ArticlePLoS computational biology2018
Maintaining maximal metabolic flux by gene expression control.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Enzyme kinetics shapes the growth response of metabolic networks.PLoS computational biology · 2026Article
- Making sense of gene expression control by flux sensing.Nature metabolism · 2025Article
- Understanding and computational design of genetic circuits of metabolic networks.Essays in biochemistry · 2024Review
- Editorial: The molecular regulation of microbial metabolism.Frontiers in cell and developmental biology · 2024Article
- A coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes.Journal of the Royal Society, Interface · 2023Article
- Mathematical properties of optimal fluxes in cellular reaction networks at balanced growth.PLoS computational biology · 2023Article
- Escherichia coli robustly expresses ATP synthase at growth rate-maximizing concentrations.The FEBS journal · 2022Article
- Bottom-Up Approach to the Discovery of Clinically Relevant Biomarker Genes: The Case of Colorectal Cancer.Cancers · 2022Article
- Searching for principles of microbial physiology.FEMS microbiology reviews · 2020Review
- Elementary Growth Modes provide a molecular description of cellular self-fabrication.PLoS computational biology · 2020Article
- The Signaling Pathways Project, an integrated 'omics knowledgebase for mammalian cellular signaling pathways.Scientific data · 2019Article
- The number of active metabolic pathways is bounded by the number of cellular constraints at maximal metabolic rates.PLoS computational biology · 2019Article
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Authors and funding
5 authors.
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Abstract
One of the marvels of biology is the phenotypic plasticity of microorganisms. It allows them to maintain high growth rates across conditions. Studies suggest that cells can express metabolic enzymes at tuned concentrations through adjustment of gene expression. The associated transcription factors are often regulated by intracellular metabolites. Here we study metabolite-mediated regulation of metabolic-gene expression that maximises metabolic fluxes across conditions. We developed an adaptive control theory, qORAC (for 'Specific Flux (q) Optimization by Robust Adaptive Control'), and illustrate it with several examples of metabolic pathways. The key feature of the theory is that it does not require knowledge of the regulatory network, only of the metabolic part. We derive that maximal metabolic flux can be maintained in the face of varying N environmental parameters only if the number of transcription-factor binding metabolites is at least equal to N. The controlling circuits appear to require simple biochemical kinetics. We conclude that microorganisms likely can achieve maximal rates in metabolic pathways, in the face of environmental changes.
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