A kinetic mathematical model of comprehensive iron metabolism in a respiring yeast cell: a basic-pathways approach to solving a large system dynamically

TL;DR

This paper presents a detailed mathematical model of iron metabolism in yeast cells, showing how iron-related processes work together as a system.

Contribution

The study introduces a comprehensive, kinetic model of iron metabolism in yeast using a basic-pathways approach to simulate dynamic behavior.

Findings

The model includes 80 components and 169 reactions across 5 compartments, capturing major iron-related processes.

The system can return to steady-state after perturbations, mimicking responses to genetic or environmental changes.

Steady-state iron concentrations in the model align closely with experimental estimates.

Abstract

The individual functions of most iron-containing species in Saccharomyces cerevisiae are fairly-well understood, but less is known regarding how they function collectively as a unified system. Here, an ODE-based kinetic cell model was developed to reveal system’s-level behavior of iron metabolism. The dimensionally-accurate in silico cell was divided into 5 compartments. It contained 80 components that engaged in 169 reactions. The cell grew on nutrients IRON, CARBON and OXYGEN. All major iron-related processes were represented including the biosynthesis and metallation of iron-containing proteins, trafficking of labile iron pools, homeostatic regulation, respiration, the TCA cycle, iron-sulfur-cluster and heme biosynthesis, the synthesis of DNA, phospholipids, amino acids, and nucleotide triphosphates, and reactions involving oxygen and reactive-oxygen-species. Iron and carbon were conserved in reaction stoichiometries. The time-dependent model was solved using the Basic Pathways approach, despite limited kinetic information. Once regulated appropriately, the system could withstand perturbations in component concentrations by returning to its original steady-state. It responded to changes in nutrient iron and oxygen concentrations and to changes in rate-constants, yielding altered sets of steady-state component concentrations. The latter type of perturbation is tantamount to altering the expression level of a gene. This ability offers the potential to explain phenotypic changes of genetic mutations on the mechanistic molecular level. The model included all established iron-related cellular processes (albeit in combined forms), and a highly interrelated reaction network reflecting a mutually autocatalytic system. Steady-state iron concentrations in the cell, organelles, and components were reasonably near to those observed/estimated experimentally.

The online version contains supplementary material available at 10.1007/s10534-025-00758-7.

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