Discriminating single-molecule binding events from diffraction-limited fluorescence

Yueming Yin, Nithin Pathoor, Kamal Kant Sharma, Shiwen Zhu, Iong Ying Loh, Yan Shan Ang, Shao Ren Sim, Lin Yue Lanry Yung, Thorsten Wohland () and Lipo Wang ()
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Yueming Yin: Nanyang Technological University
Nithin Pathoor: National University of Singapore
Kamal Kant Sharma: National University of Singapore
Shiwen Zhu: National University of Singapore
Iong Ying Loh: National University of Singapore
Yan Shan Ang: National University of Singapore
Shao Ren Sim: National University of Singapore
Lin Yue Lanry Yung: National University of Singapore
Thorsten Wohland: Nanyang Technological University
Lipo Wang: Nanyang Technological University

Nature Communications, 2025, vol. 16, issue 1, 1-18

Abstract: Abstract Single-molecule localization microscopy enables high-resolution imaging of molecular interactions, but discriminating molecular binding types has traditionally relied on complex strategies, such as multiple dyes, time-division techniques, or kinetic analysis, that are asynchronous, invasive, or time-consuming. Here, we uncover previously overlooked spatiotemporal information embedded within diffraction-limited fluorescence, enabling synchronous classification of individual binding event videos using only a single fluorescent dye. Building on this insight, we propose a Temporal-to-Context Convolutional Neural Network (T2C CNN), which integrates long-term spatial convolutions, shallow cross-connected blocks, and a pooling-free structure to enhance contextual representation while preserving fine-grained temporal features. Applied to DNA-PAINT experiments, T2C CNN achieves up to 94.76% classification accuracy and outperforms state-of-the-art video classification models by 15-25 percentage points. Our approach enables rapid and precise binding-type recognition from fluorescence video data, reducing observation time from minutes to seconds and facilitating high-throughput single-molecule imaging without requiring multiple dye channels or extended kinetic measurements.

Date: 2025
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DOI: 10.1038/s41467-025-64812-1

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