Digital recombinase polymerase amplification chip based on asymmetric contact angle composite interface

Abstract

Background

Digital recombinase polymerase amplification (dRPA) is an effective tool for the absolute quantification of nucleic acids and the detection of rare mutations. Due to the high viscosity or other physical properties of the reagent, this can compromise the accuracy and reproducibility of detection results, which limits the broader adoption and practical application of this technology. In this study, we developed an asymmetric contact angle digital isothermal detection (ACA-DID) chip and optimized the ACA-DID chip structure to achieve rapid digital recombinase polymerase amplification.

Result

We designed with a pressure-driven and highly asymmetric contact angle composite interface to enable robust digital RPA. The addition of surfactants to the PDMS creates an asymmetric contact angle between the upper and lower surfaces of the fluid channel, improving reagent flow and facilitating entry into microwells. This design addresses the challenges posed by high-viscosity reagents, which typically complicate effective digital discretization and lead to fluorescence signal aggregation. By diluting specific components of the RPA reagent, we improved the uniformity of amplification and effectively reduced signal aggregation. The hydrophobic surface of results strong adsorption to biological macromolecules, such as nucleic acids and proteins, which will decrease the efficiency of dRPA amplification. To achieve efficient amplification of reagents in the microchamber, this work uses a surface modification strategy of PDMS doped surfactant, which eliminates the issue of PDMS materials hindering dRPA amplification efficiency.

Significance and novelty

The ACA-DID chip demonstrated excellent analytical accuracy in the quantification of African swine fever DNA samples, highlighting its potential to enhance the accessibility and effectiveness of dRPA technology. This innovation promises to overcome key limitations in current digital RPA amplification platforms, driving broader adoption and application, especially in cost-sensitive or resource-limited settings.