Avian influenza virus h3 hemagglutinin may enable high fitness of novel human virus reassortants.

Reassortment of influenza A virus genes enables antigenic shift resulting in the emergence of pandemic viruses with novel hemagglutinins (HA) acquired from avian strains. Here, we investigated whether historic and contemporary avian strains with different replication capacity in human cells can donate their hemagglutinin to a pandemic human virus. We performed double-infections with two avian H3 strains as HA donors and a human acceptor strain, and determined gene compositions and replication of HA reassortants in mammalian cells. To enforce selection for the avian virus HA, we generated a strictly elastase-dependent HA cleavage site mutant from A/Hong Kong/1/68 (H3N2) (Hk68-Ela). This mutant was used for co-infections of human cells with A/Duck/Ukraine/1/63 (H3N8) (DkUkr63) or the more recent A/Mallard/Germany/Wv64-67/05 (H3N2) (MallGer05) in the absence of elastase but presence of trypsin. Among 21 plaques analyzed from each assay, we found 12 HA reassortants with DkUkr63 (4 genotypes) and 14 with MallGer05 (10 genotypes) that replicated in human cells comparable to the parental human virus. Although DkUkr63 replicated in mammalian cells at a reduced level compared to MallGer05 and Hk68, it transmitted its HA to the human virus, indicating that lower replication efficiency of an avian virus in a mammalian host may not constrain the emergence of viable HA reassortants. The finding that HA and HA/NA reassortants replicated efficiently like the human virus suggests that further HA adaptation remains a relevant barrier for emergence of novel HA reassortants.

A stochastic model for estimation of mutation rates in multiple-replication proliferation processes.

In this paper we propose a stochastic model based on the branching process for estimation and comparison of the mutation rates in proliferation processes of cells or microbes. We assume in this model that cells or microbes (the elements of a population) are reproduced by generations and thus the model is more suitably applicable to situations in which the new elements in a population are produced by older elements from the previous generation rather than by newly created elements from the same current generation. Cells and bacteria proliferate by binary replication, whereas the RNA viruses proliferate by multiple replication. The model is in terms of multiple replications, which includes the special case of binary replication. We propose statistical procedures for estimation and comparison of the mutation rates from data of multiple cultures with divergent culture sizes. The mutation rate is defined as the probability of mutation per replication per genome and thus can be assumed constant in the entire proliferation process. We derive the number of cultures for planning experiments to achieve desired accuracy for estimation or desired statistical power for comparing the mutation rates of two strains of microbes. We establish the efficiency of the proposed method by demonstrating how the estimation of mutation rates would be affected when the culture sizes were assumed similar but actually diverge.