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Updated: May 23, 2025

Fabrication of Three-dimensional Paper-based Microfluidic Devices for Immunoassays
Published on: March 9, 2017
Origami Paper-Based Immunoassay Device with CRISPR/Cas12a Signal Amplification
Hikaru Suzuki1, Guodong Tong1, Pabitra Nath2
1Department of Applied Chemistry, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa 223-8522, Japan.
Abstract:
In clinical diagnosis, the determination of target proteins at low concentration levels is generally performed by immunoassays, such as the enzyme-linked immunosorbent assay (ELISA), which is a time-consuming process. To date, paper-based ELISA platforms enabling faster and less expensive analysis have been developed, but their important issue for clinical applications is the limited sensitivity compared to conventional ELISA. To address this challenge, this paper introduces a simple, rapid, and highly sensitive detection method for non-nucleic acid targets achieved by integrating the CRISPR/Cas12a system into paper-based ELISA. An origami-type paper-based device enabling simple assay operation has been designed, and the detection of targets on the paper substrates is based on observing the fluorescence signal induced by the CRISPR/Cas12a enzyme cleaving a probe single-stranded DNA (ssDNA) labeled with fluorophore and quencher (FQ reporter). To enhance sensitivity, antibodies labeled with a network of multiple DNA activating the CRISPR/Cas12a enzyme have been utilized as detection antibodies. As a result, the developed device successfully boosted the detection sensitivity for both human IgG and the hepatitis B virus surface antigen (HBsAg). In particular, the limit of detection (LOD) for HBsAg was estimated to be 12 pg/mL, representing over 10-fold higher sensitivity compared with commercially available HBsAg ELISA kits (LOD: 200 pg/mL). In addition, the fluorescence response toward porcine whole blood samples containing different HBsAg concentrations was also confirmed by capturing images with a smartphone, followed by quantitative data analysis. These results demonstrate the potential applicability of the proposed platform for clinical tests at the point of care.
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