Viruses pose a significant threat to human health based on their ability to cause diseases such as AIDS, influenza, hepatitis, cancer and the common cold. Basic research has revealed much about the molecular details of processes that are essential for viruses to reproduce, but a critical barrier to further progress is a lack of understanding of how factors of the host environment quantitatively impact virus growth. The proposed research aims to address this barrier by advancing new quantitative experiments and computational models of virus growth. The approach will employ, combine and extend perspectives drawn from the fields of experimental evolution and systems biology.
Specific aims of the proposed project will be to: (1) advance computational models of virus growth to provide an integrated dynamic measure of cellular resource use, (2) quantify how resource use is altered during evolutionary adaptation of virus to host cells, and (3) elucidate mechanisms by which viral adaptation alters resource use. The methodology established by this research will set a basis for advancing the development of data-driven predictive models of virus growth. Results of the research will have the potential to significantly impact several fields: the design anti-viral therapeutics, applications of viruses in oncolytic (anti-tumor) cancer therapies, and development of new vaccines. At a more basic level, predictive models of virus growth will be useful for better understanding how viruses grow, evolve and persist in Nature.

Public Health Relevance

Viruses cause a diversity of human diseases including AIDS, influenza, cancer, hepatitis, and the common cold. The proposed research develops new experimental and computational approaches to study and understand how viruses grow. The broad goal of this research is to learn how to better fight diseases caused by viruses. Their work some concerns which serve to spread the enthusiasm somewhat, nevertheless, it came to rest in the exceptional range.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
Program Officer
Cassetti, Cristina
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University of Wisconsin Madison
Engineering (All Types)
Schools of Engineering
United States
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Yin, John; Redovich, Jacob (2018) Kinetic Modeling of Virus Growth in Cells. Microbiol Mol Biol Rev 82:
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