Deciphering the physiological response of Escherichia coli under high ATP demand.

ATP homeostasis central metabolism glycolysis kinetic model metabolic engineering

Journal

Molecular systems biology
ISSN: 1744-4292
Titre abrégé: Mol Syst Biol
Pays: England
ID NLM: 101235389

Informations de publication

Date de publication:
12 2021
Historique:
revised: 30 11 2021
received: 15 06 2021
accepted: 30 11 2021
entrez: 20 12 2021
pubmed: 21 12 2021
medline: 27 1 2022
Statut: ppublish

Résumé

One long-standing question in microbiology is how microbes buffer perturbations in energy metabolism. In this study, we systematically analyzed the impact of different levels of ATP demand in Escherichia coli under various conditions (aerobic and anaerobic, with and without cell growth). One key finding is that, under all conditions tested, the glucose uptake increases with rising ATP demand, but only to a critical level beyond which it drops markedly, even below wild-type levels. Focusing on anaerobic growth and using metabolomics and proteomics data in combination with a kinetic model, we show that this biphasic behavior is induced by the dual dependency of the phosphofructokinase on ATP (substrate) and ADP (allosteric activator). This mechanism buffers increased ATP demands by a higher glycolytic flux but, as shown herein, it collapses under very low ATP concentrations. Model analysis also revealed two major rate-controlling steps in the glycolysis under high ATP demand, which could be confirmed experimentally. Our results provide new insights on fundamental mechanisms of bacterial energy metabolism and guide the rational engineering of highly productive cell factories.

Identifiants

pubmed: 34928538
doi: 10.15252/msb.202110504
pmc: PMC8686765
doi:

Substances chimiques

Adenosine Triphosphate 8L70Q75FXE

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e10504

Informations de copyright

© 2021 The Authors Published under the terms of the CC BY 4.0 license.

Références

Biochem J. 2017 Nov 16;474(23):3935-3950
pubmed: 29146872
Mol Genet Genomics. 2008 Jan;279(1):87-94
pubmed: 17943314
Bioinformatics. 2006 Dec 15;22(24):3067-74
pubmed: 17032683
Biochim Biophys Acta. 1975 Feb 13;381(2):257-68
pubmed: 122902
Nat Rev Microbiol. 2014 May;12(5):327-40
pubmed: 24658329
Mol Syst Biol. 2010;6:355
pubmed: 20212527
Microb Cell Fact. 2013 Mar 18;12:26
pubmed: 23506076
J Proteome Res. 2016 Aug 5;15(8):2537-47
pubmed: 27345528
Biotechnol J. 2019 Sep;14(9):e1800438
pubmed: 30927494
Metab Eng. 2011 Jan;13(1):76-81
pubmed: 21040799
J Bacteriol. 1992 Dec;174(23):7635-41
pubmed: 1447134
Science. 1997 Sep 5;277(5331):1453-62
pubmed: 9278503
Proc Natl Acad Sci U S A. 2019 Aug 27;116(35):17592-17597
pubmed: 31405984
J Bacteriol. 2020 Aug 10;202(17):
pubmed: 32571968
Mol Microbiol. 2018 Aug;109(3):278-290
pubmed: 29923648
J Biol Chem. 1994 Feb 18;269(7):5122-6
pubmed: 8106492
Nat Chem Biol. 2016 Jul;12(7):482-9
pubmed: 27159581
Appl Environ Microbiol. 1993 Dec;59(12):4261-5
pubmed: 8285716
Biotechnol Biofuels. 2020 Nov 9;13(1):185
pubmed: 33292464
Sci Rep. 2017 Jan 03;7:39647
pubmed: 28045126
Proc Natl Acad Sci U S A. 2009 Dec 1;106(48):20180-5
pubmed: 19918073
Microb Cell Fact. 2018 Aug 28;17(1):132
pubmed: 30153840
Appl Microbiol Biotechnol. 2016 Nov;100(22):9509-9517
pubmed: 27344595
Proc Natl Acad Sci U S A. 2013 Jan 15;110(3):1130-5
pubmed: 23277571
Biotechnol J. 2018 Feb;13(2):
pubmed: 29131522
PLoS One. 2014 Sep 30;9(9):e106453
pubmed: 25268481
Biosci Biotechnol Biochem. 2008 Apr;72(4):1138-41
pubmed: 18391462
J Bacteriol. 2002 Jul;184(14):3909-16
pubmed: 12081962
J Mol Biol. 1968 Jan 14;31(1):13-35
pubmed: 4229913
Cell Syst. 2021 Jan 20;12(1):56-67.e6
pubmed: 33238135
Appl Microbiol Biotechnol. 2012 May;94(4):1079-86
pubmed: 22173482
Mol Syst Biol. 2021 Dec;17(12):e10504
pubmed: 34928538
Microbiol Mol Biol Rev. 2005 Mar;69(1):12-50
pubmed: 15755952
Biochemistry. 2009 Dec 29;48(51):12323-8
pubmed: 19905012
J Bioinform Comput Biol. 2008 Aug;6(4):843-67
pubmed: 18763746
Nature. 2020 Aug;584(7821):470-474
pubmed: 32669712
J Biotechnol. 2017 Nov 10;261:221-228
pubmed: 28499817
Theor Biol Med Model. 2006 Dec 15;3:41
pubmed: 17173669
Anal Chem. 2017 Feb 7;89(3):1624-1631
pubmed: 28050903
Nature. 2015 Dec 3;528(7580):99-104
pubmed: 26632588
J Biol Chem. 2010 Jun 4;285(23):17498-506
pubmed: 20299454
FEMS Microbiol Rev. 2020 Nov 24;44(6):821-844
pubmed: 33099619
BMC Syst Biol. 2007 Jan 08;1:2
pubmed: 17408509
Microb Cell Fact. 2021 Mar 9;20(1):63
pubmed: 33750397
J Proteome Res. 2012 Nov 2;11(11):5145-56
pubmed: 23017020
Nucleic Acids Res. 1997 Mar 15;25(6):1203-10
pubmed: 9092630
J Bacteriol. 1967 Feb;93(2):642-8
pubmed: 4289962
Biotechnol Bioeng. 2015 Oct;112(10):2195-9
pubmed: 25899755

Auteurs

Simon Boecker (S)

Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.

Giulia Slaviero (G)

Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.

Thorben Schramm (T)

Dynamic Control of Metabolic Networks, Max Planck Institute for Terrestrial Microbiology, Marburg, Germany.
Interfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.

Witold Szymanski (W)

Core Facility for Mass Spectrometry and Proteomics, Max Planck Institute for Terrestrial Microbiology, Marburg, Germany.

Ralf Steuer (R)

Institute for Biology, Humboldt-University of Berlin, Berlin, Germany.

Hannes Link (H)

Dynamic Control of Metabolic Networks, Max Planck Institute for Terrestrial Microbiology, Marburg, Germany.
Interfaculty Institute for Microbiology and Infection Medicine Tübingen, University of Tübingen, Tübingen, Germany.

Steffen Klamt (S)

Analysis and Redesign of Biological Networks, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.

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Classifications MeSH