Eipstein-Barr virus (EBV) infects more than 90% of all humans, usually without symptoms. It can also be responsible for acute infectious mononucleosis (AIM) and is associated with fatal malignancies including immunoblastic lymphoma, Hodgkin's lymphoma, Burkitt's lymphoma, nasopharyngeal carcinoma and X-linked proliferative disorder (XLP). Our long-term goal is to understand these processes in sufficient detail to guide clinical intervention. Our overall model of normal and malignant EBV biology puts us in a good position to build computer models of EBV infection.
Our specific aims i nclude the following: Evaluate the relative impacts of various factors known to play a role in EBV biology. Assess the probability of the varying fates of a cell once it has entered a particular infected state. Understand the overall dynamics of these models as dynamical systems. This includes distinguishing possible long-term behaviors and the transitory states that lead to them. We will pursue these goals by building and analyzing multiple light weight computer models of EBV infection. By "light weight" we mean that these models are easy to write, modify and run. This will allow investigations not possible with larger agent-based computer models. Epstein-Barr Virus is widespread in the human population. While it is usually asymptomatic, it is also associated with fatal malignancies. Computer simulation is a way to study the normal asymptomatic course of this infection and the ways in which this turns malignant. We hope that a better understanding of these processes will show us how they can be controlled.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
5K25AI079404-05
Application #
8304955
Study Section
Microbiology and Infectious Diseases B Subcommittee (MID)
Program Officer
Beisel, Christopher E
Project Start
2008-09-01
Project End
2014-02-28
Budget Start
2012-08-01
Budget End
2014-02-28
Support Year
5
Fiscal Year
2012
Total Cost
$124,632
Indirect Cost
$9,232
Name
Tufts University
Department
Pathology
Type
Schools of Medicine
DUNS #
039318308
City
Boston
State
MA
Country
United States
Zip Code
02111
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Hawkins, Jared B; Delgado-Eckert, Edgar; Thorley-Lawson, David A et al. (2013) The cycle of EBV infection explains persistence, the sizes of the infected cell populations and which come under CTL regulation. PLoS Pathog 9:e1003685
Floyd, William; Kay, Leslie; Shapiro, Michael (2012) A covering-graph approach to epidemics on SIS and SIS-like networks. Bull Math Biol 74:175-89
Shapiro, Michael D; Bagley, Jessamyn; Latz, Jeff et al. (2011) MicroRNA expression data reveals a signature of kidney damage following ischemia reperfusion injury. PLoS One 6:e23011
Delgado-Eckert, Edgar; Shapiro, Michael (2011) A model of host response to a multi-stage pathogen. J Math Biol 63:201-27
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Hadinoto, Vey; Shapiro, Michael; Sun, Chia Chi et al. (2009) The dynamics of EBV shedding implicate a central role for epithelial cells in amplifying viral output. PLoS Pathog 5:e1000496
Holt, Derek F; Rees, Sarah; Shapiro, Michael (2008) GROUPS THAT DO AND DO NOT HAVE GROWING CONTEXT-SENSITIVE WORD PROBLEM. Int J Algebra Comput 18:1179-1191
Goodman, Oliver; Shapiro, Michael (2008) ON A GENERALIZATION OF DEHN'S ALGORITHM. Int J Algebra Comput 18:1137-1177