Segmentation of lipid nanoparticles from cryogenic electron microscopy images

Description

Lipid nanoparticles (LNPs) were prepared as described (https://doi.org/10.1038/s42003-021-02441-2) using the lipids DLin-KC2-DMA, DSPC, cholesterol, and PEG-DMG2000 at mol ratios of 50:10:38.5:1.5. Four sample types were prepared: LNPs in the presence and absence of RNA, and with LNPs ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 ?L of LNP formulation was applied to holey carbon grids (Quantifoil, R3.5/1, 200 mesh copper). Grids were then incubated for 30 s at 298 K and 100% humidity before blotting and plunge-freezing into liquid ethane using a Vitrobot Mark IV (Thermo Fisher Scientific). Grids were imaged at 200 kV using a Talos Arctica system equipped with a Falcon 3EC detector (Thermo Fisher Scientific). A nominal magnification of 45,000x was used, corresponding to images with a pixel count of 4096x4096 and a calibrated pixel spacing of 0.223 nm. Micrographs were collected as dose-fractionated ?movies? at nominal defocus values between -1 and -3 ?m, with 10 s total exposures consisting of 66 frames with a total electron dose of 12,000 electrons per square nanometer. Movies were motion-corrected using MotionCor2 (https://doi.org/10.1038/nmeth.4193), resulting in flattened micrographs suitable for downstream particle segmentation. A total of 38 images were manually segmented into particle and non-particle regions. Segmentation masks and their corresponding images are deposited in this data set.

Resources

Name Format Description Link
KC2 LNPs at pH 4, without RNA Unknown CryoEM images of lipid nanoparticles and their segmentation masks Open resource
KC2 LNPs at pH 7, without RNA Unknown CryoEM images of lipid nanoparticles and their segmentation masks Open resource
KC2 LNPs at pH 4, with RNA Unknown CryoEM images of lipid nanoparticles and their segmentation masks Open resource
KC2 LNPs at pH 7, with RNA Unknown CryoEM images of lipid nanoparticles and their segmentation masks Open resource
Readme Text readme.txt Open resource

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