Literature DB >> 31986156

Elementary Growth Modes provide a molecular description of cellular self-fabrication.

Daan H de Groot1, Josephus Hulshof2, Bas Teusink1, Frank J Bruggeman1, Robert Planqué1,2.   

Abstract

In this paper we try to describe all possible molecular states (phenotypes) for a cell that fabricates itself at a constant rate, given its enzyme kinetics and the stoichiometry of all reactions. For this, we must understand the process of cellular growth: steady-state self-fabrication requires a cell to synthesize all of its components, including metabolites, enzymes and ribosomes, in proportions that match its own composition. Simultaneously, the concentrations of these components affect the rates of metabolism and biosynthesis, and hence the growth rate. We here derive a theory that describes all phenotypes that solve this circular problem. All phenotypes can be described as a combination of minimal building blocks, which we call Elementary Growth Modes (EGMs). EGMs can be used as the theoretical basis for all models that explicitly model self-fabrication, such as the currently popular Metabolism and Expression models. We then use our theory to make concrete biological predictions. We find that natural selection for maximal growth rate drives microorganisms to states of minimal phenotypic complexity: only one EGM will be active when growth rate is maximised. The phenotype of a cell is only extended with one more EGM whenever growth becomes limited by an additional biophysical constraint, such as a limited solvent capacity of a cellular compartment. The theory presented here extends recent results on Elementary Flux Modes: the minimal building blocks of cellular growth models that lack the self-fabrication aspect. Our theory starts from basic biochemical and evolutionary considerations, and describes unicellular life, both in growth-promoting and in stress-inducing environments, in terms of EGMs.

Entities:  

Year:  2020        PMID: 31986156      PMCID: PMC7004393          DOI: 10.1371/journal.pcbi.1007559

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  40 in total

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Journal:  Biochem Soc Trans       Date:  2015-12       Impact factor: 5.407

2.  Enzyme allocation problems in kinetic metabolic networks: optimal solutions are elementary flux modes.

Authors:  Stefan Müller; Georg Regensburger; Ralf Steuer
Journal:  J Theor Biol       Date:  2013-12-01       Impact factor: 2.691

3.  Mechanistic links between cellular trade-offs, gene expression, and growth.

Authors:  Andrea Y Weiße; Diego A Oyarzún; Vincent Danos; Peter S Swain
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-18       Impact factor: 11.205

Review 4.  Mathematics of microbial populations.

Authors:  P R Painter; A G Marr
Journal:  Annu Rev Microbiol       Date:  1968       Impact factor: 15.500

Review 5.  Bacterial growth laws and their applications.

Authors:  Matthew Scott; Terence Hwa
Journal:  Curr Opin Biotechnol       Date:  2011-05-16       Impact factor: 9.740

6.  Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity.

Authors:  Q K Beg; A Vazquez; J Ernst; M A de Menezes; Z Bar-Joseph; A-L Barabási; Z N Oltvai
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-24       Impact factor: 11.205

7.  Coordination of bacterial proteome with metabolism by cyclic AMP signalling.

Authors:  Conghui You; Hiroyuki Okano; Sheng Hui; Zhongge Zhang; Minsu Kim; Carl W Gunderson; Yi-Ping Wang; Peter Lenz; Dalai Yan; Terence Hwa
Journal:  Nature       Date:  2013-08-07       Impact factor: 49.962

8.  Emergence of robust growth laws from optimal regulation of ribosome synthesis.

Authors:  Matthew Scott; Stefan Klumpp; Eduard M Mateescu; Terence Hwa
Journal:  Mol Syst Biol       Date:  2014-08-22       Impact factor: 11.429

9.  Maintaining maximal metabolic flux by gene expression control.

Authors:  Robert Planqué; Josephus Hulshof; Bas Teusink; Johannes C Hendriks; Frank J Bruggeman
Journal:  PLoS Comput Biol       Date:  2018-09-20       Impact factor: 4.475

10.  Shifts in growth strategies reflect tradeoffs in cellular economics.

Authors:  Douwe Molenaar; Rogier van Berlo; Dick de Ridder; Bas Teusink
Journal:  Mol Syst Biol       Date:  2009-11-03       Impact factor: 11.429

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  7 in total

1.  Searching for principles of microbial physiology.

Authors:  Frank J Bruggeman; Robert Planqué; Douwe Molenaar; Bas Teusink
Journal:  FEMS Microbiol Rev       Date:  2020-11-24       Impact factor: 16.408

2.  Bacterial cell proliferation: from molecules to cells.

Authors:  Alix Meunier; François Cornet; Manuel Campos
Journal:  FEMS Microbiol Rev       Date:  2021-01-08       Impact factor: 16.408

3.  Understanding FBA Solutions under Multiple Nutrient Limitations.

Authors:  Eunice van Pelt-KleinJan; Daan H de Groot; Bas Teusink
Journal:  Metabolites       Date:  2021-04-21

Review 4.  Intelligent host engineering for metabolic flux optimisation in biotechnology.

Authors:  Lachlan J Munro; Douglas B Kell
Journal:  Biochem J       Date:  2021-10-29       Impact factor: 3.857

Review 5.  The common message of constraint-based optimization approaches: overflow metabolism is caused by two growth-limiting constraints.

Authors:  Daan H de Groot; Julia Lischke; Riccardo Muolo; Robert Planqué; Frank J Bruggeman; Bas Teusink
Journal:  Cell Mol Life Sci       Date:  2019-11-22       Impact factor: 9.261

6.  From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions.

Authors:  Matteo Mori; Zhongge Zhang; Amir Banaei-Esfahani; Jean-Benoît Lalanne; Hiroyuki Okano; Ben C Collins; Alexander Schmidt; Olga T Schubert; Deok-Sun Lee; Gene-Wei Li; Ruedi Aebersold; Terence Hwa; Christina Ludwig
Journal:  Mol Syst Biol       Date:  2021-05       Impact factor: 11.429

7.  Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth.

Authors:  Stefan Müller; Diana Széliová; Jürgen Zanghellini
Journal:  PLoS Comput Biol       Date:  2022-02-01       Impact factor: 4.475

  7 in total

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