Characterizing the Dynamics of CD4+ T Cell Priming within a Lymph Node

Abstract

Generating adaptive immunity after infection or immunization requires physical interaction within a lymph node (LN) T-zone between antigen-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, antigen-bearing DCs, or peptide-MHCII level on the DC. To address these questions, we developed an agent-based model of a LN to examine the relationships among cognate T cell frequency, DC density, parameters characterizing DC-T 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 non-linearly related to the number of antigen-bearing DCs present during infection. This addresses the applicability of two photon microscopy studies to understanding actual infection dynamics, as these types of experiments increase the cognate frequency by orders of magnitude as compared to physiologic levels. We found a trade-off between the quantity of peptide-MHCII on the surface of individual DCs and number of antigen-bearing DCs present in the LN in contributing to the production of primed CD4+ T cells. Interestingly, pMHCII half-life 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.

Reaction-Diffusion Modelling of Interferon Distribution in Secondary Lymphoid Organs

“…The focus should be made on the development of hybrid multiphysics models which integrate the spatial migration of cells and soluble substances in the lymphoid system with the real 3D geometry of immune responses microanatomy in SLO, calibrated using high-resolution fluorescence microscopy data. Although, there is a growing interest to explore the spatial complexities of the immune processes using mathematical models [2,3,4,14,18,25], the real 3D geometry of the SLO remains to be properly considered. Further studies of the similar to the presented here and recent imaging technology-driven computational developments [15] should provide a proper basis for a transition in the current modelling paradigm of mathematical immunology from a phenomenological, spatially degenerate approach to a multiphysics-based high-resolution description of immune responses in physiological environment of the organized lymphoid tissues [30].…”

Computational immuno-biology for organ transplantation and regenerative medicine

“…They predicted that chemotaxis increased total number of TC-DC contacts but decreased unique contacts between antigen-specific TCs and antigen-presenting DCs, producing less activated T-cells [83]. Subsequent refinements were developed to study T-cell and DC behavior, mediated by multiple cytokine signals and chemoattractants, after infection by Mycobacterium tuberculosis [49,[94][95][96][97]. Using these models, mechanisms that strongly correlate with better host-level outcomes have been identified, including elimination of uncontained lung granulomas by inducing low levels of lung tissue damage and inhibition of bacteria dissemination within the lung [96].…”

Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study

“…This could be considered for further investigation in a subsequent study. [38]). The molecular content of the parental cell is partitioned stochastically between the two daughters cells [39].…”

“…The lifespan of naïve T-cells lies in a range of 165-365 days (see Supplementary Information of [38]), but since this time frame is far from the scope of our model (which spans between day 3 and 5.5 post-infection), we assume no death of naïve T-cells. Except for naïve T-cells, all of the other CD8 T-cells (preactivated, activated and effector) die based on their molecular profile (once their caspase level reaches its threshold; see Table 5).…”

“…• µ • Caspase threshold: we evaluated the caspase threshold to be the value at which the lifespan of the effector T cells is ∼60 h (Supplementary Information of [38]). …”