Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics
8 affiliations
- 1Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
- 2National Science Foundation Science and Technology Center for Quantitative Cell Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
- 3Molecular Systems Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- 4Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
- 5Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
- 6Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
- 7Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- 8Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
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 in present model 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 of GAL2 mRNA 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 summary: Eukaryotic 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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BibTeX
@article{wu2026spatially,
title = {{Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics}},
author = {Tianyu Wu and Marie-Christin Spindler and Abner T Apsley and Emmy Earnest and Zane R Thornburg and Julia Mahamid and Zaida Luthey-Schulten},
journal = {PLOS Computational Biology},
year = {2026},
month = oct,
doi = {10.1371/journal.pcbi.1014811},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014811},
note = {CC BY},
}
RIS
TY - JOUR
TI - Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics
AU - Tianyu Wu
AU - Marie-Christin Spindler
AU - Abner T Apsley
AU - Emmy Earnest
AU - Zane R Thornburg
AU - Julia Mahamid
AU - Zaida Luthey-Schulten
PY - 2026
DA - 2026/10/05
JO - PLOS Computational Biology
DO - 10.1371/journal.pcbi.1014811
UR - https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014811
AB - 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 in present model 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 of GAL2 mRNA 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 summary: Eukaryotic 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.
SN - 1553-7358
SN - 1553-734X
ER -