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Title: An Interaction Library for the FcεRI Signaling Network

Journal Article · · Frontiers in Immunology
 [1];  [2];  [2];  [3]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cornell Univ., Ithaca, NY (United States)
  2. Cornell Univ., Ithaca, NY (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
+ Show Author Affiliations

Antigen receptors play a central role in adaptive immune responses. Although the molecular networks associated with these receptors have been extensively studied, we currently lack a systems-level understanding of how combinations of non-covalent interactions and post-translational modifications are regulated during signaling to impact cellular decision-making. To fill this knowledge gap, it will be necessary to formalize and piece together information about individual molecular mechanisms to form large-scale computational models of signaling networks. To this end, we have developed an interaction library for signaling by the high-affinity IgE receptor, FcεRI. The library consists of executable rules for protein–protein and protein–lipid interactions. This library extends earlier models for FcεRI signaling and introduces new interactions that have not previously been considered in a model. Thus, this interaction library is a toolkit with which existing models can be expanded and from which new models can be built. As an example, we present models of branching pathways from the adaptor protein Lat, which influence production of the phospholipid PIP3 at the plasma membrane and the soluble second messenger IP3. We find that inclusion of a positive feedback loop gives rise to a bistable switch, which may ensure robust responses to stimulation above a threshold level. In addition, the library is visualized to facilitate understanding of network circuitry and identification of network motifs.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1396113
Report Number(s):
LA-UR-13-29273
Journal Information:
Frontiers in Immunology, Vol. 5; ISSN 1664-3224
Publisher:
Frontiers Research FoundationCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 15 works
Citation information provided by
Web of Science

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Cited By (5)

An Introduction to Rule-based Modeling of Immune Receptor Signaling preprint January 2017
Automated visualization of rule-based models journal November 2017
Visualizing Regulation in Rule-based Models preprint January 2015
Immune System Modeling and Analysis journal December 2014
Parallel Tempering with Lasso for model reduction in systems biology journal March 2020

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