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. 2023 Mar 14;4(2):102166.
doi: 10.1016/j.xpro.2023.102166. Online ahead of print.

A protocol for capturing RNA-sensing innate immune receptors in multiple conformations by single-particle cryo-EM

Affiliations

A protocol for capturing RNA-sensing innate immune receptors in multiple conformations by single-particle cryo-EM

Wenshuai Wang et al. STAR Protoc. .

Abstract

Capturing different conformations of receptor proteins that are complexed with ligands by single-particle cryo-EM facilitates our understanding toward the mechanisms of ligand recognition and receptor activation cascades. Here, we present a protocol for capturing RNA-sensing innate immune receptors, such as RIG-I, in multiple conformations by single-particle cryo-EM. We describe steps for protein-ligand sample preparation, data acquisition, and image processing covering focused three-dimensional classification. This protocol can be adapted to capture the dynamic behavior of other receptors that can be stabilized. For complete details on the use and execution of this protocol, please refer to Wang and Pyle (2022).1.

Keywords: Cryo-EM; Immunology; Molecular Biology; Protein Biochemistry; Protein Expression and Purification; Structural Biology.

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Conflict of interest statement

Declaration of interests Yale University has submitted patent applications for Stem-loop RNAs. A.M.P. has founded a company (RIGImmune) to develop SLRs as therapeutic agents.

Figures

None
Graphical abstract
Figure 1
Figure 1
Representative results during protein and RNA preparation (A) Representative size-exclusion chromatography elution profile of human full-length RIG-I using Superdex 200 Increase 10/300 GL column. (B) Representative purification step of synthesized RNA oligonucleotide using 16% urea denaturing polyacrylamide gel. (C) Representative purity evaluation of ssRNA namely OHSLR30 using mass spec. The sodium adducts are OHSLR30 bound to multiple sodium ions. (D) Representative annealing evaluation of annealed dsRNA using 15% native gel.
Figure 2
Figure 2
Representative data during data collection and processing (A) Representative micrograph. (B) Representative 2D class averages using manual pick particles. (C) Representative 2D class averages showing good and bad features. The 1:1 and 2:1 RIG-I:RNA complexes are rendered. The representative 2D class averages of bad particles (upper left), ice contamination (upper right) and carbon (lower left) are shown. (D) Representative 3D maps of intact 1:1 RIG-I:RNA complex and unbound end-removed complex.
Figure 3
Figure 3
Workflow of improving global resolution and identifying different conformational states using focused 3D classification w/i and w/o alignment (A) Focused 3D classification w/i alignment using mask to exclude the unbound RNA end. (B) Focused 3D classification w/o alignment using mask covering the whole EM map.

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References

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