Understanding and computational design of genetic circuits of metabolic networks

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

The expression of metabolic proteins is controlled by genetic circuits, matching metabolic demands and changing environmental conditions. Ideally, this regulation brings about a competitive level of metabolic fitness. Understanding how cells can achieve a robust (close-to-optimal) functioning of metabolism by appropriate control of gene expression aids synthetic biology by providing design criteria of synthetic circuits for biotechnological purposes. It also extends our understanding of the designs of genetic circuitry found in nature such as metabolite control of transcription factor activity, promoter architectures and transcription factor dependencies, and operon composition (in bacteria). Here, we review, explain and illustrate an approach that allows for the inference and design of genetic circuitry that steers metabolic networks to achieve a maximal flux per unit invested protein across dynamic conditions. We discuss how this approach and its understanding can be used to rationalize Escherichia coli's strategy to regulate the expression of its ribosomes and infer the design of circuitry controlling gene expression of amino-acid biosynthesis enzymes. The inferred regulation indeed resembles E. coli's circuits, suggesting that these have evolved to maximize amino-acid production fluxes per unit invested protein. We end by an outlook of the use of this approach in metabolic engineering applications.

Original languageEnglish
Pages (from-to)41-51
Number of pages11
JournalEssays in Biochemistry
Volume68
Issue number1
Early online date30 Apr 2024
DOIs
Publication statusPublished - Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s).

Funding

F.J.B. and M.R. acknowledge funding by NWO-XL grant OCENW.XL21.XL21.007 \u2018Taking Control of Metabolism in Microbial Cell Factories by Applying Non-canonical Redox Cofactors\u2019. L.S. acknowledges funding by CONACYT. R.P.\u2019s work was funded by NWO grant 613.009.131 \u2018Control of maximal growth rate by single-celled organisms\u2019. A.B.\u2019s work was funded by the European Union\u2019s Horizon 2020 research and innovation programme under the Marie Sk\u0142odowska-Curie grant agreement no. 713669.

FundersFunder number
Consejo Nacional de Humanidades, Ciencias y Tecnologías
Horizon 2020 Framework Programme
NWO-XLOCENW.XL21.XL21.007
Nederlandse Organisatie voor Wetenschappelijk Onderzoek613.009.131
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
H2020 Marie Skłodowska-Curie Actions713669
H2020 Marie Skłodowska-Curie Actions

    Keywords

    • Escherichia coli
    • gene expression and regulation
    • mathematical modelling
    • microbiology

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