Spectral STORM: Multi-colour super-resolution imaging with a single excitation laser

Single-molecule localization microscopy allows us to observe cellular structures on the nanoscale. Due to the high frame numbers required to achieve good localization precision, multi-colour experiments can however be challenging.  Here, we present an approach to record four standard organic fluorescent dyes simultaneously with a single excitation wavelength over a large field of view. This approach dissolves problems with image registration, chromatic aberrations and sample drift common to other multi-colour approaches on the nanoscale.

Method: We use a 638 nm diode laser and a microlens-based Köhler integrator¹ for homogenous epi-illumination of the entire field of view. This ensures field-independent image resolution². Stochastic emission events from samples labelled with ‎DyLight 633, Alexa Fluor 647, Biotium CF660 and CF680 are detected through an image splitter on a sCMOS camera. For 3D localization, a cylindrical lens introduces a depth-dependent astigmatism in one detection path. Microscope control and localization fitting are performed in open-source software µManger³ and Fiji/ ThunderSTORM^4,5. Subsequent custom spectral analysis assigns a false colour to each localized emission event based on its spectroscopic signature.

In contrast to previous spectroscopic super-resolution microscopy efforts^6,7 we can achieve nanometer resolution in 3D with a single objective and camera over a field of view of 130 x 60 µm². We use immunolabelling with standard organic dyes, which makes this method applicable to a wide range of molecular biology samples. The optical setup can be implemented on any epi-fluorescence microscope. We intend to publish the spectral analysis as an open source package in the near future.

References

1. Völkel, R. & Weible, K. J. Laser Beam Homogenizing: Limitations and Constraints. Proc. SPIE 7102 (2008).
2. Douglass, K. M. et al. Super-resolution imaging of multiple cells by optimized flat-field epi-illumination. Nat. Photonics 10 (2016).
3. Edelstein, A. D. et al. Advanced methods of microscope control using μManager software. J. Biol. Methods (2014).
4. Ovesný, M. et al. ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging. Bioinformatics 30 (2014).
5. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods (2012).
6. Dong, B. et al. Super-resolution spectroscopic microscopy via photon localization. Nat. Commun. 7 (2016).
7. Zhang, Z. et al.  Ultrahigh-throughput single-molecule spectroscopy and spectrally resolved super-resolution microscopy. Nat. Methods 12 (2015).