An AI-assisted hyperbranched RCA-based colorimetric biosensing platform for ultrasensitive detection of BPA

Bisphenol A (BPA), a common industrial chemical and endocrine disruptor, poses serious health risks, highlighting the need for sensitive detection methods. We developed an artificial intelligence-assisted colorimetric biosensor integrating aptamer-target recognition-triggered hyperbranched rolling circle amplification (HRCA) with DNA-functionalized gold nanoparticles (AuNPs-DP) as visual probes. BPA binding induces aptamer conformational switching, initiating HRCA via Phi29 DNA polymerase to produce abundant DNA products that cause AuNPs-DP aggregation and distinct colorimetric changes. This enables direct visual detection with minimal background interference and high specificity, achieving an ultra-low detection limit of 0.575 pg mL^-1. Colorimetric images analyzed using a ResNet-18 model allow rapid and accurate BPA quantification both locally and remotely. The proposed biosensor offers low cost, easy operation, and exceptional sensitivity, demonstrating strong potential for on-site water safety monitoring and practical biosensing applications.