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From cartoons to quantitative models in Golgi transport
Author(s) -
Quiros D. Nicolas,
Nieto Franco,
Mayorga Luis S.
Publication year - 2021
Publication title -
biology of the cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.543
H-Index - 85
eISSN - 1768-322X
pISSN - 0248-4900
DOI - 10.1111/boc.202000107
Subject(s) - golgi apparatus , schematic , intracellular transport , organelle , biology , vesicular transport protein , computer science , dynamism , vesicle , biological system , computational biology , microbiology and biotechnology , intracellular , endoplasmic reticulum , membrane , physics , engineering , biochemistry , quantum mechanics , electronic engineering
Background Cell biology is evolving to become a more formal and quantitative science. In particular, several mathematical models have been proposed to address Golgi self‐organisation and protein and lipid transport. However, most scientific articles about the Golgi apparatus are still using static cartoons that miss the dynamism of this organelle. Results In this report, we show that schematic drawings of Golgi trafficking can be easily translated into an agent‐based model using the Repast platform. The simulations generate an active interplay among cisternae and vesicles rendering quantitative predictions about Golgi stability and transport of soluble and membrane‐associated cargoes. The models can incorporate complex networks of molecular interactions and chemical reactions by association with COPASI, a software that handles ordinary differential equations. Conclusions The strategy described provides a simple, flexible and multiscale support to analyse Golgi transport. The simulations can be used to address issues directly linked to the mechanism of transport or as a way to incorporate the complexity of trafficking to other cellular processes that occur in dynamic organelles. Significance We show that the rules implicitly present in most schematic representations of intracellular trafficking can be used to build dynamic models with quantitative outputs that can be compared with experimental results.