Zewei Luo 1,2†Guodong Zang 1,2Ge Wu 1,2Mengting Kong 1,2[ ... ]Tongsheng Chen 1,2,*
Author Affiliations
Abstract
1 South China Normal University, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
2 South China Normal University, College of Biophotonics, Guangdong Key Laboratory of Laser Life Science, Guangzhou, China
Structured illumination-based super-resolution Förster resonance energy transfer microscopy (SIM-FRET) provides an approach to resolving molecular behavior localized in intricate biological structures in living cells. However, SIM reconstruction artifacts will decrease the quantitative analysis fidelity of SIM-FRET signals. To address these issues, we have developed a method called HiFi spectrum optimization SIM-FRET (HiFi-SO-SIM-FRET), which uses optimized Wiener parameters in the two-step spectrum optimization to suppress sidelobe artifacts and achieve super-resolution quantitative SIM-FRET. We validated our method by demonstrating its ability to reduce reconstruction artifacts while maintaining the accuracy of FRET signals in both simulated FRET models and live-cell FRET-standard construct samples. In summary, HiFi-SO-SIM-FRET provides a promising solution for achieving high spatial resolution and reducing SIM reconstruction artifacts in quantitative FRET imaging.
super-resolution structured illumination microscopy Förster resonance energy transfer living cells quantitative measurement 
Advanced Photonics Nexus
2023, 2(5): 056008
Zewei Luo 1,2†Ge Wu 1,2†Mengting Kong 1,2Zhi Chen 1,2[ ... ]Tongsheng Chen 1,2,3,6,*
Author Affiliations
Abstract
1 Key Laboratory of Laser Life Science, Ministry of Education, College of Biophotonics, South China Normal Universityhttps://ror.org/01kq0pv72, Guangzhou 510631, China
2 Guangdong Key Laboratory of Laser Life Science, College of Biophotonics, South China Normal University, Guangzhou 510631, China
3 SCNU Qingyuan Institute of Science and Technology Innovation, South China Normal University, Qingyuan 511520, China
4 Chongqing Key Laboratory of Image Cognition, College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
5 e-mail: fanjc@cqupt.edu.cn
6 e-mail: chentsh@scnu.edu.cn
Förster resonance energy transfer (FRET) microscopy provides unique insight into the functionality of biological systems via imaging the spatiotemporal interactions and functional state of proteins. Distinguishing FRET signals from sub-diffraction regions requires super-resolution (SR) FRET imaging, yet is challenging to achieve from living cells. Here, we present an SR FRET method named SIM-FRET that combines SR structured illumination microscopy (SIM) imaging and acceptor sensitized emission FRET imaging for live-cell quantitative SR FRET imaging. Leveraging the robust co-localization prior of donor and accepter during FRET, we devised a mask filtering approach to mitigate the impact of SIM reconstruction artifacts on quantitative FRET analysis. Compared to wide-field FRET imaging, SIM-FRET provides nearly twofold spatial resolution enhancement of FRET imaging at sub-second timescales and maintains the advantages of quantitative FRET analysis in vivo. We validate the resolution enhancement and quantitative analysis fidelity of SIM-FRET signals in both simulated FRET models and live-cell FRET-standard construct samples. Our method reveals the intricate structure of FRET signals, which are commonly distorted in conventional wide-field FRET imaging.
Photonics Research
2023, 11(5): 887

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