MPicker: visualizing and picking membrane proteins for cryo-electron tomography

X Xiaofeng Yan S Shudong Li W Weilin Huang (State Key Laboratory for Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials and Department of Chemistry, College of Chemistry and Chemical Engineering, Tan Kah Kee Innovation Laboratory (IKKEM)) H Hao Wang (Division of Quantitative Sciences, Department of Oncology Johns Hopkins University School of Medicine Baltimore Maryland USA) T Tianfang Zhao M Mingtao Huang N Niyun Zhou (Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University) Y Yuan Shen X Xueming Li

Abstract

Abstract Advancements in cryo-electron tomography (cryoET) allow the structure of macromolecules to be determined in situ, which is crucial for studying membrane protein structures and their interactions in the cellular environment. However, membranes are often highly curved and have a strong contrast in cryoET tomograms, which masks the signals from membrane proteins. These factors pose difficulties in observing and revealing the structures of membrane proteins in situ. Here, we report a membrane-flattening method and the corresponding software, MPicker, designed for the visualization, localization, and orientation determination of membrane proteins in cryoET tomograms. This method improves the visualization of proteins on and around membranes by generating a flattened tomogram that eliminates membrane curvature and reduces the spatial complexity of membrane protein analysis. In MPicker, we integrated approaches for automated particle picking and coarse alignment of membrane proteins for sub-tomogram averaging. MPicker was tested on tomograms of various cells to evaluate the method for visualizing, picking, and analyzing membrane proteins.

Article Details

Volume / Issue Vol. 16, Issue 1
Published January 08, 2025
ISSN 2041-1723
Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (9)

X

Xiaofeng Yan

S

Shudong Li

W

Weilin Huang

State Key Laboratory for Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials and Department of Chemistry, College of Chemistry and Chemical Engineering, Tan Kah Kee Innovation Laboratory (IKKEM)

H

Hao Wang

Division of Quantitative Sciences, Department of Oncology Johns Hopkins University School of Medicine Baltimore Maryland USA

T

Tianfang Zhao

M

Mingtao Huang

N

Niyun Zhou

Ministry of Education Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University

Y

Yuan Shen

X

Xueming Li