3D computation modelling of the influence of cytokine secretion on Th‐cell development suggests that negative selection (inhibition of Th1 cells) is more effective than positive selection by IL‐4 for Th2 cell dominance

Abstract

Th-cell development has been suggested to include selective mechanisms in which certain cytokines select either Th1 or Th2 cells to proliferate and grow. The selective theory is based on the observation that Th2 cells secrete IL-4, a cytokine that promotes Th2 development, whereas Th1 cells secrete interferon-c (IFN-c) that favours Th1 development, and both positive and negative selective influences have been suggested to operate. In this study, we investigate the role of autocrine secretion and utilization of IL-4 by Th2 cells and address the question of whether an activated Th2 cell can be positively selected by IL-4 secreted from other Th2 cells. We present a spatial three dimensional (3D) modelling approach to simulate the interaction between the IL-4 ligand and its IL-4 receptors expressed on discrete IL-4 secreting cells. The simulations, based on existing experimental data on the IL-4 receptor-ligand system, illustrate how Th-cell development is highly dependent on the distance between cells that are communicating. The model suggests that a single Th2 cell is likely to communicate with possible target cells within a range of approximately 100 lm and that an activated Th2 cell manages to fill most of its own IL-4 receptors, even at a low secretion rate. The predictions made by the model suggest that negative selection against Th1 cells is more effective than positive selection by IL-4 for promoting Th2 dominance.

Simulating T‐cell motility in the lymph node paracortex with a packed lattice geometry

“…The close packing of cells—one per lattice site—complicates the generation of random cell motion. The previous models of T cells moving on a lattice allowed jumps only into vacant sites, 20 , 21 but this approach is not valid when almost every site is occupied by a T cell. When sites are fully occupied the motion of all cells becomes interdependent, as the cell in a target site must move to make way for the incoming cell.…”

“…Although it is not clear how the 2D numbers should be extrapolated to 3D, it seems that only 14% of the space was occupied by T cells in this model. A 3D agent‐based model with lattice geometry was created to investigate the influence of cytokine secretion on Th1–Th2 development 20 . A lattice of 100 × 100 × 100=10 6 sites was used, each 10 × 10 × 10 μm site permitted to hold at most one T cell (although the average volume of a T cell is approximately 150 μm 3 ).…”

“…A 3D agent-based model with lattice geometry was created to investigate the influence of cytokine secretion on Th1-Th2 development. 20 A lattice of 100Â100Â100¼10 6 sites was used, each 10Â10Â10 mm site permitted to hold at most one T cell (although the average volume of a T cell is approximately 150 mm 3 ). In other words, the fraction of the paracortex volume occupied by T cells in this model is less than 15%.…”

“…Diagonals at 54.71 (arctan(2)) to last step (group 3) 10, 11,12,13 On axes at 901 to last step (group 4) 14, 15,16,17 Diagonals at 901 to last step (group 5) 18, 19,20,21 Diagonals at 144.71 to last step (group 6) 22, 23,24,25 Diagonals at 1351 to last step (group 7) 26…”

T cell responses in lymph nodes

“…This would necessitate a method for computing IL‐2 secretion, as a function of state of activation, and also the simulation of the IL‐2 concentration field, accounting for diffusion, absorption and decay. Although such a model for IL‐2 secretion does not yet exist, 3D models have been developed for related cytokines such as IL‐4 based on available data59 and these could provide a template for consideration of other common γ‐chain receptors.…”