Issue 4, 2023

Compact wide-field femtoliter-chamber imaging system for high-speed and accurate digital bioanalysis

Abstract

The femtoliter-chamber array is a bioanalytical platform that enables highly sensitive and quantitative analysis of biological reactions at the single-molecule level. This feature has been considered a key technology for “digital bioanalysis” in the biomedical field; however, its versatility is limited by the need for a large and expensive setup such as a fluorescence microscope, which requires a long time to acquire the entire image of a femtoliter-chamber array. To address these issues, we developed a compact and inexpensive wide-field imaging system (COWFISH) that can acquire fluorescence images with a large field of view (11.8 mm × 7.9 mm) and a high spatial resolution of ∼ 3 μm, enabling high-speed analysis of sub-million femtoliter chambers in 20 s. Using COWFISH, we demonstrated a CRISPR-Cas13a-based digital detection of viral RNA of SARS-CoV-2 with an equivalent detection sensitivity (limit of detection: 480 aM) and a 10-fold reduction in total imaging time, as compared to confocal fluorescence microscopy. In addition, we demonstrated the feasibility of COWFISH to discriminate between SARS-CoV-2-positive and -negative clinical specimens with 95% accuracy, showing its application in COVID-19 diagnosis. Therefore, COWFISH can serve as a compact and inexpensive imaging system for high-speed and accurate digital bioanalysis, paving a way for various biomedical applications, such as diagnosis of viral infections.

Graphical abstract: Compact wide-field femtoliter-chamber imaging system for high-speed and accurate digital bioanalysis

Supplementary files

Article information

Article type
Paper
Submitted
10 Aug 2022
Accepted
13 Oct 2022
First published
18 Oct 2022

Lab Chip, 2023,23, 684-691

Author version available

Compact wide-field femtoliter-chamber imaging system for high-speed and accurate digital bioanalysis

T. Iida, J. Ando, H. Shinoda, A. Makino, M. Yoshimura, K. Murai, M. Mori, H. Takeuchi, T. Noda, H. Nishimasu and R. Watanabe, Lab Chip, 2023, 23, 684 DOI: 10.1039/D2LC00741J

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