Deep mutational scanning of influenza A virus neuraminidase facilitates the identification of drug resistance mutations in vivo

ABSTRACT Neuraminidase (NA) is a pivotal surface enzyme and a key therapeutic target in combating the influenza A virus. Its evolution can lead to potential zoonotic transmission, seasonal epidemics, and the emergence of drug-resistant mutants. To gain comprehensive insights into the mutational effects and drug resistance profiles of NA, we employed a high-throughput profiling system to quantify the replication capacity of NA mutants at the single-nucleotide level in mouse lung tissues. The fitness of NA mutants is generally correlated with natural mutation occurrence and is constrained by both the requirement to maintain protein stability and NA function. Leveraging this system, we profiled the drug resistance to the three most commonly used neuraminidase inhibitors (NAIs): zanamivir, oseltamivir, and peramivir. In addition to identifying previously reported drug resistance mutations, we validated novel mutants. Notably, we identified an allosteric mutation that confers resistance to all three drugs, which may affect drug binding by interfering with the tetramerization of NA. Moreover, the fitness cost associated with drug-resistant mutations may limit their widespread dissemination. In summary, we provided a parallel characterization of NA’s fitness and drug resistance landscape in an in vivo context, which may guide the rational selection of antiviral drugs for optimal therapeutic efficacy and second-generation NAI development. IMPORTANCE NA is a crucial surface antigen and drug target of influenza A virus. A comprehensive understanding of NA’s mutational effect and drug resistance profiles in vivo is essential for comprehending the evolutionary constraints and making informed choices regarding drug selection to combat resistance in clinical settings. In the current study, we established an efficient deep mutational screening system in mouse lung tissues and systematically evaluated the fitness effect and drug resistance to three neuraminidase inhibitors of NA single-nucleotide mutations. The fitness of NA mutants is generally correlated with a natural mutation in the database. The fitness of NA mutants is influenced by biophysical factors such as protein stability, complex formation, and the immune response triggered by viral infection. In addition to confirming previously reported drug-resistant mutations, novel mutations were identified. Interestingly, we identified an allosteric drug-resistance mutation that is not located within the drug-binding pocket but potentially affects drug binding by interfering with NA tetramerization. The dual assessments performed in this study provide a more accurate assessment of the evolutionary potential of drug-resistant mutations and offer guidance for the rational selection of antiviral drugs. NA is a crucial surface antigen and drug target of influenza A virus. A comprehensive understanding of NA’s mutational effect and drug resistance profiles in vivo is essential for comprehending the evolutionary constraints and making informed choices regarding drug selection to combat resistance in clinical settings. In the current study, we established an efficient deep mutational screening system in mouse lung tissues and systematically evaluated the fitness effect and drug resistance to three neuraminidase inhibitors of NA single-nucleotide mutations. The fitness of NA mutants is generally correlated with a natural mutation in the database. The fitness of NA mutants is influenced by biophysical factors such as protein stability, complex formation, and the immune response triggered by viral infection. In addition to confirming previously reported drug-resistant mutations, novel mutations were identified. Interestingly, we identified an allosteric drug-resistance mutation that is not located within the drug-binding pocket but potentially affects drug binding by interfering with NA tetramerization. The dual assessments performed in this study provide a more accurate assessment of the evolutionary potential of drug-resistant mutations and offer guidance for the rational selection of antiviral drugs.

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