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Updated: Jul 15, 2025

Fluorescence detection methods for microfluidic droplet platforms
Published on: December 10, 2011
An approach for integrating droplet generation and detection in digital polymerase chain reaction applications based
Jinxian Wang1, Xin Lyu2, Xiaoliang Zhang1
1School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
Abstract:
Digital polymerase chain reaction (dPCR) is an approach for absolute nucleic acid quantification with high sensitivity. Although several successful commercial dPCR devices have been developed to date, further miniaturizing device dimensions, decreasing cross-contamination, and improving automation level are still research highlights. In this study, we developed a fully contamination-free dPCR detection chip with fluorescence flow cytometry and micro droplet approach. A bifunctional cross-structure (BFCS) was designed to realize monodisperse sample droplet generation in forward flow and droplet detection in backward flow with simple pneumatic control and fixed chip position. In order to improve droplet detection efficiency and accuracy, droplets morphology and sequence pattern during microfluidic droplet generation and backward flow droplet detection at the same cross-structure were observed and analyzed under different pneumatic pressures. In addition, during backward flow droplet detection, an optimized declination angle of the chip was applied to increase droplet reflux rates. For the validation of PCR performance, temperature changing processes during PCR cycles were achieved by heating the monodispersed droplet array with a customized PCR amplification device. The fluorescence signal of each droplet right after passing the cross-structure was excitated and detected. The absolute quantification ability of our integrated dPCR microfluidic chip utilizing flow fluorescence cytometry was tested and verified with Influenza A virus gene (from 7.5 copies/μL to 30000 copies/μL). Thus, our platform provides a novel and integrated approach for ddPCR analysis.

