About

Approach

Given the spillover risk posed by Nipah virus, we sought to understand how mutations affect important phenotypes of the fusion protein. Specifically, we measured how mutations affect cell entry and antibody neutralization. To do this, we used a technique called deep mutational scanning, which allows us to measure the effects of thousands of mutations in parallel. These data provide a comprehensive view of the functional importance of each amino acid in the fusion protein, and can help us understand how the virus might evolve in the future. Furthermore, we show that certain antibodies are less affected by escape mutations, suggesting they may be promising candidates for therapeutic development.

Links to data

Our final filtered datasets in csv format can be found here:

• Cell Entry
• Antibody Escape

People

Primary work performed in the Bloom lab at the Fred Hutch Cancer Center with contributions from the Veesler lab at the University of Washington.

• Brendan Larsen
• Sheri Harari
• Risako Gen
• Cameron Stewart
• David Veesler
• Jesse Bloom

Biosafety

We take biosafety seriously and took multiple steps to ensure our experiments were safe. To measure the effects of ~8,500 Nipah fusion mutations, we used non-replicative pseudoviruses. These particles can enter cells but cannot replicate or produce new virus particles, and are not infectious agents. Importantly, we used a vector that expresses no viral proteins besides the Nipah fusion protein, and other essential pseudovirus components are provided from four separate plasmids. This approach allowed us to safely measure the effects of mutations without the risks associated with working with authentic virus.

To limit generating hazardous information about human-specific adaptations, we performed all experiments in cells expressing either bat ephrin-B2 or -B3 from the black flying fox, a natural host of henipaviruses. By measuring the effects of mutations in this context, we minimized the risk of generating hazardous information about human-specific adaptations. We previously published data from deep mutational scanning of the receptor binding protein using the same safe approach.