Computational Models of Ex Vivo HIV-1 Dynamics and Fitness Across Scales

When modeling multicellular systems, we are often interested in mapping collective macroscopic behavior to cell level characteristics, and vice versa. One of the difficulties in bridging cell level and macroscopic scales is how to interpret the meaning of model parameters when moving from one scale to another. We explore this issue in the context of growth competition assays, used to quantify the ex vivo replicative fitness of two HIV-1 isolates, by developing cell level and macroscopic models, and investigating the relationship between the model parameters at the different scales. We present a detailed, spatially distributed, hybrid stochastic-deterministic cell level model of the dynamics of two competing virus variants, and use it to perform in silico growth competition experiments to better understand how the characteristics of a virus strain influence its ex vivo fitness. To move from the cell level to the macroscopic level, we approximate the cell level model with low resolution and high resolution deterministic macroscopic models, which do not account for cell level biological details or spatial structure. To establish a link between the models at the different scales, we generate data with our cell level model by simulating growth competition experiments between two virus variants with different characteristics, and estimate the parameters of the two macroscopic models from the simulated data sets, approaching the parameter estimation problem from the Bayesian perspective. We investigate how well the macroscopic models specified by the estimated parameters are able to explain the data, and elucidate the intricacies of inferring underlying virus characteristics from macroscopic kinetics by exploring how the parameters of the cell level model relate to those of its macroscopic approximations.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Applied Mathematics

Grantor dc:publisher

Case Western Reserve University School of Graduate Studies

Year dc:date

2013

Author dc:creator

• Immonen, Taina Tuulia

Contributors dc:contributor

• Calvetti, Daniela
• Somersalo, Erkki

• Applied Mathematics

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=case1365173809

OAI identifier oai:identifier

oai:etd.ohiolink.edu:case1365173809