Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics

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.

Authors

Institutions

Publication Details

Journal
PLoS Computational Biology
Published
2026-10-05
DOI
https://doi.org/10.1371/journal.pcbi.1014811
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics

Zaida Ann Luthey-Schulten, Marie-Christin Spindler, Julia Mahamid, Abner T. Apsley et al.
PLoS Computational Biology
Gene Regulatory Network Analysis
article

Spatially resolved reaction–diffusion modeling reveals effects of intracellular spatial heterogeneity on yeast galactose network dynamics

Zaida Ann Luthey-Schulten, Marie-Christin Spindler, Julia Mahamid, Abner T. Apsley, Zane R. Thornburg, Emmy Earnest, TIANYU WU
article en

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.

PLoS Computational BiologyVol. 22(10)
University of Illinois Urbana-Champaign (US), European Molecular Biology Laboratory (DE), European Molecular Biology Laboratory (DE)
Openalex Percentile: Top 21%
Gene Regulatory Network Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.