Influenza viruses emerge unpredictably from their reservoirs in aquatic birds to cause pandemics in humans. The processes by which avian influenza viruses adapt to replication and transmission in mammals has been the subject of intense study, with much work focused on identifying specific molecular determinants that con- fer mammalian-transmissible phenotypes. Dr. Friedrich?s group uses deep sequencing to focus not on specific mutations, but rather on the evolutionary processes by which host-adapting changes in influenza viruses are generated and selected. This work has shown that natural selection on hemagglutinin (HA) can impose a significant genetic bottleneck on avian influenza viruses during transmission between mammals. In parallel, Dr. Mehle?s group developed a novel bioluminescent reporter virus that allows for direct in-vivo imag- ing of influenza replication in ferrets. This work revealed that airborne transmission can result in infection of distinct respiratory tract compartments in different animals. Such localized replication suggests that airborne transmission is subject to physical constraints that could act to randomly reduce viral genetic diver- sity. Indeed, it has become clear that airborne transmission of influenza viruses is associated with a genetic bottleneck, a previously unappreciated determinant of host adaptation by influenza viruses. The transmis- sion bottleneck has been variously reported to be governed by random events or by natural selection on viral genes. The relative contributions of selective and random processes to the transmission bottleneck profoundly influence the rate of influenza viral evolution: Strong selective effects would effectively amplify fit variants from within the viral swarm. If random effects predominate, low-frequency fit variants would likely be lost to genetic drift before they find a susceptible host. We present here a conceptual model that unifies previous findings on influenza transmission bottlenecks, and suggests that strongly selective bottlenecks are signature features of viruses in transition from avian to mammalian phenotypes. This project will bring together a unique team of multidisciplinary investigators with expertise in viral ge- nomics, virology, and molecular evolution to test predictions from this model and understand the mechanisms that govern the influenza transmission bottleneck. The project has 2 complementary, but distinct aims:
Aim 1 will determine the nature of bottlenecks during transmission of a mammal-adapted 2009 H1N1 pandemic (H1N1pdm) virus.
Aim 2 will define how transmission bottlenecks impact selection as viruses encoding an avian-style HA adapt to mammalian hosts. If our hypothesis is correct, deep sequencing viruses causing human spillover infections to detect signatures of selection during transmission would provide a novel and rapid means for assessing pan- demic risks.

Public Health Relevance

Avian influenza viruses like H5N1 and H7N9 do not frequently infect humans, but when they do, they cause serious disease and death. So far, such viruses have not evolved the ability to be easily transmitted between humans, but if they do, they could cause a major pandemic. We have shown that influenza virus transmission between mammals is associated with a drastic reduction in viral genetic diversity?a bottleneck. This project aims to understand the viral and host factors that influence this bottleneck and determine how bottlenecks affect the ability of influenza viruses to jump from from birds to mammals.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI125392-03
Application #
9613786
Study Section
Virology - B Study Section (VIRB)
Program Officer
Hauguel, Teresa M
Project Start
2017-01-01
Project End
2021-12-31
Budget Start
2019-01-01
Budget End
2019-12-31
Support Year
3
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Type
Schools of Veterinary Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
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Weger-Lucarelli, James; Garcia, Selene M; Rückert, Claudia et al. (2018) Using barcoded Zika virus to assess virus population structure in vitro and in Aedes aegypti mosquitoes. Virology 521:138-148