Development of an RPA-CRISPR/Cas12a-based rapid visual detection method for two insecticide resistance-associated mutations in Aphis gossypii: A302S in the ace1 gene and M918L in the para gene.

Authors

Rujing Kang, Yucheng Qian, Yuanchi Zuo, Ren Li, Lei Zhang

Published in

Pesticide biochemistry and physiology. Volume 223. Pages 107303. Epub Aug 10, 2026.

Abstract

The resistance of Aphis gossypii to pyrethroids and organophosphate/carbamate insecticides has become increasingly severe. The para M918L and ace1 A302S target-site mutations are the key mechanisms conferring resistance to these two types of insecticides, respectively. However, rapid and field-deployable methods for detecting these mutations are still lacking. In this study, the genotype and allele frequencies of eight field populations collected in 2023 were investigated, and a rapid visual detection method based on RPA-CRISPR/Cas12a was developed. By optimizing the concentration of the reaction components, specific recognition of both mutations was achieved. The optimized assay could be completed within 1 h under a single-temperature condition of 37 °C, with fluorescence signals directly visualized using a portable 440-460 nm blue-light illuminator without PCR thermocyclers, fluorescence readers or sequencing platforms. Validation using the tested field samples showed complete concordance with Sanger sequencing. In addition, Sanger sequencing further showed that no homozygous susceptible genotype was detected at the para M918 locus across all populations, whereas the 302S allele frequency at the ace1 A302S locus exhibited significant geographic variation, ranging from 0% to 100%. The RPA-CRISPR-based visual detection method developed in this study is rapid, accurate, and does not require expensive instrumentation. Together with previously developed neonicotinoid resistance detection techniques, it forms a comprehensive monitoring system for multiple resistance in A. gossypii, providing a practical tool for rapid field diagnosis and more informed insecticide selection.

PMID:
42697672
Bibliographic data and abstract were imported from PubMed on 05 Sep 2026.

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