Abstract
Genetic research on influenza virus biology has been informed in large part by nucleotide variants present in seasonal or pandemic samples, or individual mutants generated in the laboratory, leaving a substantial part of the genome uncharacterized. Here, we have developed a single-nucleotide resolution genetic approach to interrogate the fitness effect of point mutations in 98% of the amino acid positions in the influenza A virus hemagglutinin (HA) gene. Our HA fitness map provides a reference to identify indispensable regions to aid in drug and vaccine design as targeting these regions will increase the genetic barrier for the emergence of escape mutations. This study offers a new platform for studying genome dynamics, structure-function relationships, virus-host interactions, and can further rational drug and vaccine design. Our approach can also be applied to any virus that can be genetically manipulated.
Highlights
Genetic research on influenza virus biology has been informed in large part by nucleotide variants present in seasonal or pandemic samples, or individual mutants generated in the laboratory, leaving a substantial part of the genome uncharacterized
We have developed a comprehensive strategy using the influenza A virus as a model system to profile the fitness effects of individual point mutations and to identify essential residues throughout the HA gene in a high-throughput manner
Two studies that describe the development of a deep sequencing-based high-throughput genetic platform at singlenucleotide resolution have been reported in the literature[33,34]
Summary
Genetic research on influenza virus biology has been informed in large part by nucleotide variants present in seasonal or pandemic samples, or individual mutants generated in the laboratory, leaving a substantial part of the genome uncharacterized. We have developed a single-nucleotide resolution genetic approach to interrogate the fitness effect of point mutations in 98% of the amino acid positions in the influenza A virus hemagglutinin (HA) gene. We developed a single-nucleotide resolution genetic approach using a large mutant library and a sensitive deep sequencing technique to annotate the influenza A virus hemagglutinin (HA) gene, which carries critical roles in receptor binding, viral entry, host shifts, and immune escape mechanisms. The high-throughput profiling platform established in this study can be applied to any genetically manipulable viral gene or genome to probe mutational fitness effects under any specified growth condition
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