Optimality principles reveal a complex interplay of intermediate toxicity and kinetic efficiency in the regulation of prokaryotic metabolism

Please always quote using this URN: urn:nbn:de:bvb:20-opus-180870
  • A precise and rapid adjustment of fluxes through metabolic pathways is crucial for organisms to prevail in changing environmental conditions. Based on this reasoning, many guiding principles that govern the evolution of metabolic networks and their regulation have been uncovered. To this end, methods from dynamic optimization are ideally suited since they allow to uncover optimality principles behind the regulation of metabolic networks. We used dynamic optimization to investigate the influence of toxic intermediates in connection with theA precise and rapid adjustment of fluxes through metabolic pathways is crucial for organisms to prevail in changing environmental conditions. Based on this reasoning, many guiding principles that govern the evolution of metabolic networks and their regulation have been uncovered. To this end, methods from dynamic optimization are ideally suited since they allow to uncover optimality principles behind the regulation of metabolic networks. We used dynamic optimization to investigate the influence of toxic intermediates in connection with the efficiency of enzymes on the regulation of a linear metabolic pathway. Our results predict that transcriptional regulation favors the control of highly efficient enzymes with less toxic upstream intermediates to reduce accumulation of toxic downstream intermediates. We show that the derived optimality principles hold by the analysis of the interplay between intermediate toxicity and pathway regulation in the metabolic pathways of over 5000 sequenced prokaryotes. Moreover, using the lipopolysaccharide biosynthesis in Escherichia coli as an example, we show how knowledge about the relation of regulation, kinetic efficiency and intermediate toxicity can be used to identify drug targets, which control endogenous toxic metabolites and prevent microbial growth. Beyond prokaryotes, we discuss the potential of our findings for the development of antifungal drugs.show moreshow less

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Metadaten
Author: Jan Ewald, Martin Bartl, Thomas Dandekar, Christoph Kaleta
URN:urn:nbn:de:bvb:20-opus-180870
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Language:English
Parent Title (English):PLOS Computational Biology
Year of Completion:2017
Volume:13
Issue:2
Article Number:e1005371
Pagenumber:19
Source:PLOS Computational Biology (2017) 13:2, e1005371. https://doi.org/10.1371/journal.pcbi.1005371
DOI:https://doi.org/10.1371/journal.pcbi.1005371
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:Enzyme kinetics; Enzyme metabolism; Enzyme regulation; Enzymes; Metabolic pathways; Predictive toxicology; Toxicity; Transcriptional control
Release Date:2021/05/17
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International