Related Experiment Video
Updated: Sep 17, 2026

Portable Paper-Based Immunoassay Combined with Smartphone Application for Colorimetric and Quantitative Detection of Dengue NS1 Antigen
Published on: January 26, 2024
A smartphone-integrated plasmonic biosensor for amplification-free detection of African swine fever virus
Sanjay Singh1,2, Haile Yancy3, Evangelyn Alocilja1,2
1Nano-Biosensors Lab, Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA. alocilja@msu.edu.
Abstract:
African Swine Fever Virus (ASFV) poses a catastrophic threat to global swine production, with recent outbreaks across Europe, Asia, and the Caribbean, significantly elevating the biosecurity risk to the United States' billion-dollar pork industry. Current diagnostic gold standards are laboratory-dependent and introduce critical delays in outbreak response. To address this gap, a plasmonic biosensor based on functionalized gold nanoparticles (GNPs) was developed for the rapid, amplification-free detection of ASFV. GNPs were surface-functionalized with 11-mercaptoundecanoic acid (MUDA) and combined in situ with ASFV-specific oligonucleotide probes targeting a conserved region of the p72 (B646L) gene. The detection mechanism relies on acid-induced aggregation: hybridization of target ASFV DNA to the probe generates a rigid duplex that shields the nanoparticles from acid-induced destabilization, maintaining a ruby-red color, whereas in the absence of target DNA the GNPs aggregate, producing a visible red-to-blue color shift. The optimized plasmonic biosensor demonstrated 100% analytical specificity, with no cross-reactivity against a panel of 19 non-target bacterial genomic DNA samples representative of the swine environment. Detection limits determined by the IUPAC 3σ criterion were 285 copies per reaction for Probe 1 and 402 copies per reaction for Probe 2, within the same order of magnitude as the qPCR reference assay run on the same dilution series (approximately 312 copies per reaction) under the experimental conditions used here. A smartphone-based Bio-Analytics App employing an RGB color-conversion algorithm served as a quantitative reader, yielding signal-to-noise ratios (S/N) that strongly correlated with benchtop spectrophotometric readings (A520/A620 ratio, R2 = 0.96) and achieved diagnostic concordance with qPCR binary calls. This platform offers a robust and low-cost (∼$2 per test), amplification-free approach to ASFV screening with potential for point-of-need deployment, subject to future validation in clinical specimens.

