A protocol for registration and correction of multicolour STED superresolution images.

V. WESTPHAL,S.E. LEHNART,E. HEBISCH,E. WAGNER,J.J. SIEBER

doi:10.1111/jmi.12556

Abstract

Multicolour fluorescence imaging by STimulated Emission Depletion (STED) superresolution microscopy with doughnut-shaped STED laser beams based on different wavelengths for each colour channel requires precise image registration. This is especially important when STED imaging is used for co-localisation studies of two or more native proteins in biological specimens to analyse nanometric subcellular spatial arrangements. We developed a robust postprocessing image registration protocol, with the aim to verify and ultimately optimise multicolour STED image quality. Importantly, this protocol will support any subsequent quantitative localisation analysis at nanometric scales. Henceforth, using an approach that registers each colour channel present during STED imaging individually, this protocol reliably corrects for optical aberrations and inadvertent sample drift. To achieve the latter goal, the protocol combines the experimental sample information, from corresponding STED and confocal images using the same optical beam path and setup, with that of an independent calibration sample. As a result, image registration is based on a strategy that maximises the cross-correlation between sequentially acquired images of the experimental sample, which are strategically combined by the protocol. We demonstrate the general applicability of the image registration protocol by co-staining of the ryanodine receptor calcium release channel in primary mouse cardiomyocytes. To validate this new approach, we identify user-friendly criteria, which - if fulfilled - support optimal image registration. In summary, we introduce a new method for image registration and rationally based postprocessing steps through a highly standardised protocol for multicolour STED imaging, which directly supports the reproducibility of protein co-localisation analyses. Although the reference protocol is discussed exemplarily for two-colour STED imaging, it can be readily expanded to three or more colours and STED channels.

Highlights

We have developed a protocol to register and correct multicolour STimulated Emission Depletion (STED) microscopy images based on imaging schemes that generally use more than one STED doughnut
The image registration protocol maximises the crosscorrelation between defined image colour channels, it requires a relatively small number of images from a calibration sample in addition to the actual sample as data input
The image registration protocol consists of four major steps that we have thoroughly investigated and validated: (1) Prior validation of the beam alignment status for any ‘multi-doughnut’ STED microscope configuration

Summary

Introduction

Stimulated emission depletion (STED) microscopy provides subdiffraction resolution in far-field fluorescence microscopy, which increases the accuracy of fluorescence imaging and localisation of complex biological samples (cf. Berning et al, 2012; Chojnacki et al, 2012; Wagner et al, 2012; D’Este et al, 2015; Brandenburg et al, 2016), just to name a few). Three reasons for image registration mismatch appear prevalent: (1) inadvertent displacement between laser beams in a given experimental setup, either between the excitation and STED laser beams, between the different excitation laser beams or – most important for multicolour protocols – between the different STED laser beams; (2) chromatic aberrations and (3) inadvertent drift or movement, both lateral or axial, of the biological sample between consecutive imaging scans These three issues cannot be addressed separately during imaging, but rather occur in combination and can lead to a highly undesirable offset between the different colour channels. We extend this approach through readily applicable options that integrate the calibration of the microscope system and provide validation strategies for image correction in order to create standardised, thorough, and reproducible approaches for multicolour STED image analysis

Methods

Results

A-II. Use the images of the actual sample:

Conclusions

Funding sources