Shifts in growth strategies reflect tradeoffs in cellular economics

By Douwe Molenaar, Rogier van Berlo, D. de Ridder, Bas Teusink. Molecular Systems Biology, 2009

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The growth rate‐dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self‐replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self‐replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies.

Subfields: General Agricultural and Biological Sciences, Molecular Biology, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/ae61a69bf1667f08a10e7d61bddeaa69604914c3

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Citations in the corpus

The Warburg Effect: How Does it Benefit Cancer Cells? (2016, background): “Another issue is that, in conditions completely isolated from the environment, such as in the growth phase of unicellular yeast, the Warburg Effect remains the choice of energy metabolism from glucose [38].”
Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism (2014, background): “Specifically, to what extent are present-day metabolic pathways the result of evolutionary optimization rather than fossilized accidents? In recent years various aspects of central metabolism have been explained on the basis of specific selection pressures and constraints imposed during evolution [1”
Improving the phenotype predictions of a yeast genome‐scale metabolic model by incorporating enzymatic constraints (2017, methodology): “Alternative approaches such as resource balance analysis (Goelzer et al, 2015), self-replicating models (Molenaar et al, 2009; Berkhout et al, 2013), and whole-cell models (Karr et al, 2012) have also been developed to account for protein limitations.”
Probiotics and competitive exclusion of pathogens in shrimp aquaculture (2020, background): “…et al., 2009), has been observed in a number of fast-growing bacterial and fungal species including Saccharomyces cerevisiae, Escherichia coli and Bacillus subtilis (van Dijken et al., 1993; Vemuri et al., 2006; Sonenshein, 2007; Molenaar et al., 2009; Basan et al., 2015; LaCroix et al., 2015).”
A mechanistic link between cellular trade-offs, gene expression and growth (2015, neutral): “In contrast to other approaches [13, 14], we emphasize that we do not optimize either growth rate or any other physiological variable.”
Constraint-based models predict metabolic and associated cellular functions (2014, background): “Other studies have questioned the universality of the objective function of biomass growth for predicting relevant metabolic fluxes 38–40 .”