Title
Quantitative structural analysis of influenza virus by cryo-electron tomography and convolutional neural networks
UMMS Affiliation
Department of Biochemistry and Molecular Biotechnology; Department of Medicine; Schiffer Lab; Graduate School of Biomedical Sciences
Publication Date
2022-03-14
Document Type
Article
Disciplines
Amino Acids, Peptides, and Proteins | Biochemistry | Medicinal Chemistry and Pharmaceutics | Medicinal-Pharmaceutical Chemistry | Molecular Biology | Structural Biology | Virology | Viruses
Abstract
Influenza viruses pose severe public health threats globally. Influenza viruses are extensively pleomorphic, in shape, size, and organization of viral proteins. Analysis of influenza morphology and ultrastructure can help elucidate viral structure-function relationships and aid in therapeutics and vaccine development. While cryo-electron tomography (cryoET) can depict the 3D organization of pleomorphic influenza, the low signal-to-noise ratio inherent to cryoET and viral heterogeneity have precluded detailed characterization of influenza viruses. In this report, we leveraged convolutional neural networks and cryoET to characterize the morphological architecture of the A/Puerto Rico/8/34 (H1N1) influenza strain. Our pipeline improved the throughput of cryoET analysis and accurately identified viral components within tomograms. Using this approach, we successfully characterized influenza morphology, glycoprotein density, and conducted subtomogram averaging of influenza glycoproteins. Application of this processing pipeline can aid in the structural characterization of not only influenza viruses, but other pleomorphic viruses and infected cells.
Keywords
convolutional neural networks, cryo-electron tomography, cryoET, hemagglutinin, influenza, tomography, virus glycoprotein, virus ultrastructure
DOI of Published Version
10.1016/j.str.2022.02.014
Source
Huang QJ, Song K, Xu C, Bolon DNA, Wang JP, Finberg RW, Schiffer CA, Somasundaran M. Quantitative structural analysis of influenza virus by cryo-electron tomography and convolutional neural networks. Structure. 2022 May 5;30(5):777-786.e3. doi: 10.1016/j.str.2022.02.014. Epub 2022 Mar 14. PMID: 35290796. Link to article on publisher's site
Journal/Book/Conference Title
Structure (London, England : 1993)
Related Resources
PubMed ID
35290796
Repository Citation
Huang QY, Song K, Xu C, Bolon DN, Wang JP, Finberg RW, Schiffer CA, Somasundaran M. (2022). Quantitative structural analysis of influenza virus by cryo-electron tomography and convolutional neural networks. Schiffer Lab Publications. https://doi.org/10.1016/j.str.2022.02.014. Retrieved from https://escholarship.umassmed.edu/schiffer/52