EMPIAR-13426 - Cryo-EM SPA dataset of arginine oxidase from Pseudomonas sp. TRU 7192 [5035 multi-frame micrographs composed of 40 frames each in TIFF format]

EMPIAR-13426

Cryo-EM SPA dataset of arginine oxidase from Pseudomonas sp. TRU 7192 [5035 multi-frame micrographs composed of 40 frames each in TIFF format]

Publication:

Open and closed structures of L-arginine oxidase by cryo-electron microscopy and X-ray crystallography

Yamaguchi H, Takahashi K, Numoto N, Suzuki H, Tatsumi M, Kamegawa A, Nishikawa K, Asano Y, Mizukoshi T, Miyano H, Fujiyoshi Y, Sugiki M

Journal of biochemistry (2025)

PMID: 39420599

DOI: 10.1093/jb/mvae070

Related EMDB entry:

EMD-36635

Deposited:

2024-12-05

Released:

2026-06-17

Last modified:

2026-06-17

Imageset size:

916.40 GB

Imageset DOI:

10.6019/EMPIAR-13426

Experimental metadata:

Download xml json

Deposited via PDBj

Contains:

micrographs - multiframe

Image Sets

1. Structure of arginine oxidase from Pseudomonas sp. TRU 7192

Category:

micrographs - multiframe

Image format:

TIFF

No. of images or tilt series:

5035

Image size:

(3710, 3838)

Pixel type:

UNSIGNED 16 BIT INTEGER

Pixel spacing:

(0.96, 0.96)

Details:

- Microscope: JEOL JEM-Z320FHC
- Acceleration voltage (kV): 300
- Spherical aberration (mm) : 3.4
- Detector: Gatan K2 Summit
- Please ignore the pixel size in the header; use 0.96 A/px.
- Dose per frame (e-/A^2): 1.74
- Number of frames per image: 40
- Gain reference (MRC format) is included in the folder with the movie files. The gain was created from the dataset by using the 'relion_estimate_gain' command and can be used in RELION without flipping/rotation. In CryoSPARC, select "flip gain ref in Y".
- Please ignore the pixel size in the header; use 0.96 A/px.

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Citations

AlignPCA-2D: PCA-reduced Euclidean vector alignment for 2D classification in cryo-EM.

Ramírez-Aportela E, Zarrabeitia OL, Fonseca YC, Ceska T, Subramaniam S, Carazo JM, Sorzano COS. (2026)

A variational framework with composite sparse regularization for cryo-electron tomography reconstruction.

Yu C, Xu Z, Zeng Q, Wan X, El-Messiry H, Zhang F, Han R. (2026)

Helical reconstruction of amyloids in cryoSPARC.

Schaefer JH, O'Neill RT, Donnelly JP, Powers ET, Kelly JW, Lander GC. (2026)

CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs.

Poudel B, Gyawali R, Dhakal A, Cheng J, Xu D. (2026)

An unattended image-processing pipeline for on-the-fly quality assessment and 3D exploration in cryo-EM.

Marchán Torres D, Conesa P, Garcia A, Iceta M, Broche L, Gragera M, Linares R, Kwong HS, Chichón FJ, Svensson O, Arranz R, Effantin G, Kandiah E, Carazo JM, Sorzano COS. (2026)

prismPYP: Power-spectrum and image domain learning for self-supervised micrograph evaluation.

He L, Bartesaghi A. (2026)

CryoSIP: unleashing protein high-resolution Cryo-EM via semantic-instance collaborative picking.

Deng Y, Wang S, Xiang M, Li Y, Zhuo L, Cao D, Fu X, Zou Q. (2026)

Unbend, correction of local beam-induced sample motion in cryo-EM images using a 3D spline model.

Kong L, Zottig X, Elferich J, Grigorieff N. (2026)

CryoVirusDB: An Annotated Dataset for AI-Based Virus Particle Identification in Cryo-EM Micrographs.

Gyawali R, Dhakal A, Wang L, Cheng J. (2026)

Chart builder: an interactive tool for user driven data visualization in the electron microscopy data bank.

Fonseca N, Duraisamy AK, Wang Z, Somasundharam S, Tayebinia M, de Oliveira LC, Ma M, Turner J, Patwardhan A, Kleywegt GJ, Hartley M, Morris KL. (2026)

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