These findings provide a foundation for future validation studies in samples critical to monitoring foodborne pathogens across various food production and processing systems. Moreover, they highlight the potential of the smartphone-aided nano-biosensing system as a cost-effective, field-deployable means of pathogen surveillance.

Journal of Biological Engineering
Orthopaedic Associates of Michigan (US), Poultry Research Institute (CN), Tuskegee University (US), Michigan State University (US)
Michigan Department of Agriculture and Rural Development, National Institute of Food and Agriculture
Zero hunger
Openalex Percentile: Top 23%
Biosensors and Analytical Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.