A label-free electrochemical biosensor is presented for the detection of miRNA-223, a host immune-derived biomarker upregulated in early mastitis. The biosensor consists of porous anodic alumina (pAAO) membranes featuring high-aspect-ratio porous structure, functionalized with ssDNA probes. This nanochannel-based design increases surface area for probe immobilization and enhances sensitivity by amplifying hybridization-induced changes in ionic transport. Upon hybridization with miRNA-223 to the immobilized ssDNA probe, partial pore blockage impedes the diffusion of a redox probe added to the measuring solution. This change in diffusion is quantified via square wave voltammetry. The biosensor enables direct miRNA detection in raw milk, eliminating the need for RNA extraction or amplification. The biosensor was systematically optimized for pore diameter, probe concentration, and blocking conditions, and demonstrated consistent signal suppression in the presence of synthetic miRNA-223 across a dynamic range from 0.1 pM to 1 nM in both phosphate buffer and 0.1% raw milk. Application to milk collected from clinically classified cows showed clear discrimination between healthy and subclinical samples, with an area under the receiver operating characteristic curve of 0.96. Statistical analysis across 30 replicate sensor readings confirmed significant group-level discrimination (p = 0.016, Mann–Whitney U test). The biosensor’s high sensitivity and specificity are attributed to its diffusion-limited pore-based architecture and stable surface functionalization, which together enable selective and reproducible hybridization responses. Its demonstrated compatibility with raw milk furthers its robustness and analytical reliability under real sample conditions. The ability to detect early-stage, immune-derived miRNAs in minimally processed milk (0.1% v/v raw milk in phosphate buffer) supports the deployment of this biosensor in on-farm, real-time surveillance systems. By eliminating reliance on pathogen detection and enabling pre-symptomatic classification, this work aims to contribute to improved livestock health management, antimicrobial stewardship, and broader one-health objectives.
Verma et al. (Wed,) studied this question.