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Timescale Separation of Positive and Negative Signaling Creates History-Dependent Responses to IgE Receptor Stimulation

Journal Article · · Scientific Reports
 [1];  [2];  [3];  [4];  [5];  [1];  [3];  [2];  [2];  [5];  [4];  [6]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States). Dept. of Systems Biology. Biological and Material Sciences
  2. Cornell Univ., Ithaca, NY (United States). Dept. of Chemistry and Chemical Biology
  3. Sandia National Lab. (SNL-CA), Livermore, CA (United States). Dept. of Biotechnology and Bioengineering. Biological and Material Sciences
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  5. Univ. of New Mexico, Albuquerque, NM (United States). School of Medicine. Dept. of Pathology
  6. Sandia National Lab. (SNL-CA), Livermore, CA (United States). Biological and Material Sciences
+ Show Author Affiliations

The high-affinity receptor for IgE expressed on the surface of mast cells and basophils interacts with antigens, via bound IgE antibody, and triggers secretion of inflammatory mediators that contribute to allergic reactions. To understand how past inputs (memory) influence future inflammatory responses in mast cells, a microfluidic device was used to precisely control exposure of cells to alternating stimulatory and non-stimulatory inputs. We determined that the response to subsequent stimulation depends on the interval of signaling quiescence. For shorter intervals of signaling quiescence, the second response is blunted relative to the first response, whereas longer intervals of quiescence induce an enhanced second response. Through an iterative process of computational modeling and experimental tests, we found that these memory-like phenomena arise from a confluence of rapid, short-lived positive signals driven by the protein tyrosine kinase Syk; slow, long-lived negative signals driven by the lipid phosphatase Ship1; and slower degradation of Ship1 co-factors. This work advances our understanding of mast cell signaling and represents a generalizable approach for investigating the dynamics of signaling systems.

Research Organization:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States); Cornell Univ., Ithaca, NY (United States); Univ. of New Mexico, Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); USDOE National Nuclear Security Administration (NNSA); National Inst. of Health (NIH) (United States)
Grant/Contract Number:
AC52-06NA25396; NA0003525
OSTI ID:
1457302
Alternate ID(s):
OSTI ID: 1481886
Report Number(s):
LA-UR--15-28484
Journal Information:
Scientific Reports, Journal Name: Scientific Reports Vol. 7; ISSN 2045-2322
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (4)

Parameter estimation and uncertainty quantification for systems biology models journal December 2019
PyBioNetFit and the Biological Property Specification Language journal September 2019
The Autoimmune Skin Disease Bullous Pemphigoid: The Role of Mast Cells in Autoantibody-Induced Tissue Injury journal March 2018
Rational programming of history-dependent logic in cellular populations posted_content April 2019

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59 BASIC BIOLOGICAL SCIENCES
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