Computational methods for in situ structural studies with cryogenic electron tomography

Frontiers in Cellular and Infection Microbiology

Cellular and Infection Microbiology

Jiaqi Zhai¹  Chongjiao Ren¹  Huangtao Zhang¹  Jiaxin Gou¹  Shilin Zhu¹  Qian Zhao¹  Yaqi Zhang¹  Da Lu¹  Cuicui Zhao¹  Xinqi Gong² 

[1] Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China;Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China;Beijing Academy of Intelligence, Beijing, China;

关键词: cryo-electron tomography (cryo-ET);    subtomogram averaging (STA);    in situ;    3D reconstruction;    deep learning;    mathematical models;   

DOI  :  10.3389/fcimb.2023.1135013

 received in 2022-12-31, accepted in 2023-08-29,  发布年份 2023

来源: Frontiers

【 摘 要 】

Cryo-electron tomography (cryo-ET) plays a critical role in imaging microorganisms in situ in terms of further analyzing the working mechanisms of viruses and drug exploitation, among others. A data processing workflow for cryo-ET has been developed to reconstruct three-dimensional density maps and further build atomic models from a tilt series of two-dimensional projections. Low signal-to-noise ratio (SNR) and missing wedge are two major factors that make the reconstruction procedure challenging. Because only few near-atomic resolution structures have been reconstructed in cryo-ET, there is still much room to design new approaches to improve universal reconstruction resolutions. This review summarizes classical mathematical models and deep learning methods among general reconstruction steps. Moreover, we also discuss current limitations and prospects. This review can provide software and methods for each step of the entire procedure from tilt series by cryo-ET to 3D atomic structures. In addition, it can also help more experts in various fields comprehend a recent research trend in cryo-ET. Furthermore, we hope that more researchers can collaborate in developing computational methods and mathematical models for high-resolution three-dimensional structures from cryo-ET datasets.

【 授权许可】

Unknown   
Copyright © 2023 Zhao, Lu, Zhao, Ren, Zhang, Zhai, Gou, Zhu, Zhang and Gong