18087
2017
eng
19
2
13
article
1
2019-05-20
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Optimality principles reveal a complex interplay of intermediate toxicity and kinetic efficiency in the regulation of prokaryotic metabolism
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 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.
PLOS Computational Biology
10.1371/journal.pcbi.1005371
urn:nbn:de:bvb:20-opus-180870
PLOS Computational Biology (2017) 13:2, e1005371. https://doi.org/10.1371/journal.pcbi.1005371
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true
CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International
Jan Ewald
Martin Bartl
Thomas Dandekar
Christoph Kaleta
eng
uncontrolled
Enzyme regulation
eng
uncontrolled
Toxicity
eng
uncontrolled
Metabolic pathways
eng
uncontrolled
Enzymes
eng
uncontrolled
Transcriptional control
eng
uncontrolled
Enzyme kinetics
eng
uncontrolled
Enzyme metabolism
eng
uncontrolled
Predictive toxicology
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/18087/Ewald_PlosComputationalBiology_2017.pdf
6482
2012
eng
article
1
2013-03-16
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Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum
Background: Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade Milnesium tardigradum were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress. Results: In this study we propose a novel integrative approach for the analysis of metabolic networks to identify modules of joint shifts on the transcriptomic and metabolic levels. We derive a tardigrade-specific metabolic network represented as an undirected graph with 3,658 nodes (metabolites) and 4,378 edges (reactions). Time course metabolite profiles are used to score the network nodes showing a significant change over time. The edges are scored according to information on enzymes from the EST data. Using this combined information, we identify a key subnetwork (functional module) of concerted changes in metabolic pathways, specific for de- and rehydration. The module is enriched in reactions showing significant changes in metabolite levels and enzyme abundance during the transition. It resembles the cessation of a measurablemetabolism (e.g. glycolysis and amino acid anabolism) during the tun formation, the production of storage metabolites and bioprotectants, such as DNA stabilizers, and the generation of amino acids and cellular components from monosaccharides as carbon and energy source during rehydration. Conclusions: The functional module identifies relationships among changed metabolites (e.g. spermidine) and reactions and provides first insights into important altered metabolic pathways. With sparse and diverse data available, the presented integrated metabolite network approach is suitable to integrate all existing data and analyse it in a combined manner.
urn:nbn:de:bvb:20-opus-75241
7524
In: BMC Systems Biology (2012) 6: 72, doi:10.1186/1752-0509-6-72
Daniela Beisser
Markus A. Grohme
Joachim Kopka
Marcus Frohme
Ralph O. Schill
Steffen Hengherr
Thomas Dandekar
Gunnar W. Klau
Marcus Dittrich
Tobias Müller
deu
swd
Milnesium tardigradum
eng
uncontrolled
Integrated network analysis
eng
uncontrolled
Functional modules
eng
uncontrolled
Metabolic profiles
eng
uncontrolled
Metabolic pathways
eng
uncontrolled
Trend test
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Förderzeitraum 2012
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/6482/019_1752_0509_6_72.pdf