| Autor: |
Tan, Timothy J. C., Mou, Zongjun, Lei, Ruipeng, Ouyang, Wenhao O., Yuan, Meng, Song, Ge, Andrabi, Raiees, Wilson, Ian A., Kieffer, Collin, Dai, Xinghong, Matreyek, Kenneth A., Wu, Nicholas C. |
| Předmět: |
|
| Zdroj: |
Nature Communications; 4/10/2023, Vol. 14 Issue 1, p1-12, 12p |
| Abstrakt: |
Designing prefusion-stabilized SARS-CoV-2 spike is critical for the effectiveness of COVID-19 vaccines. All COVID-19 vaccines in the US encode spike with K986P/V987P mutations to stabilize its prefusion conformation. However, contemporary methods on engineering prefusion-stabilized spike immunogens involve tedious experimental work and heavily rely on structural information. Here, we establish a systematic and unbiased method of identifying mutations that concomitantly improve expression and stabilize the prefusion conformation of the SARS-CoV-2 spike. Our method integrates a fluorescence-based fusion assay, mammalian cell display technology, and deep mutational scanning. As a proof-of-concept, we apply this method to a region in the S2 domain that includes the first heptad repeat and central helix. Our results reveal that besides K986P and V987P, several mutations simultaneously improve expression and significantly lower the fusogenicity of the spike. As prefusion stabilization is a common challenge for viral immunogen design, this work will help accelerate vaccine development against different viruses. Designing vaccine immunogens is often a tedious process. Here the authors develop a deep mutational scanning-based method to rapidly and comprehensively identify prefusion stabilizing mutations of SARS-CoV-2 spike as a vaccine immunogen. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
Full text from SpringerLink