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Our Main Methods

Depending on the preferred geometry of the proteins studied, we employ various lipid layer-mimetics to find the one with optimal properties for our specific sample: this includes simple detergent micelles, amphipols, Saposin A nanoparticles, nanodiscs, lipid vesicles and lipid nanotubes. Furthermore, we actively investigate approaches to customize and optimize these templates, with the aim of applying them for dynamic structure determination.

The focus of our sample preparation for electron microscopy work is to capture dynamic processes. Thus, we concentrate on timed freezing/vitrification and trapping proteins in functional relevant conformations. In addition, we are also employing liquid phase sample preparation for selection questions.

Transmission images are then either directly evaluated to study the ultra-structure of the sample, or used to reconstruct the underlying three-dimensional structures employing either single particle, helical reconstruction or sub-tomogram averaging methods, depending on the geometry and homogeneity of the sample studied.

Electron Microscopy Equipment

The university of Cologne has made a strategic effort to establish high-resolution cryo-EM in Cologne. This resulted in establishing the platform for molecular Cryo-EM, StruBiTEM, which was inaugurated in late 2021. Using StruBiTEM, we have access to various means to prepare cryo samples, including an FEI Vitrobot and a Gatan CP3 but also custom-build freeze plungers for specific applications. For screening cryo samples, and for imaging negative stain samples, we have access to a fully automated ThermoFisher Talos L120C. High-resolution data acquisition is then done using a Titan Krios with phase plate and direct electron detector. We have developed an analysis and reconstruction pipeline that allows us to work on data while the dataset is still being acquired in order to ensure highest data quality. For this, data is immediately transferred to the HPC section of the RRZK were we process data on dedicated GPU nodes.