Structured illumination-based super-resolution live-cell quantitative FRET imaging

Abstract

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.