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A CTF-Based Data Augmentation Method for the Segmentation of Lipid Nanoparticles in Cryo-EM

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. RNA was not included and LNPs were ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 μL 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 μm, 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. Images were manually segmented into particle and non-particle regions. Segmentation masks and their corresponding images are deposited in this data set.

About this Dataset

Updated: 2026-09-04
Metadata Last Updated: 2026-02-23 00:00:00
Date Created: N/A
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Dataset Owner: N/A

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Title A CTF-Based Data Augmentation Method for the Segmentation of Lipid Nanoparticles in Cryo-EM
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. RNA was not included and LNPs were ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 μL 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 μm, 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. Images were manually segmented into particle and non-particle regions. Segmentation masks and their corresponding images are deposited in this data set.
Modified 2026-02-23 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Lipid , nanoparticle , LNP , Cryo-EM , TEM , electron microscopy , segmentation , augmentation , Contrast transfer function , CTF , machine learning , ML , AI , Drug delivery , KC2
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