Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget
Abstract Camera-based single-molecule techniques have emerged as crucial tools in revolutionizing the understanding of biochemical and cellular processes due to their ability to capture dynamic processes with high precision, high-throughput capabilities, and methodological maturity. However, the str...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54652-w |
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| author | Yu Miao Yuxiao Cheng Yushi Xia Yongzhen Hei Wenjuan Wang Qionghai Dai Jinli Suo Chunlai Chen |
| author_facet | Yu Miao Yuxiao Cheng Yushi Xia Yongzhen Hei Wenjuan Wang Qionghai Dai Jinli Suo Chunlai Chen |
| author_sort | Yu Miao |
| collection | DOAJ |
| description | Abstract Camera-based single-molecule techniques have emerged as crucial tools in revolutionizing the understanding of biochemical and cellular processes due to their ability to capture dynamic processes with high precision, high-throughput capabilities, and methodological maturity. However, the stringent requirement in photon number per frame and the limited number of photons emitted by each fluorophore before photobleaching pose a challenge to achieving both high temporal resolution and long observation times. In this work, we introduce MUFFLE, a supervised deep-learning denoising method that enables single-molecule FRET with up to 10-fold reduction in photon requirement per frame. In practice, MUFFLE extends the total number of observation frames by a factor of 10 or more, greatly relieving the trade-off between temporal resolution and observation length and allowing for long-term measurements even without the need for oxygen scavenging systems and triplet state quenchers. |
| format | Article |
| id | doaj-art-33fa399fda404137aacac07228585522 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-33fa399fda404137aacac072285855222025-01-05T12:38:41ZengNature PortfolioNature Communications2041-17232025-01-0116111010.1038/s41467-024-54652-wSupervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budgetYu Miao0Yuxiao Cheng1Yushi Xia2Yongzhen Hei3Wenjuan Wang4Qionghai Dai5Jinli Suo6Chunlai Chen7State Key Laboratory of Membrane Biology, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua UniversityDepartment of Automation, Tsinghua UniversityState Key Laboratory of Membrane Biology, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua UniversityState Key Laboratory of Membrane Biology, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua UniversityTechnology Center for Protein Sciences, School of Life Sciences, Tsinghua UniversityDepartment of Automation, Tsinghua UniversityDepartment of Automation, Tsinghua UniversityState Key Laboratory of Membrane Biology, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua UniversityAbstract Camera-based single-molecule techniques have emerged as crucial tools in revolutionizing the understanding of biochemical and cellular processes due to their ability to capture dynamic processes with high precision, high-throughput capabilities, and methodological maturity. However, the stringent requirement in photon number per frame and the limited number of photons emitted by each fluorophore before photobleaching pose a challenge to achieving both high temporal resolution and long observation times. In this work, we introduce MUFFLE, a supervised deep-learning denoising method that enables single-molecule FRET with up to 10-fold reduction in photon requirement per frame. In practice, MUFFLE extends the total number of observation frames by a factor of 10 or more, greatly relieving the trade-off between temporal resolution and observation length and allowing for long-term measurements even without the need for oxygen scavenging systems and triplet state quenchers.https://doi.org/10.1038/s41467-024-54652-w |
| spellingShingle | Yu Miao Yuxiao Cheng Yushi Xia Yongzhen Hei Wenjuan Wang Qionghai Dai Jinli Suo Chunlai Chen Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget Nature Communications |
| title | Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget |
| title_full | Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget |
| title_fullStr | Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget |
| title_full_unstemmed | Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget |
| title_short | Supervised multi-frame dual-channel denoising enables long-term single-molecule FRET under extremely low photon budget |
| title_sort | supervised multi frame dual channel denoising enables long term single molecule fret under extremely low photon budget |
| url | https://doi.org/10.1038/s41467-024-54652-w |
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