This platform combines DNA nanoarchitectures with metal-tannic acid for detecting low-abundance mutations, suggesting advancements in agricultural monitoring.
Rapid and on-site identification of pesticide-resistant genes (PRGs), especially low-abundance single-nucleotide mutations (SNMs) concealed within wild-type sequences, is vital for precision agriculture. However, existing bioassays face challenges in achieving sufficient specificity to distinguish mutations while maintaining sensitivity to detect mutant alleles at 0.1% frequency and multiplexing capability. Here, we report an ultrasensitive, multimodal platform that couples programmable DNA nanoarchitectures (DNAarch) with metal-tannic acid (MTA; M = Co, Fe, Mn) nanospheres, delivering instant visual readouts and high-fidelity photoelectrochemical (PEC) qualification. In the MTA-RCA@DNAarch construct, MTA nanospheres bind strongly to ultralong single-stranded rolling circle amplification (ssRCA) product-engineered DNAarch, imparting adhesion, pH-responsiveness, and photothermal/colorimetric signatures. Using three SNMs in the ryanodine-receptor gene of Plutella xylostella as models, target recognition triggers an RCA reaction, followed by selective MTA binding to the corresponding ssRCA amplicons, enabling on-site mutation screening via photothermal and colorimetric shifts. Under acidic conditions, the release of Co2+/Fe2+/Mn2+ modulates the photoelectrode surface charge, boosting PEC signals for quantitative analysis. This assay achieves attomolar detection limits and discriminates SNMs present just at 0.01% within a wild-type sequence, while supporting multiplex operation. Field-sample validation confirms its robustness, positioning this visual/PEC multimodal platform as a powerful, real-time tool for monitoring PRG evolution in agricultural ecosystems.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: