Emergent dynamics of thymocyte development and lineage determination

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.

Figure 1. A Snapshot of the Simulated Thymus at Run Time

(A) Different colors stand for different stages during thymocyte selection. The legend box shows the different developmental stages and their corresponding colors. (B) Different icons beneath the figure stand for different tools for the control and the visualization of the simulation. The tools include the ability to zoom into parts of the visualization, show and hide the two tiers of the simulation, highlight interacting cells, display or hide chemokine gradients, display statistical information through real-time communication with Matlab, visualize apoptotic levels in real-time, initiate and stop a backtrack of a cell's migration, and more. (A,B) In the lower right hand side, the elapsed time is displayed, together with a utility that enables the control of time progression.

Figure 2. A Trace of the Path of a Single Thymocyte from Its Birth via Proliferation at the SCZ to Its Position as a Mature Cell in the Medulla

We generate the visual trace by utilizing the built-in tracing tool. The trace is color-coded: the current time is highlighted in red and the beginning of the trace is enriched with blue. Intermediate times are marked as mixtures of these two colors on the trace line.

Figure 3. Comparing a Knockout to a Wild-Type Thymus

(A) The left panel shows a figure borrowed from [19] of the effect of a CXCR4 knockout. The right panel was taken from the simulation. Red-colored cells in this right panel correspond to DN cells. The thymocytes in the experimental system, marked red fluorescence, remain very close to the CMJ, where they first entered the thymus, which is situated at the lower right corner of the plate. (B) A wild-type thymus (labeled lck[Cre]) shows thymocytes scattered throughout the thymic lobule both in the experimental plate from [19] on the right, and in its in silico equivalent on the left. The blue cells correspond to DP cells. DN cells and DP cells spread throughout the thymus in a normal fashion.

Figure 4. The Effect of Knocking Out CCR9 in Thymocytes

(A) Shows the distribution of wild-type cells (color coded as in Figure 1). (B) Shows the altered distribution of the knockout cells (colored gray). The normal cells and the altered cells are colored differently to be compatible with Video S2, where we show the results of a competition experiment between the different cell types. The major differences are in the abilities of thymocytes to migrate from the SCZ into the cortex, after maturation from pre-DP stages. This altered behavior is responsible for the diluted numbers of thymocytes in the cortex of the knockout thymuses.

Figure 5. Competition In Silico between CCR9−/− Cells and Wild-Type Cells

The three panels at the bottom, with context lines leading to the time-graph, show the ratios between the two cell populations developing over time. An initial peak of maturing wild-type cells is followed by a decrease and an eventual asymptotic ratio, as the buildup of random pressure of CCR9−/− cells eventually generates homeostasis. An asymptotic value of four wild-type thymocytes to every CCR9−/− thymocyte is reached. See text for further discussion.

Figure 6. The Influence of Competition on the Pattern of Apoptosis in the Thymus

We visualize the different levels of apoptosis by using different colors to show the relative numbers of apoptosing cells across the thymic grid. Red zones correspond to higher levels of apoptosis. (A) Shows the normal distribution of apoptosis primarily to the SCZ; some apoptosis is seen in the outer cortex (OC) and some in the medulla (M); the inner cortex (IC) and CMJ show relatively fewer apoptotic cells. (B) Shows the influence of removing competition between thymocytes for developmental niches. The lack of competition moves the bulk of apoptosis from the SCZ to the CMJ and the M zones. In the wild-type thymus, most of the cells die in their DP stages, in the cortex, and in the SCZ. This is in agreement with experimental results, where only 10% of cells survive to the SP stage (see review; [30]). In contrast, in the altered thymus displayed in (B), most of the cells survive to the SP stage and die in the medulla of negative selection.

Figure 7. Histogram of the Different Migration Velocities of Thymocytes

The faster cells are more likely to survive thymic selection by contacting the process of an epithelial cell; but slower cells also can have an advantage (see text).

Figure 8. Influence of CD4 and CD8 Dissociation Rates on Lineage Commitment Ratio

Measuring the ratio of CD4 mature cells to CD8 mature cells, in silico, as a function of the dissociation rate, we find that to achieve the experimentally measured 2:1 ratio, the dissociation rate of CD8 cells should be anywhere between 0.38 to 0.45 that of CD4 thymocytes. The expanded insert zooms in on this zone, which produces the experimentally observed ratio of two CD4 cells for every CD8 cell. Figure 8 shows that an increase in the dissociation rate of CD8 over CD4 could result in a CD4:CD8 population equilibrium, or even to overpopulation of the thymus with CD8 cells, depending on the relative dissociation rate.