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Interactions between the immune system, influenza A virus, and bacterial pneumonia

Keef , Ericka (2016) Interactions between the immune system, influenza A virus, and bacterial pneumonia. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Influenza and pneumonia continue to be leading causes of morbidity and mortality in the United States each year. These pathogens can be lethal on their own, but they are particularly dangerous if encountered simultaneously in an influenza-pneumonia superinfection. The severity of the infection can be controlled by the strength of the host’s immune response, which is often dependent on the age and species of the host. In this work, the intrahost immune response to respiratory infections is explored with mathematical modeling. We first examine how different species of mice react to an identical Streptococcus pneunoniae infection. A low-order ordinary differential equation (ODE) model is used to model data from four strains of mice, each of which represents a distinct phenotype in response to the infection. By changing only a small number of parameters, representing variations in the strength of the immune response, the output of the model can change significantly. We next examine the complementary study, in which the host species remains constant but the strain of bacteria administered is different. Again adjusting only a few parameters in our small ODE model, we can again reproduce several phenotypes of responses to these varied infections. We then examine the immune response to influenza infection. First, we develop a large ODE model to fit to data from mice infected with either a sublethal or lethal dose of H1N1. The model is the first of its kind to include a detailed study of the inflammatory response to infection. Next we use a Boolean network model to study data taken from adult and elderly mice infected with influenza to assess differences in the immune response that arise with age. Finally, we propose an ODE model of influenza-pneumonia superinfection. In each of these five studies, we discuss the implications of our work for further experiments and identify potential avenues for future research.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Keef , Erickaedm29@pitt.eduEDM290000-0002-3804-387X
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairSwigon, Davidswigon@pitt.eduSWIGON
Committee MemberClermont, Gillescler@pitt.eduCLER
Committee MemberLangmead, Christopher Jlangmead@pitt.eduLANGMEAD
Committee MemberErmentrout, Bardbard@pitt.eduBARD
Date: 6 June 2016
Date Type: Publication
Defense Date: 4 April 2016
Approval Date: 6 June 2016
Submission Date: 14 April 2016
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 211
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Computational Biology
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: influenza; pneumonia; mathematical modeling; viral kinetics; ordinary differential equations; Boolean model; rule-based model
Date Deposited: 06 Jun 2016 18:55
Last Modified: 15 Nov 2016 14:32
URI: http://d-scholarship.pitt.edu/id/eprint/27702

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