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Epstein-Barr: A Virtual Look At A Vexing Virus

Date:
October 23, 2007
Source:
Tufts University, Health Sciences
Summary:
Researchers have created a computer model called Pathogen Simulation to study the sometimes deadly Epstein-Barr virus, which infects greater than 90 percent of the world's population. Researchers hope to determine why some infected patients fall ill while others show no symptoms.
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Researchers at Tufts University School of Medicine in collaboration with the Virginia Bioinformatics Institute at Virginia Tech have created a computer program called Pathogen Simulation (PathSim) to study the progression of Epstein-Barr virus (EBV) in humans.

David Thorley-Lawson, PhD, professor of pathology at Tufts University School of Medicine, is combining PathSim, laboratory methods, and clinical studies to provide a new and powerful approach to understanding EBV and ultimately designing anti-viral therapies.

"PathSim is an agent-based computer program. The agents are the virus itself, and the T and B cells of the patient's immune system," explains Thorley-Lawson. Using PathSim, Thorley-Lawson can manipulate these agents to simulate EBV infection and persistence in humans. "EBV can infect one person and remain latent -- not cause any symptoms. It can infect another person and cause infectious mononucleosis, or, in rare cases, cancer, like Hodgkin's, Burkitt's, and immunoblastic lymphomas," says Thorley-Lawson.

"Scientists can use PathSim like a video game and change variables, such as number of virus particles or characteristics of the patient's immune cells, to follow the course of disease and observe what drives the virus to either latency or illness.

We validated PathSim by comparing it to EBV infection in patients," says Thorley-Lawson. "For example, PathSim projected that the peak in the number of infected immune cells, called B cells, would occur 33 through 38 days post-infection, which is consistent with the peak of 35 through 50 days actually seen in infected patients. This consistency is important because it validates the predictive power of PathSim; the power to reveal what EBV is doing in a patient's body," says Thorley-Lawson.

"It takes one full week to run one simulation," says Thorley-Lawson. "Then we compile the data and look for critical switch points of disease." A switch point is a small change in the behavior of an agent that can influence the progression of disease. Such a change may determine whether the virus persists in the body in a latent state, or causes illness and even death by replicating out of control.

"Once these critical switch points are understood, biologists may be able to develop drugs that target specific points in the interaction between the virus and immune system at specific times," explains Thorley-Lawson. "The more targeted the drug, the more safe and effective the resulting therapy. We hope that this marriage of computers and biology will eventually lead to better patient treatment against EBV."

The study was supported by the National Institute of Allergy and Infectious Diseases and the National Cancer Institute of the National Institutes of Health.

Reference: Duca KA, Shapiro M, Delgado-Eckert E, Hadinoto V, Jarrah AS, Laubenbacher R, Lee K, Luzuriaga K, Polys NF and Thorley-Lawson DA. PLoS Pathogens. 2007 (October);3(10): e137. "A Virtual Look at Epstein-Barr Virus Infection: Biological Interpretations."


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Materials provided by Tufts University, Health Sciences. Note: Content may be edited for style and length.


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Tufts University, Health Sciences. "Epstein-Barr: A Virtual Look At A Vexing Virus." ScienceDaily. ScienceDaily, 23 October 2007. <www.sciencedaily.com/releases/2007/10/071022120216.htm>.
Tufts University, Health Sciences. (2007, October 23). Epstein-Barr: A Virtual Look At A Vexing Virus. ScienceDaily. Retrieved April 26, 2024 from www.sciencedaily.com/releases/2007/10/071022120216.htm
Tufts University, Health Sciences. "Epstein-Barr: A Virtual Look At A Vexing Virus." ScienceDaily. www.sciencedaily.com/releases/2007/10/071022120216.htm (accessed April 26, 2024).

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