Vaccine-induced NA immunity decreases viral shedding, but does not disrupt chains of airborne transmission for the 2009 pandemic H1N1 virus in ferrets.

Split-virion-inactivated influenza vaccines are formulated based on viral hemagglutinin content. These vaccines also contain the viral neuraminidase (NA) protein, but NA content is not standardized and varies between manufacturers. In clinical studies and animal models, antibodies directed toward NA reduced disease severity and viral load; however, the impact of vaccine-induced NA immunity on airborne transmission of influenza A viruses is not well characterized. Therefore, we evaluated if vaccination against NA could disrupt chains of airborne transmission for the 2009 pandemic H1N1 virus in ferrets. Immunologically naïve donor ferrets were infected with the 2009 pandemic H1N1 virus and then paired in transmission cages with mock- or NA-vaccinated respiratory contacts. The mock- and NA-vaccinated animals were then monitored daily for infection, and once infected, these animals were paired with a naive secondary respiratory contact. In these studies, all mock- and NA-vaccinated animals became infected; however, NA-vaccinated animals shed significantly less virus for fewer days relative to mock-vaccinated animals. For the secondary contacts, 6/6 and 5/6 animals became infected after exposure to mock- and NA-vaccinated animals, respectively. To determine if vaccine-induced immune pressure selected for escape variants, we sequenced viruses recovered from ferrets. No mutations in NA became enriched during transmission. These findings indicate that despite reducing viral load, vaccine-induced NA immunity does not prevent infection during continuous airborne exposure and subsequent onward airborne transmission of the 2009 pandemic H1N1 virus. IMPORTANCE: In humans and animal models, immunity against neuraminidase (NA) reduces disease severity and viral replication during influenza infection. However, we have a limited understanding of the impact of NA immunity on viral transmission. Using chains of airborne transmission in ferrets as a strategy to simulate a more natural route of infection, we assessed if vaccine-induced NA immunity could disrupt transmission of the 2009 pandemic H1N1 virus. The 2009 pandemic H1N1 virus transmitted efficiently through chains of transmission in the presence of NA immunity, but NA-vaccinated animals shed significantly less virus and had accelerated viral clearance. To determine if immune pressure led to the generation of escape variants, viruses in ferret nasal wash samples were sequenced, and no mutations in NA were identified. These findings demonstrate that vaccine-induced NA immunity is not sufficient to prevent infection via airborne exposure and onward airborne transmission of the 2009 pandemic H1N1 virus.

Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCE: When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.