Image processing was performed with the RELION 2.1 software package (29). The micrographs were motion-corrected using MotionCorr2 (30), and contrast transfer function (CTF) information was determined using ctffind4.1 (31). Together, 262 micrographs with CTF rings extending beyond 4.6 Å were selected for further processing. A total of 3600 particles were boxed using RELION autopicking software. After two-dimensional (2D) classification (fig. S3C) and 3D classification with imposed icosahedral symmetry, initial 3D autorefinement led to a reconstruction of ~4.2-Å resolution. Further rounds of 3D classification/refinement were carried out on polished particles before using postprocessing for masking and automatic B factor sharpening. The resolution of the final map was determined to be 3.5 Å based on the Fourier shell correlation (FSC) 0.143 cutoff criterion (fig. S3D) (32). Local resolution was calculated using local resolution estimation program in RELION (fig. S3E).

Processing and 3D classification of ADDomer were performed using public cloud resources provided by the Oracle Cloud Infrastructure. Using this rather than an institutional cluster allowed a faster turnaround time of analysis. Because of the particular nature of the computational work carried out by the steps within RELION, a heterogeneous cluster was prepared with both central processing unit (CPU)– and graphical processing unit (GPU)–focused resources. A pipeline of workloads was created, allowing the work best suited to each compute type to use just the resources needed and to automatically release compute resources when no longer needed. This permitted parts of the workflow to use lower-cost CPU resources and to burst to GPU only for those parts that would benefit from GPU optimization, reducing overall cost while increasing total data throughput. The total cost for running the image processing pipeline on the cloud was approximately £200.

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