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Investigating Mast Cell Secretory Granules; from Biosynthesis to Exocytosis
Published on: January 26, 2015
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The stealthy nano-machine behind mast cell granule size distribution
Ilan Hammel1, Isaac Meilijson2
1Sackler Faculty of Medicine, Department of Pathology, Tel Aviv University, Tel Aviv 6997801, Israel.
Molecular Immunology
|March 18, 2014
Summary
A new model explains mast cell granule formation using statistical mechanics. This approach views Soluble NSF Attachment Protein REceptor (SNARE) components as particles driving granule growth and secretion.
Area of Science:
- Cell Biology
- Biophysics
- Systems Biology
Background:
- Mast cells synthesize and store mediators in secretory granules.
- Classical models describe granule formation via condensation and fusion.
- Existing models lack a dynamic explanation for granule inventory management.
Purpose of the Study:
- To present a novel stochastic model for mast cell granule growth and elimination (G&E).
- To elucidate the role of Soluble NSF Attachment Protein REceptor (SNARE) components in granule dynamics.
- To explain the inventory management strategies for mast cell granules.
Main Methods:
- Statistical mechanics approach viewing SNAREs as interacting particles.
- Development of a stochastic model for granule G&E.
- Mathematical calculations and statistical modeling.
Main Results:
- The model proposes a 'nano-machine' of SNARE self-aggregation for granule growth and secretion.
- Granule stock acts as a buffer against demand uncertainty and production lead times.
- A rationale for nearly last-in, first-out (LIFO) inventory management emerged.
Conclusions:
- The stochastic G&E model provides a mechanistic explanation for mast cell secretory granule dynamics.
- SNARE self-aggregation is a key process in granule formation and secretion.
- The model offers insights into cellular inventory management strategies.
