Summary: | Influenza virus tissue tropism defines the host cells and tissues that support viral replication and contributes to determining which regions of the respiratory tract are infected in humans. The location of influenza virus infection along the respiratory tract is a key determinant of virus pathogenicity and transmissibility, which are at the basis of influenza burdens in the human population. As the pathogenicity and transmissibility of influenza virus ultimately determine its reproductive fitness at the population level, strong selective pressures will shape influenza virus tissue tropisms that maximize fitness. At present, the relationships between influenza virus tissue tropism within hosts and reproductive fitness at the population level are poorly understood. The selective pressures and constraints that shape tissue tropism and thereby influence the location of influenza virus infection along the respiratory tract are not well characterized. We use mathematical models that link within-host infection dynamics in a spatially-structured human respiratory tract to between-host transmission dynamics, with the aim of characterizing the possible selective pressures on influenza virus tissue tropism. The results indicate that spatial heterogeneities in virus clearance, virus pathogenicity or both, resulting from the unique structure of the respiratory tract, may drive optimal receptor binding affinity--that maximizes influenza virus reproductive fitness at the population level--towards sialic acids with α2,6 linkage to galactose. The expanding cell pool deeper down the respiratory tract, in association with lower clearance rates, may result in optimal infectivity rates--that likewise maximize influenza virus reproductive fitness at the population level--to exhibit a decreasing trend towards deeper regions of the respiratory tract. Lastly, pre-existing immunity may drive influenza virus tissue tropism towards upper regions of the respiratory tract. The proposed framework provides a new template for the cross-scale study of influenza virus evolutionary and epidemiological dynamics in humans.
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