Literature DB >> 23979724

Dynamic optimization identifies optimal programmes for pathway regulation in prokaryotes.

Martin Bartl1, Martin Kötzing, Stefan Schuster, Pu Li, Christoph Kaleta.   

Abstract

To survive in fluctuating environmental conditions, microorganisms must be able to quickly react to environmental challenges by upregulating the expression of genes encoding metabolic pathways. Here we show that protein abundance and protein synthesis capacity are key factors that determine the optimal strategy for the activation of a metabolic pathway. If protein abundance relative to protein synthesis capacity increases, the strategies shift from the simultaneous activation of all enzymes to the sequential activation of groups of enzymes and finally to a sequential activation of individual enzymes along the pathway. In the case of pathways with large differences in protein abundance, even more complex pathway activation strategies with a delayed activation of low abundance enzymes and an accelerated activation of high abundance enzymes are optimal. We confirm the existence of these pathway activation strategies as well as their dependence on our proposed constraints for a large number of metabolic pathways in several hundred prokaryotes.

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Year:  2013        PMID: 23979724     DOI: 10.1038/ncomms3243

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  11 in total

1.  Regulatory Networks Governing Methionine Catabolism into Volatile Organic Sulfur-Containing Compounds in Clonostachys rosea.

Authors:  Yang-Hua Xu; Kai-Zhi Jia; Ya-Jie Tang
Journal:  Appl Environ Microbiol       Date:  2018-10-30       Impact factor: 4.792

2.  Footprints of optimal protein assembly strategies in the operonic structure of prokaryotes.

Authors:  Jan Ewald; Martin Kötzing; Martin Bartl; Christoph Kaleta
Journal:  Metabolites       Date:  2015-04-28

Review 3.  Computing the functional proteome: recent progress and future prospects for genome-scale models.

Authors:  Edward J O'Brien; Bernhard O Palsson
Journal:  Curr Opin Biotechnol       Date:  2015-01-08       Impact factor: 9.740

4.  Generating dynamic gene expression patterns without the need for regulatory circuits.

Authors:  Sahil B Shah; Alexis M Hill; Claus O Wilke; Adam J Hockenberry
Journal:  PLoS One       Date:  2022-05-26       Impact factor: 3.752

Review 5.  Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.

Authors:  Fei He; Ettore Murabito; Hans V Westerhoff
Journal:  J R Soc Interface       Date:  2016-04-13       Impact factor: 4.118

6.  Sequential metabolic phases as a means to optimize cellular output in a constant environment.

Authors:  Aljoscha Palinkas; Sascha Bulik; Alexander Bockmayr; Hermann-Georg Holzhütter
Journal:  PLoS One       Date:  2015-03-18       Impact factor: 3.240

7.  Optimal programs of pathway control: dissecting the influence of pathway topology and feedback inhibition on pathway regulation.

Authors:  Gundián M de Hijas-Liste; Eva Balsa-Canto; Jan Ewald; Martin Bartl; Pu Li; Julio R Banga; Christoph Kaleta
Journal:  BMC Bioinformatics       Date:  2015-05-16       Impact factor: 3.169

8.  Modelling the host-pathogen interactions of macrophages and Candida albicans using Game Theory and dynamic optimization.

Authors:  Sybille Dühring; Jan Ewald; Sebastian Germerodt; Christoph Kaleta; Thomas Dandekar; Stefan Schuster
Journal:  J R Soc Interface       Date:  2017-07       Impact factor: 4.118

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

Authors:  Jan Ewald; Martin Bartl; Thomas Dandekar; Christoph Kaleta
Journal:  PLoS Comput Biol       Date:  2017-02-17       Impact factor: 4.475

10.  A simple method for identifying parameter correlations in partially observed linear dynamic models.

Authors:  Pu Li; Quoc Dong Vu
Journal:  BMC Syst Biol       Date:  2015-12-14
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