Subcellular mRNA localization is an evolutionarily conserved mechanism to spatially and temporally drive local translation and, in turn, protein targeting. Hence, this mechanism achieves precise control of gene expression and establishes functional and structural networks during cell growth and development as well as during stimuli response. Since its discovery in ascidian eggs, mRNA localization has been extensively studied in animal and yeast cells. Although our knowledge of subcellular mRNA localization in plant cells lags considerably behind other biological systems, mRNA localization to the endoplasmic reticulum (ER) has also been well established since its discovery in cereal endosperm cells in the early 1990s. Storage protein mRNA targeting to distinct subdomains of the ER determines efficient accumulation of the corresponding proteins in different endosomal storage sites and, in turn, underlies storage organelle biogenesis in cereal grains. The targeting process requires the presence of RNA localization elements, also called zipcodes, and specific RNA-binding proteins that recognize and bind these zipcodes and recruit other factors to mediate active transport. Here, we review the current knowledge of the mechanisms and functions of mRNA localization to the ER in plant cells and address directions for future research.
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Spatially Resolved Reaction–Diffusion Modeling Reveals Effects of Intracellular Spatial Heterogeneity on Yeast Galactose Network Dynamics
Abstract Eukaryotic cells are spatially organized into functionally-distinct compartments. This three-dimensional(3D) organization generates intracellular heterogeneities that can modulate regulatory dynamics. Despite this knowledge of subcellular organization, most quantitative gene-regulation models still assume a well-mixed environment in which molecules can react regardless of their spatial positions. Here, we use the well-established galactose switch in budding yeast (Saccharomyces cerevisiae) to develop spatially-resolved models that integrate experimentally-derived intracellular architectures, including chromosome organization, the endoplasmic reticulum (ER) and spatially distinct ribosome populations. We implement a hybrid stochastic–deterministic framework in which gene expression is modeled using a reaction–diffusion master equation that enforces locality (i.e., reactions occur only when molecules are in physical proximity), while metabolic and transport processes are captured by ordinary differential equations. Guided by electron microscopy and biochemical constraints, we quantify how accounting for intracellular spatial organization alters regulatory predictions in the galactose switch. We show that chromosome geometry has little effect on Gal2p output, whereas ER-associated translation reduces Gal2p delivery to the plasma membrane; the largest decrease of Gal2p abundance occurs when translation ofGAL2mRNA is restricted to a population of ribosomes physically bound to the ER. Together, these results demonstrate that more realistic 3D cellular architectures and local reaction rules can qualitatively change regulatory predictions, motivating integration of intracellular organization in future whole-cell models. Author SummaryEukaryotic cells are highly organized spaces with distinct subcellular compartments and heterogeneous distributions of molecules which influence how cells function. Yet, most computational models of gene regulation assume a spatially homogeneous intracellular environment. To quantify how intracellular architecture influences regulatory predictions, we developed spatially resolved models of the galactose switch in budding yeast, a well-characterized gene regulatory system controlling the response to extracellular galactose. We compared conventional well-stirred simulations with models that explicitly incorporate experimentally informed intracellular organization, including chromosome positioning, endoplasmic reticulum geometry, and functionally distinct ribosome populations. Incorporating these spatial features substantially altered the dynamics of predicted gene activity, protein production, and intracellular sugar levels. Our results demonstrate that the three-dimensional organization of eukaryotic cells can significantly change regulatory outcomes of computational models, underscoring the need for integrating realistic spatial architectures in future models of eukaryotic gene regulation.
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- Award ID(s):
- 2243257
- PAR ID:
- 10686239
- Publisher / Repository:
- bioRxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- bioRxiv
- Sponsoring Org:
- National Science Foundation
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