Krios microscope

Tomographic tilt series were collected using serialEM and the FastTomo script^{30 (link)} on a Titan Krios microscope equipped with Gatan BioQuantum K3 imaging filter and camera. A bidirectional scheme was used for the tilting, from −30° to +60° and then to −60° with a 2° step. A fixed electron dosage of about 2.5e⁻/² (measured at empty area) was used for each exposure, which was fractionated into 12 frames. A nominal magnification of 81,000x was used, corresponding to a pixel size of 0.539 /pixel on the camera at super-resolution mode. A target defocus of −1.6 micron was set at the beginning of each tilt series. A slit of 20 eV was used for the imaging filter.

See Supplementary Table 1 for number of tomograms collected for each variant and with which microscope.
The Talos microscope, fitted with a Falcon 3 camera, was operated at 200 kV. Tomograms were collected using the Thermo Fisher Tomography 5 software in linear mode, using a dose-symmetric scheme at 3° intervals to + /− 57° at a pixel size of 2.58 Å, and total dose of 94e^-/Ų.
The Titan Krios microscope is fitted with a Gatan GIF Quantum energy filter operated in zero-loss mode with a 20 eV slit width, and a K2 Summit detector (Gatan) operated in counting mode. Dose-symmetric tilt series were aquired using the Thermo Fisher Tomography 5 software at 3° intervals to + /−60°, using a defocus range of −2.5 to -5um, at a pixel size if 2.22 Å and 4 frames per tilt image. The total tomogram dose was 98e^-/Ų.

We used a cryo-EM dataset of 70S ribosome comprising 68,543 particle images with box size of 280 pixels and a pixel size of 1.32 Å from Prof. Ning Gao’s group. These micrographs were taken from a Titan Krios microscope equipped with a Gatan K2-Summit electron counting camera. We firstly reconstructed a 3D volume of the entire 70S ribosome following the conventional way. This 3D reconstruction was further refined with a local angular search range of 15°, during which a 30S or 50S mask was applied, resulting in the 3D map of 30S or 50S subunit, respectively. We then segmented the 30S subunit from the dataset with a box size of 280 pixels by subtracting the 50S subunit with the segmentation algorithm. The segmented 30S particles were subjected to 2D classification to select good particles for further 3D auto-refinement. The 50S subunit was subsequently segmented from the 70S ribosome images by subtracting the 30S signal using the segmentation algorithm. The segmented 50S subunit images were then refined to reconstruct a 3D volume. As a control, we also generated 30S or 50S sub-particles with relion_project and performed 3D auto-refinement with these sub-particles. The rotating angles between segmented 30S and 50S subunits were calculated with a program CompareDataStars_data.py written with EMAN2 package.