Cooperation between T cell receptor and Toll-like receptor 5 signaling for CD4 ⁺ T cell activation

Abstract

CD4+ T cells recognize antigens through their T cell receptors (TCRs); however, additional signals involving costimulatory receptors, for example, CD28, are required for proper T cell activation. Alternative costimulatory receptors have been proposed, including members of the Toll-like receptor (TLR) family, such as TLR5 and TLR2. To understand the molecular mechanism underlying a potential costimulatory role for TLR5, we generated detailed molecular maps and logical models for the TCR and TLR5 signaling pathways and a merged model for cross-interactions between the two pathways. Furthermore, we validated the resulting model by analyzing how T cells responded to the activation of these pathways alone or in combination, in terms of the activation of the transcriptional regulators CREB, AP-1 (c-Jun), and NF-κB (p65). Our merged model accurately predicted the experimental results, showing that the activation of TLR5 can play a similar role to that of CD28 activation with respect to AP-1, CREB, and NF-κB activation, thereby providing insights regarding the cross-regulation of these pathways in CD4+ T cells.

An Integrative Network Modeling Approach to T CD4 Cell Activation

“…The minimal regulatory network studied in this work considers some of the basic elements included in previous works (Klamt et al, 2006;Saez-Rodriguez et al, 2007;Rodríguez-Jorge et al, 2019), in a abridged form; furthermore, it incorporates other crucial elements involved in the early signaling events leading to CD4 T-cell activation. This model may constitute a conceptual framework to integrate the main early signaling events involved in the T CD4 cell activation through the TCR, co-stimulation and micro-environmental factors, and it can be enriched by the addition of components regulating different elements in the signaling cascades.…”

“…Previous approaches to mathematical modeling of the early events of T cell activation and differentiation have been undertaken, integrating detailed pathways of activation from the TCR and co-stimulatory molecules (Klamt et al, 2006;Saez-Rodriguez et al, 2007;Rodríguez-Jorge et al, 2019), as well as the regulation of the cell phenotype by cytokines (Naldi et al, 2010;Martinez-Sanchez et al, 2018;Puniya et al, 2018). The model we put forward is based on a network that abridges basic pathways considered in these publications and incorporates other relevant players as intrinsic elements of the signaling initiated by TCR and CD28 stimulation.…”

Multi-Approach and Multi-Scale Model of CD4+ T Cells Predicts Switch-Like and Oscillatory Emergent Behaviors in Inflammatory Response to Infection

“…While they made the individual agents adapt to the changing cell populations and cytokine concentrations, they did not capture the resulting feedback control with the overall models. Logical models informing the phenotype of CD4 T cells have been developed [28] and even been used to build multi-cellular models [29]. However, if used for our study, the lack of differentiated anatomical compartments would not allow time delays caused by cell migration at the systemic scale to be captured, such as the time delay in Fig.…”

Realizing Cancer Precision Medicine by Integrating Systems Biology and Nanomaterial Engineering

“…Various systems biology studies have constructed mathematical models for T cells, macrophages, and dendritic cells, which are the predominant cell types within TME. [144][145][146] With these mathematical models, researchers have predicted how these cells affect tumor angiogenesis. For instance, Norton et al investigated how the amounts of macrophages and fibroblasts within the TME affect tumor vasculature.…”