Cited by 14Microbial Metabolic Engineering and BioproductionGene Regulatory Network AnalysisBioinformatics and Genomic Networks

Mathematical properties of optimal fluxes in cellular reaction networks at balanced growth

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Dourado, Hugo, Liebermeister, Wolfram, Ebenhöh, Oliver, Lercher, Martin J.·2023·PLOS Computational Biology

Published version of a preprint

Abstract

The physiology of biological cells evolved under physical and chemical constraints, such as mass conservation across the network of biochemical reactions, nonlinear reaction kinetics, and limits on cell density. For unicellular organisms, the fitness that governs this evolution is mainly determined by the balanced cellular growth rate. We previously introduced growth balance analysis (GBA) as a general framework to model and analyze such nonlinear systems, revealing important analytical properties of optimal balanced growth states. It has been shown that at optimality, only a minimal subset of reactions can have nonzero flux. However, no general principles have been established to determine if a specific reaction is active at optimality. Here, we extend the GBA framework to study the optimality of each biochemical reaction, and we identify the mathematical conditions determining whether a reaction is active or not at optimal growth in a given environment. We reformulate the mathematical problem in terms of a minimal number of dimensionless variables and use the Karush-Kuhn-Tucker (KKT) conditions to identify fundamental principles of optimal resource allocation in GBA models of any size and complexity. Our approach helps to identify from first principles the economic values of biochemical reactions, expressed as marginal changes in cellular growth rate; these economic values can be related to the costs and benefits of proteome allocation into the reactions’ catalysts. Our formulation also generalizes the concepts of Metabolic Control Analysis to models of growing cells. We show how the extended GBA framework unifies and extends previous approaches of cellular modeling and analysis, putting forward a program to analyze cellular growth through the stationarity conditions of a Lagrangian function. GBA thereby provides a general theoretical toolbox for the study of fundamental mathematical properties of balanced cellular growth.

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Authors
Dourado, H., Liebermeister, W., Ebenhöh, O., & Lercher, M. J.
Affiliations
  • Heinrich Heine University Düsseldorf (DE)
  • Université Paris-Saclay (FR)
Corresponding author
  • Dourado, Hugo
  • Lercher, Martin J.
Venue
PLOS Computational Biology
Published
2023-06-06
Volume
19
Issue
6
Pages
e1011156
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W4379537813
Cited by
14
References
7
Citations by year
2026: 5 · 2025: 2 · 2024: 4 · 2023: 2 · 2022: 1
FWCI
1.15
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
  • HAL (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Volkswagen Foundation (“Life?” grant)
  • Deutsche Forschungsgemeinschaft (CRC1310, EXC 2048/1 (Project ID: 390686111))
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
Karush-Kuhn-Tucker conditions, metabolic network optimization, resource allocation optimization, proteome allocation, metabolic control analysis, nonlinear reaction kinetics
MeSH terms
Cell Cycle, Kinetics, Models, Biological, Cell Proliferation

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