Characterizing the dynamics of CD4+ T cell priming within a lymph node

Abstract

Generating adaptive immunity postinfection or immunization requires physical interaction within a lymph node T zone between Ag-bearing dendritic cells (DCs) and rare cognate T cells. Many fundamental questions remain regarding the dynamics of DC-CD4+ T cell interactions leading to priming. For example, it is not known how the production of primed CD4+ T cells relates to the numbers of cognate T cells, Ag-bearing DCs, or peptide-MHCII level on the DC. To address these questions, we developed an agent-based model of a lymph node to examine the relationships among cognate T cell frequency, DC density, parameters characterizing DC-T cell interactions, and the output of primed T cells. We found that the output of primed CD4+ T cells is linearly related to cognate frequency, but nonlinearly related to the number of Ag-bearing DCs present during infection. This addresses the applicability of two photon microscopy studies to understanding actual infection dynamics, because these types of experiments increase the cognate frequency by orders of magnitude compared with physiologic levels. We found a trade-off between the quantity of peptide-major histocompatibility class II on the surface of individual DCs and number of Ag-bearing DCs present in the lymph node in contributing to the production of primed CD4+ T cells. Interestingly, peptide-major histocompatibility class II t(1/2) plays a minor, although still significant, role in determining CD4+ T cell priming, unlike the primary role that has been suggested for CD8+ T cell priming. Finally, we identify several pathogen-targeted mechanisms that, if altered in their efficiency, can significantly effect the generation of primed CD4+ T cells.

Figure 1

Model schematics and rules. (a) The model represents events occurring in the T-zone of the LN, a region in which naïve T cells and DCs have an opportunity to interact. (b) The model geometry is a section of LN represented by a lattice of 25×200 micro-compartments, a section of which is diagrammed here. Cells move onto, off of, and around on the grid. T cells and DCs enter the grid via the high endothelial venules and afferent lymphatics, respectively. Cells can move to any adjacent square and also can divide. The larger DCs occupy an entire square, while up to 4 T cells (which are much smaller) can occupy a single square. Cells in adjacent squares can interact. T cells leave the grid via medullary sinuses that collect into efferent lymphatic vessels. (c) Shown are possible cell-cell interactions. Interaction of an Ab-DC or LDC with a cognate naïve CD4+ T cell can give rise to a primed CD4+ T cell (see also Fig. 3). Similarly, interaction of an LDC with a cognate naïve CD8+ T cells can give rise to a primed CD8+ T cell. The interaction of an Ab-DC with a primed CD4+ T cell can produce a LDC, and the interaction of an Ab-DC or LDC with an IDC can produce an Ab-DC. Finally, LDCs can also license Ab-DCs.

Figure 2

Simulation snapshots. An enlarged view of a portion of the LN simulation grid is shown. High endothelial venules (red triangles), afferent lymphatics (white cylinders) and medullary sinuses (grey cylinders) are indicated; these are the entrance and exit ports for cells. Individual cells are shown as circles of various colors. See legend for details. 138:24 represents the time the snapshot was taken in hours and minutes.

Figure 3

Interaction of an antigen-bearing dendritic cell (Ab-DC) with a cognate naïve T CD4+ cell can result in binding and priming of a T cell. Shown are the sigmoid relationships used in the model (more details and equations are given in the Supplement 1). Binding probability is assumed to be a function of the number of pMHCII displayed by the Ab-DC; the curve is characterized by the binding threshold and binding shape parameters. Binding threshold defines the number of pMHCII at which the binding probability is 50%; binding shape describes the slope of the binding probability vs. pMHCII level curve at that point. Priming (of a CD4+ T cell already bound to an Ab-DC) is assumed to be a function of the product of pMHCII and time; the curve is characterized by the priming threshold and priming shape parameters.

Figure 4

Acute and chronic infection scenarios. The cartoons along the top indicate the flow of cells into, on and out of the LN and correspond to the plots below. (a, e) Cumulative number of DCs that have entered the LN. (b,f) Numbers of each population of DCs in the LN during the infection. In (b), experimental data on the total number of DC in a human LN at particular times (66) is shown for comparison. (c,g) Cumulative number of primed CD4+ T cells exiting the LN. (d,h) Cumulative number of primed CD8+ T cells exiting the LN. In (c,d), experimental data from a mouse spleen are shown for comparison (64). No measure of variability (e.g. standard deviation) is available for these data. Model parameter values used are from Table I with 60% Ab-DCs, cognate frequency 1:300, pMHC half-life 60 h.

Figure 5

Simulation of primed CD4+ T cell production during chronic infection (i.e. input of DCs is constant). (a) Cumulative (14 day) output of primed CD4+ T cells from the LN as a function of % Ab-DC by differing cognate frequencies (denoted Cog in the figure legend). (b) Data in (a) re-plotted as the ratio of the cumulative primed CD4+ T cell output to the number of naïve cognate CD4+ T cells entering the LN for different cognate frequencies. (c) Simulations results as in (b) but for the case of no licensing of DCs. (d) Average match percentage, search time and transit time for cognate CD4+ T cells entering the LN for the simulations shown in (a,b). Standard deviations are also given. Data in (d) are averaged across all cognate frequencies as differences between cognate frequency were not statistically significant for these outputs. Simulation parameter values are found in Table I.

Figure 6

Trade-off between initial pMHC levels on DCs and % Ab-DC affect primed CD4+ T cell production. Pairs of values of the % Ab-DCs and the number of pMHCII per Ab-DC that gave the same cumulative (14 day) output of primed CD4+ T cells are plotted. Cognate frequency 1:3000 (100 cumulative primed CD4+ T cells at day 14, solid line) and cognate frequency 1:300 (500 cumulative primed CD4+ T cells at day 14, dashed line) are shown. See methods for more details of how these plots are generated.

Figure 7

Effect of inhibition of particular mechanisms on primed CD4+ T cell output. Cumulative (14 day) CD4+ T cell output (cognate frequency 1:300) from the LN is shown for (1) reduced pMHC half-life, (2) increased unbinding threshold, (3) increased binding threshold, (4) increased priming threshold. Each parameter was reduced (or increased) by a standardized amount (lowest or highest range value and then by half as much more reduced (or added). The effect of combinations of 2,3 and 4 of these changes is also shown.