SAM‐dPCR: Accurate and Generalist Nuclei Acid Quantification Leveraging the Zero‐Shot Segment Anything Model
Digital PCR (dPCR) has transformed nucleic acid diagnostics by enabling the absolute quantification of rare mutations and target sequences. However, traditional dPCR detection methods, such as those involving flow cytometry and fluorescence imaging, may face challenges due to high costs, complexity, limited accuracy, and slow processing speeds. In this study, SAM-dPCR is introduced, a training-free open-source bioanalysis paradigm that offers swift and precise absolute quantification of biological samples. SAM-dPCR leverages the robustness of the zero-shot Segment Anything Model (SAM) to achieve rapid processing times (<4 seconds) with an accuracy exceeding 97.10%. This method has been extensively validated across diverse samples and reactor morphologies, demonstrating its broad applicability. Utilizing standard laboratory fluorescence microscopes, SAM-dPCR can measure nucleic acid template concentrations ranging from 0.154 copies µL<sup>-1</sup> to 1.295 × 10<sup>3</sup> copies µL<sup>-1</sup> for droplet dPCR and 0.160 × 10<sup>3</sup> to 3.629 × 10<sup>3</sup> copies µL<sup>-1</sup> for microwell dPCR. Experimental validation shows a strong linear relationship (r<sup>2</sup> > 0.96) between expected and determined sample concentrations. SAM-dPCR offers high accuracy, accessibility, and the ability to address bioanalytical needs in resource-limited settings, as it does not rely on hand-crafted "ground truth" data.
Authors
- Fuyang Qu (ORCID: https://orcid.org/0000-0002-4641-0289)
- Guoxun Zhang (ORCID: https://orcid.org/0000-0002-7709-3925)
- Yi‐Ping Ho (ORCID: https://orcid.org/0000-0002-2052-9724)
- Wu Yuan (ORCID: https://orcid.org/0000-0001-9405-519X)
- Ho‐Pui Ho (ORCID: https://orcid.org/0000-0001-5001-5911)
- Shanhang Luo
- Yuanyuan Wei (ORCID: https://orcid.org/0000-0003-1886-0407)
- Yi Zhang (ORCID: https://orcid.org/0000-0001-7147-9125)
- Changran Xu
- Yingqi Fu
Institutions
- National University of Singapore (SG)
- City University of Hong Kong (HK)
- Chinese University of Hong Kong (HK)
- Center for Excellence in Molecular Plant Sciences (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1002/advs.202406797
- Citations
- 5
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.92