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Segmentation of lipid nanoparticles from cryogenic electron microscopy images

Contact: Thomas Cleveland.
Identifier: doi:10.18434/mds2-2753
Version: 1.0 First Released: 2023-02-01 Revised: 2023-02-01
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.
Research Areas
NIST R&D: Information Technology: Software researchInformation Technology: Computational sciencePhysics: Biological physicsNanotechnology: NanobiotechnologyBioscience: Biomaterials
Keywords: Lipid NanoparticleLNPcryogenic electron microscopyCryoEMmachine learningShow more...
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Version: 1.0 First Released: 2023-02-01 Revised: 2023-02-01
Cite this dataset
Thomas Cleveland (2022), Segmentation of lipid nanoparticles from cryogenic electron microscopy images, National Institute of Standards and Technology, https://doi.org/10.18434/mds2-2753 (Accessed 2025-02-14)
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