The influenza pandemic that emerged in 2009 provided an unprecedented opportunity to study adaptation of a virus recently acquired from an animal source during human transmission. In the United Kingdom, the novel virus spread in three temporally distinct waves between 2009 and 2011. Phylogenetic analysis of complete viral genomes showed that mutations accumulated over time. Second- and third-wave viruses replicated more rapidly in human airway epithelial (HAE) cells than did the first-wave virus. In infected mice, weight loss varied between viral isolates from the same wave but showed no distinct pattern with wave and did not correlate with viral load in the mouse lungs or severity of disease in the human donor. However, second- and third-wave viruses induced less alpha interferon in the infected mouse lungs. NS1 protein, an interferon antagonist, had accumulated several mutations in second- and third-wave viruses. Recombinant viruses with the third-wave NS gene induced less interferon in human cells, but this alone did not account for increased virus fitness in HAE cells. Mutations in HA and NA genes in third-wave viruses caused increased binding to α-2,6-sialic acid and enhanced infectivity in human mucus. A recombinant virus with these two segments replicated more efficiently in HAE cells. A mutation in PA (N321K) enhanced polymerase activity of third-wave viruses and also provided a replicative advantage in HAE cells. Therefore, multiple mutations allowed incremental changes in viral fitness, which together may have contributed to the apparent increase in severity of A(H1N1)pdm09 influenza virus during successive waves.

Influenza viruses cause annual seasonal epidemics and occasional pandemics. It is important to elucidate the stringency of bottlenecks during transmission to shed light on mechanisms that underlie the evolution and propagation of antigenic drift, host range switching or drug resistance. The virus spreads between people by different routes, including through the air in droplets and aerosols, and by direct contact. By housing ferrets under different conditions, it is possible to mimic various routes of transmission. Here, we inoculated donor animals with a mixture of two viruses whose genomes differed by one or two reverse engineered synonymous mutations, and measured the transmission of the mixture to exposed sentinel animals. Transmission through the air imposed a tight bottleneck since most recipient animals became infected by only one virus. In contrast, a direct contact transmission chain propagated a mixture of viruses suggesting the dose transferred by this route was higher. From animals with a mixed infection of viruses that were resistant and sensitive to the antiviral drug oseltamivir, resistance was propagated through contact transmission but not by air. These data imply that transmission events with a looser bottleneck can propagate minority variants and may be an important route for influenza evolution.

Information on the immunopathobiology of coronavirus disease 2019 (COVID-19) is rapidly increasing; however, there remains a need to identify immune features predictive of fatal outcome. This large-scale study characterized immune responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection using multidimensional flow cytometry, with the aim of identifying high-risk immune biomarkers. Holistic and unbiased analyses of 17 immune cell-types were conducted on 1,075 peripheral blood samples obtained from 868 COVID-19 patients and on samples from 24 patients presenting with non-SARS-CoV-2 infections and 36 healthy donors. Immune profiles of COVID-19 patients were significantly different from those of age-matched healthy donors but generally similar to those of patients with non-SARS-CoV-2 infections. Unsupervised clustering analysis revealed three immunotypes during SARS-CoV-2 infection; immunotype 1 (14% of patients) was characterized by significantly lower percentages of all immune cell-types except neutrophils and circulating plasma cells, and was significantly associated with severe disease. Reduced B-cell percentage was most strongly associated with risk of death. On multivariate analysis incorporating age and comorbidities, B-cell and non-classical monocyte percentages were independent prognostic factors for survival in training (n=513) and validation (n=355) cohorts. Therefore, reduced percentages of B-cells and non-classical monocytes are high-risk immune biomarkers for risk-stratification of COVID-19 patients.