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Zhao C, Lu D, Zhao Q, Ren C, Zhang H, Zhai J, Gou J, Zhu S, Zhang Y, Gong X. Computational methods for in situ structural studies with cryogenic electron tomography. Front Cell Infect Microbiol 2023; 13:1135013. [PMID: 37868346 PMCID: PMC10586593 DOI: 10.3389/fcimb.2023.1135013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 08/29/2023] [Indexed: 10/24/2023] Open
Abstract
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.
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Affiliation(s)
- Cuicui Zhao
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Da Lu
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Qian Zhao
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Chongjiao Ren
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Huangtao Zhang
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Jiaqi Zhai
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Jiaxin Gou
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Shilin Zhu
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Yaqi Zhang
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
| | - Xinqi Gong
- Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China
- Beijing Academy of Intelligence, Beijing, China
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Eymieux S, Uzbekov R, Rouillé Y, Blanchard E, Hourioux C, Dubuisson J, Belouzard S, Roingeard P. Secretory Vesicles Are the Principal Means of SARS-CoV-2 Egress. Cells 2021; 10:2047. [PMID: 34440816 DOI: 10.3390/cells10082047] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/06/2021] [Accepted: 08/08/2021] [Indexed: 01/01/2023] Open
Abstract
The mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) egress, similar to those of other coronaviruses, remain poorly understood. The virus buds in intracellular compartments and is therefore thought to be released by the biosynthetic secretory pathway. However, several studies have recently challenged this hypothesis. It has been suggested that coronaviruses, including SARS-CoV-2, use lysosomes for egress. In addition, a focused ion-beam scanning electron microscope (FIB/SEM) study suggested the existence of exit tunnels linking cellular compartments rich in viral particles to the extracellular space resembling those observed for the human immunodeficiency (HIV) in macrophages. Here, we analysed serial sections of Vero cells infected with SARS-CoV-2 by transmission electron microscopy (TEM). We found that SARS-CoV-2 was more likely to exit the cell in small secretory vesicles. Virus trafficking within the cells involves small vesicles, with each generally containing a single virus particle. These vesicles then fuse with the plasma membrane to release the virus into the extracellular space. This work sheds new light on the late stages of the SARS-CoV-2 infectious cycle of potential value for guiding the development of new antiviral strategies.
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