Deep-Tissue Super-Resolution Microscopy using Single-Scattering Accumulation Algorithm
ABC 2020
Single-molecule localization microscopy has enabled the resolving of biomolecules well beyond the diffraction-limited spatial resolution. However, its imaging depth has been too shallow to investigate thick biological tissues. A sample-induced aberration is one of the major reasons for this limitation. It gives rise to the blur and distortion of single-molecule emission images, impairing the extremely sensitive single-molecule localization process. To resolve this issue, we combined the closed-loop accumulation of single scattering (CLASS) microscopy with stochastic optical reconstruction microscopy (STORM). CLASS microscopy identifies the sample-induced aberration based on elastic backscattering, which is then applied to a spatial light modulator in the excitation beam path of STORM for aberration correction. We demonstrated super-resolution imaging of cell microtubules under artificially generated severe aberration consisting of Zernike modes higher than mode 20 and the STORM imaging of neurons in 100µm-thick mouse brain tissue at the depth of ~70µm.