Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions.

Kevin Thurley,Lani F Wu,Steven J Altschuler

doi:10.1016/j.cels.2018.01.016

Kevin Thurley, Lani F Wu + Show 1 more

Open Access

https://doi.org/10.1016/j.cels.2018.01.016

Copy DOI

Journal: Cell Systems	Publication Date: Mar 1, 2018
Citations: 61	License type: cc-by

Affiliation: University of California, San Francisco

Abstract

SUMMARYCell-to-cell communication networks have critical roles in coordinating diverse organismal processes, such as tissue development or immune cell response. However, compared with intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far less understood. Major complications include: cells are themselves regulated by complex intracellular signaling networks; individual cells are heterogeneous; and output of any one cell can recursively become an additional input signal to other cells. Here, we make use of a framework that treats intracellular signal transduction networks as “black boxes” with characterized input-to-output response relationships. We study simple cell-to-cell communication circuit motifs and find conditions that generate bimodal responses in time, as well as mechanisms for independently controlling synchronization and delay of cell-population responses. We apply our modeling approach to explain otherwise puzzling data on cytokine secretion onset times in T cells. Our approach can be used to predict communication network structure using experimentally accessible input-to-output measurements and without detailed knowledge of intermediate steps.

Highlights

In multicellular organisms, cells live in communities and constantly exchange signaling molecules
An important example is interferon gamma (IFN-g), which is secreted by Th1 cells, stimulates macrophages, and induces the differentiation of T cells toward Th1 cells
The timing of cellular responses often cannot be described by a simple Poisson process, which would characteristically show exponentially distributed response times (Figure 1B) (Gillespie, 1992)

Summary

Introduction

Cells live in communities and constantly exchange signaling molecules. Prominent examples of short-range communication are diffusible ligands shaping immune responses (Schwartz et al, 2015) and the tumor microenvironment (Balkwill et al, 2012), notch-delta-mediated signals (Guruharsha et al, 2012), and microvesicles (Raposo and Stoorvogel, 2013). In the mammalian immune system, cell-to-cell communication can involve multiple cell types (e.g., T cells, neutrophils, macrophages, and epithelial cells) communicating through tens of different types of cytokine species (Burmester et al, 2014; Schwartz et al, 2015). An important example is interferon gamma (IFN-g), which is secreted by Th1 cells (a subclass of T cells), stimulates macrophages, and induces the differentiation of T cells toward Th1 cells. The levels of various cytokine species vary by an order of magnitude or more between supernatants of isolated cells and cell populations (Schrier et al, 2016; Shalek et al, 2014; Xue et al, 2015), suggesting pronounced effects of cell-to-cell communication on the cytokine milieu

Methods

Results

Discussion

Conclusion