Computational methods for in situ structural studies with cryogenic electron tomography - Zhao, Cuicui; Lu, Da; Zhao, Qian; Ren, Chongjiao; Zhang, Huangtao; Zhai, Jiaqi; Gou, Jiaxin; Zhu, Shilin; Zhang, Yaqi; Gong, Xinqi (Frontiers in Cellular and Infection Microbiology, 2023)
Cryo-electron tomography (cryo-ET) plays a critical role in imaging microorganisms in situ for further analyzing virus working mechanisms, drug exploitation, etc. 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 challenges to the reconstruction procedure.Because just 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 summarises 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 choice of each step in the whole procedure from tilt series by cryo-ET to 3D atomic structures. In addtion, it also can help more experts in various fields comprehend a recent research trend in cryo-ET. Furthermore, we hope that more researchers can join in the development of computational methods and mathematical models for high resolution three-dimensional structures from cryo-ET datasets.