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Self-assembled superstructure alleviates air-water interface effect in cryo-EM

Author

Listed:
  • Liming Zheng

    (Peking University)

  • Jie Xu

    (Tsinghua University
    Tsinghua University)

  • Weihua Wang

    (China Academy of Aerospace Science and Innovation)

  • Xiaoyin Gao

    (Peking University)

  • Chao Zhao

    (Shenzhen University of Advanced Technology
    Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Weijun Guo

    (Peking University)

  • Luzhao Sun

    (Beijing Graphene Institute (BGI))

  • Hang Cheng

    (Shuimu BioSciences Ltd)

  • Fanhao Meng

    (Shuimu BioSciences Ltd)

  • Buhang Chen

    (Beijing Graphene Institute (BGI))

  • Weiyu Sun

    (Peking University
    Peking University)

  • Xia Jia

    (Tsinghua University
    Tsinghua University)

  • Xiong Zhou

    (Peking University)

  • Kai Wu

    (Peking University)

  • Zhongfan Liu

    (Peking University
    Beijing Graphene Institute (BGI))

  • Feng Ding

    (Shenzhen University of Advanced Technology
    Chinese Academy of Sciences
    Chinese Academy of Sciences)

  • Nan Liu

    (Tsinghua University
    The University of Hong Kong)

  • Hong-Wei Wang

    (Tsinghua University
    Tsinghua University)

  • Hailin Peng

    (Peking University
    Beijing Graphene Institute (BGI)
    Peking University)

Abstract

Cryo-electron microscopy (cryo-EM) has been widely used to reveal the structures of proteins at atomic resolution. One key challenge is that almost all proteins are predominantly adsorbed to the air-water interface during standard cryo-EM specimen preparation. The interaction of proteins with air-water interface will significantly impede the success of reconstruction and achievable resolution. Here, we highlight the critical role of impenetrable surfactant monolayers in passivating the air-water interface problems, and develop a robust effective method for high-resolution cryo-EM analysis, by using the superstructure GSAMs which comprises surfactant self-assembled monolayers (SAMs) and graphene membrane. The GSAMs works well in enriching the orientations and improving particle utilization ratio of multiple proteins, facilitating the 3.3-Å resolution reconstruction of a 100-kDa protein complex (ACE2-RBD), which shows strong preferential orientation using traditional specimen preparation protocol. Additionally, we demonstrate that GSAMs enables the successful determinations of small proteins (

Suggested Citation

  • Liming Zheng & Jie Xu & Weihua Wang & Xiaoyin Gao & Chao Zhao & Weijun Guo & Luzhao Sun & Hang Cheng & Fanhao Meng & Buhang Chen & Weiyu Sun & Xia Jia & Xiong Zhou & Kai Wu & Zhongfan Liu & Feng Ding , 2024. "Self-assembled superstructure alleviates air-water interface effect in cryo-EM," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51696-w
    DOI: 10.1038/s41467-024-51696-w
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    References listed on IDEAS

    as
    1. Yun-Tao Liu & Heng Zhang & Hui Wang & Chang-Lu Tao & Guo-Qiang Bi & Z. Hong Zhou, 2022. "Isotropic reconstruction for electron tomography with deep learning," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    2. Liming Zheng & Yanan Chen & Ning Li & Jincan Zhang & Nan Liu & Junjie Liu & Wenhui Dang & Bing Deng & Yanbin Li & Xiaoyin Gao & Congwei Tan & Zi Yang & Shipu Xu & Mingzhan Wang & Hao Yang & Luzhao Sun, 2020. "Robust ultraclean atomically thin membranes for atomic-resolution electron microscopy," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
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