Abstract
Experiments have generated a plethora of data about the genes, molecules, and cells involved in thymocyte development. Here, we use a computer-driven simulation that uses data about thymocyte development to generate an integrated dynamic representation—a novel technology we have termed reactive animation (RA). RA reveals emergent properties in complex dynamic biological systems. We apply RA to thymocyte development by reproducing and extending the effects of known gene knockouts: CXCR4 and CCR9. RA simulation revealed a previously unidentified role of thymocyte competition for major histocompatability complex presentation. We now report that such competition is required for normal anatomical compartmentalization, can influence the rate of thymocyte velocities within chemokine gradients, and can account for the disproportion between single-positive CD4 and CD8 lineages developing from double-positive precursors.
Highlights
The mammalian thymus receives stem cells from the bone marrow
reactive animation (RA) uses a bottom-up integration of diverse experimental data to create an integrated and dynamic representation of the system’s interacting cells and molecules
We report that competition between thymocytes for sites of stimulation could be important in generating the fine anatomy of the thymus, in selecting for thymocytes with a range of migration velocities, and in explaining the paradox of CD4 to CD8 T cell lineage ratios
Summary
The mammalian thymus receives stem cells from the bone marrow. These cells—thymocytes—go through a series of anatomical subcompartments in a process termed T cell education [1,2]. Subfields of thymus research include genes, gene expression and differentiation; molecules (integrins, chemokines, cytokines, receptors, antigens, and other ligands); cells (stem cells, thymocytes, epithelial cells, dendritic cells, and macrophages); cell behavior (adhesion, migration, and anatomic localization); cell states (differentiation states, cell cycle, proliferation, and apoptosis); and physiology (antigen expression, positive and negative selection, lineage choice, and antigenreceptor repertoires). A systematic integration of these data into an accurate and comprehensive representation is much needed. We address this need using reactive animation (RA) to reveal multiscalar emergent properties and to guide experimentation in thymocyte development
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