期刊
NATURE PHOTONICS
卷 15, 期 4, 页码 297-304出版社
NATURE PORTFOLIO
DOI: 10.1038/s41566-020-00749-9
关键词
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资金
- GDR ImaBio
- IDEX Paris Saclay [ANR-11-IDEX-0003-02]
- Labex PALM [ANR10-LABX-0039-PALM]
- AXA research fund
- ANR [ANR-10-LABX-24, LABEX WIFI]
- ANR MSM-modulated super-resolution microscopy [ANR-17-CE09-0040]
- IDEX Paris Saclay
- Labex PALM
The modulated localization microscopy achieves high molecular localization precision through an illumination modulation method, improving axial localization precision while maintaining fast acquisition speed. Compared to existing super-resolution fluorescence microscopy, this method offers unique advantages.
Adapting the amplitude-modulated light detection and ranging approach to super-resolution microscopy offers a typical axial localization precision of 6.8 nm over the entire field of view and the axial capture range, enabling imaging of biological samples by up to several micrometres in depth. Distance measurements are commonly performed by phase detection based on a lock-in strategy. Super-resolution fluorescence microscopy is still striving to perform axial localization but through entirely different strategies. Here we show that an illumination modulation approach can achieve nanometric axial localization precision without compromising the acquisition time, emitter density or lateral localization precision. The excitation pattern is obtained by shifting tilted interference fringes. The molecular localizations are performed by measuring the relative phase between each fluorophore response and the reference modulated excitation pattern. We designed a fast demodulation scheme compatible with the short emission duration of single emitters. This modulated localization microscopy offers a typical axial localization precision of 6.8 nm over the entire field of view and the axial capture range. Furthermore, the interfering pattern being robust to optical aberrations, a nearly uniform axial localization precision enables imaging of biological samples by up to several micrometres in depth.
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