Simulation of Stimulation: Cytokine Dosage and Cell Cycle Crosstalk Driving Timing-Dependent T Cell Differentiation

Abstract

Triggering an appropriate protective response against invading agents is crucial to the effectiveness of human innate and adaptive immunity. Pathogen recognition and elimination requires integration of a myriad of signals from many different immune cells. For example, T cell functioning is not qualitatively, but quantitatively determined by cellular and humoral signals. Tipping the balance of signals, such that one of these is favored or gains advantage on another one, may impact the plasticity of T cells. This may lead to switching their phenotypes and, ultimately, modulating the balance between proliferating and memory T cells to sustain an appropriate immune response. We hypothesize that, similar to other intracellular processes such as the cell cycle, the process of T cell differentiation is the result of: (i) pleiotropy (pattern) and (ii) magnitude (dosage/concentration) of input signals, as well as (iii) their timing and duration. That is, a flexible, yet robust immune response upon recognition of the pathogen may result from the integration of signals at the right dosage and timing. To investigate and understand how system’s properties such as T cell plasticity and T cell-mediated robust response arise from the interplay between these signals, the use of experimental toolboxes that modulate immune proteins may be explored. Currently available methodologies to engineer T cells and a recently devised strategy to measure protein dosage may be employed to precisely determine, for example, the expression of transcription factors responsible for T cell differentiation into various subtypes. Thus, the immune response may be systematically investigated quantitatively. Here, we provide a perspective of how pattern, dosage and timing of specific signals, called interleukins, may influence T cell activation and differentiation during the course of the immune response. We further propose that interleukins alone cannot explain the phenotype variability observed in T cells. Specifically, we provide evidence that the dosage of intercellular components of both the immune system and the cell cycle regulating cell proliferation may contribute to T cell activation, differentiation, as well as T cell memory formation and maintenance. Altogether, we envision that a qualitative (pattern) and quantitative (dosage) crosstalk between the extracellular milieu and intracellular proteins leads to T cell plasticity and robustness. The understanding of this complex interplay is crucial to predict and prevent scenarios where tipping the balance of signals may be compromised, such as in autoimmunity.

A Mechanistic Computational Model Reveals That Plasticity of CD4+ T Cell Differentiation Is a Function of Cytokine Composition and Dosage

“…Input availability and relative dosage at which inputs generate a productive signaling cascade necessarily result in a variable timing of an immune response. Specifically, we and others propose that dosage- and timing-dependent impact of inputs, such as ILs, may impact the T cell differentiation ( Barberis et al, 2018 ; Martinez-Sanchez et al, 2018 ). This may be investigated by employing experimental methodologies that we have recently envisioned ( Barberis and Verbruggen, 2017 ).…”

“…This may be investigated by employing experimental methodologies that we have recently envisioned ( Barberis and Verbruggen, 2017 ). Furthermore, crosstalk between ILs and signaling cascades, such as the one governing the cell cycle, may impinge on a timely T cell-mediated protective response ( Barberis et al, 2018 ). These aspects are the focus of our current research efforts.…”

Neuro-Immune Hemostasis: Homeostasis and Diseases in the Central Nervous System

“…Other possibilities are offered by dynamic systems biology models ( Abudukelimu et al, 2018 ; Barberis et al, 2018 ), whose computational analysis has been able to shed some light on the regulatory logic governing either inflammation response or T cell differentiation. It is expected that the interactions of computational models and new experiments, suggested by the model predictions, will be able to elucidate the fine structure of molecular events generated by blood coagulation and neuro-immune response in several CNS diseases, thereby opening the way to more effective treatments.…”

Role of Cytokine Combinations on CD4+ T Cell Differentiation, Partial Polarization, and Plasticity: Continuous Network Modeling Approach

“…Each cell state or type corresponds to an attractor, and our system let us to study the conditions required to drive the system from one attractor to another one ( Haken, 1977 ). We explore pathways that lead to equilibrium points, but also alterations of the expression levels of the networks components and the microenvironment, that may induce that cells transit between attractors ( Mendoza, 2006 ; Naldi et al, 2010 ; Carbo et al, 2013 ; Abou-Jaoudé et al, 2014 ; Martinez-Sanchez et al, 2015 ; Eizenberg-Magar et al, 2017 ; Barberis et al, 2018 ; Puniya et al, 2018 ).…”