Elementary approaches to microbial growth rate maximisation

Daan Hugo de Groot

Research output: PhD ThesisPhD-Thesis - Research and graduation internal

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Abstract

This thesis, called Elementary approaches to microbial growth rate maximisation, reports on a theoretical search for principles underlying single cell growth, in particular for microbial species that are selected for fast growth rates. First, the optimally growing cell is characterised in terms of its elementary modes. We prove an extremum principle: a cell that maximises a metabolic rate uses few Elementary Flux Modes (EFMs, the minimal pathways that support steady-state metabolism). The number of active EFMs is bounded by the number of growth-limiting constraints. Later, this extremum principle is extended in a theory that explicitly accounts for self-fabrication. For this, we had to define the elementary modes that underlie balanced self-fabrication: minimal self-supporting sets of expressed enzymes that we call Elementary Growth Modes (EGMs). It turns out that many of the results for EFMs can be extended to their more general self-fabrication analogue. Where the above extremum principles tell us that few elementary modes are used by a rate-maximising cell, it does not tell us how the cell can find them. Therefore, we also search for an elementary adaptation method. It turns out that stochastic phenotype switching with growth rate dependent switching rates provides an adaptation mechanism that is often competitive with more conventional regulatory-circuitry based mechanisms. The derived theory is applied in two ways. First, the extremum principles are used to review the mathematical fundaments of all optimisation-based explanations of overflow metabolism. Second, a computational tool is presented that enumerates Elementary Conversion Modes. These elementary modes can be computed for larger networks than EFMs and EGMs, and still provide an overview of the metabolic capabilities of an organism.
Original languageEnglish
QualificationPhD
Awarding Institution
  • Vrije Universiteit Amsterdam
Supervisors/Advisors
  • Teusink, Bas, Supervisor
  • Bruggeman, FJ, Co-supervisor
  • Planque, Bob, Co-supervisor
Award date10 Mar 2021
Place of PublicationAmsterdam
Publisher
Print ISBNs9789464164183
Publication statusPublished - 10 Mar 2021

Keywords

  • Elementary Mode Analysis
  • Growth rate dependent phenotype switching
  • Growth rate maximisation
  • Microbial metabolism
  • Overflow metabolism
  • ecmtool

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