Viral infections in the lower respiratory tract cause severe disease and are responsible for a majority of pediatric hospitalizations. Molecular diagnostic assays have revealed that approximately 20% of these patients are infected by more than one viral pathogen. Clinical data indicate that disease severity can be enhanced, reduced or be unaffected by viral co-infection. However, it is not clear how unrelated viruses interact within the context of a complex host to determine disease severity. The long-term goal of this research is to uncover the causal relationships between co-infection and the resulting respiratory disease severity. Variables that will potentially predict disease severity include viral strains, doses, timing, viral competition, genetic variation in the host, and the immune response. The proposed research will develop a murine model with cellular and organismal components and a human in vitro model to test the central hypothesis that respiratory viral co- infections change disease severity both by direct viral interactions and by modulating host responses. Statistical and stochastic modeling will reveal the complex interactions between heterologous viruses within their shared target cells and host organisms.
In Aim 1, a mouse strain that exhibits mild, moderate, or severe disease when infected with three respiratory viruses individually will be infected with pairwise combinations of these viruses as concurrent and sequential co-infections. Co-infection variables that lead to differences in morbidity and mortality compared to individual virus infections will be identified. Pathology response variables, including viral loads, inflammatory cells, and histopathology will be analyzed and statistical models will be developed to reveal how both infection variables and pathology response variables predict disease severity during co-infection. Lung transcriptome analysis and complex systems modeling will be used to elucidate mechanisms of host responses that result in differing disease outcomes during co-infection.
In Aim 2, viral co- infections will be performed in respiratory epithelial cells in vitro, to determine the effects of co-infection on viral growth dynamics and the response of infected cells. This will reveal the complex interactions between co- infecting viruses within their shared target cells in the respiratory tract. Parallel experiments in murine and human cell lines will test the generality of our findings and may allow us to make predictions about how viral co-infections affect disease severity in humans. Completion of the project aims will result in understanding how interactions between co-infecting viruses, their target cells, and the immune system dictate disease severity during respiratory viral co-infections. Modeling these complex interactions will lead to testable hypotheses about the mechanisms that regulate disease severity during infection by heterologous respiratory viruses.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory Grants (P20)
Project #
5P20GM104420-03
Application #
9233168
Study Section
Special Emphasis Panel (ZGM1-TWD-A)
Project Start
Project End
Budget Start
2017-02-01
Budget End
2018-01-31
Support Year
3
Fiscal Year
2017
Total Cost
$288,602
Indirect Cost
$86,962
Name
University of Idaho
Department
Type
Domestic Higher Education
DUNS #
075746271
City
Moscow
State
ID
Country
United States
Zip Code
83844
Dutta, Rabijit; Xing, Tao; Swanson, Craig et al. (2018) Comparison of flow and gas washout characteristics between pressure control and high-frequency percussive ventilation using a test lung. Physiol Meas 39:035001
Li, Longze; Vakanski, Aleksandar (2018) Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement Episodes. Int J Mach Learn Comput 8:428-436
Rowley, Paul A; Patterson, Kurt; Sandmeyer, Suzanne B et al. (2018) Control of yeast retrotransposons mediated through nucleoporin evolution. PLoS Genet 14:e1007325
Vakanski, Aleksandar; Jun, Hyung-Pil; Paul, David et al. (2018) A Data Set of Human Body Movements for Physical Rehabilitation Exercises. Data (Basel) 3:
Damase, Tulsi Ram; Miura, Tanya A; Parent, Christine E et al. (2018) Application of the Open qPCR Instrument for the in Vitro Selection of DNA Aptamers against Epidermal Growth Factor Receptor and Drosophila C Virus. ACS Comb Sci 20:45-54
Baumgaertner, Bert; Carlisle, Juliet E; Justwan, Florian (2018) The influence of political ideology and trust on willingness to vaccinate. PLoS One 13:e0191728
Miller, Craig R; Van Leuven, James T; Wichman, Holly A et al. (2018) Selecting among three basic fitness landscape models: Additive, multiplicative and stickbreaking. Theor Popul Biol 122:97-109
Baumgaertner, Bert O; Fetros, Peter A; Krone, Stephen M et al. (2018) Spatial opinion dynamics and the effects of two types of mixing. Phys Rev E 98:022310
Garry, Daniel J; Ellington, Andrew D; Molineux, Ian J et al. (2018) Viral attenuation by engineered protein fragmentation. Virus Evol 4:vey017
Bull, James J; Christensen, Kelly A; Scott, Carly et al. (2018) Phage-Bacterial Dynamics with Spatial Structure: Self Organization around Phage Sinks Can Promote Increased Cell Densities. Antibiotics (Basel) 7:

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