Modeling T Cells

Children born without thymus glands have given Duke researchers a rare opportunity to study how a new immune system develops its population of infection-fighting T cells.

Interdisciplinary research at the medical center led by Thomas Kepler, division chief of computational biology and professor of bioinformatics and biostatistics at Duke Medical School, tracked three such young patients after thymus tissue transplantation. (Duke has pioneered thymus transplantation for children born with DiGeorge Syndrome, a rare congenital disease marked by a missing thymus gland.)

Kepler, along with colleague Stanca Ciupe, a postdoctoral fellow in the Duke Laboratory of Computational Immunology, collaborated with M. Louise Markert M.D. '79, Ph.D. '81, professor of pediatrics and director of the Laboratory of Thymus Transplantation, on the research.

"What we haven't understood until now is how maintaining the diversity of T cells with different receptors works while a body also maintains appropriate T cell numbers overall," Kepler says. "Our paper is the first to use information about changes in T cell receptor diversity to infer properties of the T cell regulatory mechanisms."

Ciupe, lead author on the study, created mathematical formulas to model how T cells grow and diversify.

"What is novel is our ability to take the results from assays and quantify them to get a numerical measure of diversity, to get a picture of what really happens when T cells mature," Ciupe says. "Secondly, we were able to develop a mathematical model to feed the data into."

By applying mathematics to biological systems and engineering, researchers will continue to develop new applications for humans, such as better vaccines.

"So much scientific work is done in model organisms, but we can't manipulate humans in those ways," Kepler says. "This paper shows that with more sophisticated mathematical tools, you can get the information you need to learn about human biology" without needing human research subjects.

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