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 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

SUBMITTER: Miao Y 

PROVIDER: S-EPMC11697068 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature