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. 2009:5:323.
doi: 10.1038/msb.2009.82. Epub 2009 Nov 3.

Shifts in growth strategies reflect tradeoffs in cellular economics

Douwe Molenaar  1 , Rogier van Berlo, Dick de Ridder, Bas Teusink
Affiliations

Shifts in growth strategies reflect tradeoffs in cellular economics

Douwe Molenaar et al. Mol Syst Biol. 2009.

Abstract

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.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
A general trend in the use of alternative metabolic pathways and a comparison with the predictions of different models. (A) A schematic representation of the metabolism of a cell that has a metabolically or energetically efficient and an inefficient pathway to regenerate NAD. A small fraction of the intermediate metabolite is used in anabolism for biomass synthesis. (B) Use of efficient and inefficient pathways at different growth rates (or, equivalently, at different substrate concentrations) as a fraction of the total flux, which equals the flux through glycolysis, in this case. The gradually increased use of inefficient pathways is a generally observed phenomenon. The lower panel shows how different types of growth models try to explain the use of these alternative pathways. Predictions from FBA are the following: as growth rate increases (indicated by the arrow), the flux through the efficient pathway hits its maximal limit (indicated by the butterfly symbol) and the surplus of substrate flows through the inefficient pathway. In what we call here the ‘Composite hypothesis', the efficient pathway is active when cells cooperate in a structured environment (left) and the inefficient pathway is active when in free-living cells the ATP production rate, as a proxy for the growth rate, is maximized (right). The self-replicator model predicts a shift from efficient to inefficient use of substrate as the growth rate increases, only as a result of growth rate maximization. The self-replicator model is explained in this paper. For the other models we also refer to reviews of FBA (Kauffman et al, 2003) and the Composite hypothesis (Pfeiffer and Schuster, 2005).
Figure 2
Figure 2
The simplest self-replicator. It consists of a ‘ribosome' that reproduces by converting a precursor to copies of itself. The types of arrows are also used in the other figures to indicate general metabolic conversions and protein synthesis in particular. Conceptually, however, there is no difference between these types of reactions.
Figure 3
Figure 3
Optimal regulation of a basic self-replicator, consisting of four enzymes and a membrane. The cell (A) consists of a pool of ribosomes that catalyze protein synthesis, including their own; a substrate transporter protein pool; a metabolic enzyme pool and a pool of enzymes that synthesize the lipid component of the membrane. The membrane consists of transporter protein and lipid. The cell accumulates a substrate from the environment and converts it into a metabolite that is used for protein synthesis and lipid synthesis. It can regulate the relative proportion of each of the protein pools by adjusting the amount of ribosomes that is engaged in the synthesis of each of the four proteins. (B, C) The results of numerical optimizations are shown. The individual protein pool fractions relative to total protein and the volume/surface ratio (cell shape parameter in the model description in the Supplementary information) were optimized (C) so as to maximize the growth rate (B) at different extracellular substrate concentrations. The points indicate the results of numerical simulations. (D) The experimental results of glucose uptake capacity in Klebsiella pneumoniae at different growth rates (Teixeira de Mattos and Neijssel, 1997). (E) The relative rate of synthesis of ribosomal protein to that of total protein (Gausing, 1977) in E. coli at different growth rates. Under balanced growth these relative rates directly translate into relative amounts of protein.
Figure 4
Figure 4
Prediction of switching or shifting of optimal metabolic strategies. (A) The two alternative metabolically efficient (MetEf) and catalytically efficient (CatEf) pathways that replace the ‘Metabolic pathway' in Figure 3A. The CatEf pathway is metabolically inefficient because it not only generates less Precursor per Substrate molecule, but also requires less protein (or equivalently, has higher kcat) than the MetEf pathway to generate a similar flux of Precursor. The graph on the right shows the optimal relative flux through each of these pathways as a function of the extracellular substrate concentration. (B) A different configuration of metabolism, namely one in which an energy intermediate (ATP) is produced with different efficiencies in the alternative pathways. The ATP is used to activate an intermediate to a precursor. Also here the CatEf pathway has a higher kcat than the MetEf pathway. In contrast to the configuration in panel A, a mixed strategy is optimal at a range of substrate concentrations in this configuration (see the text for an explanation). (C, D) Experimental data of shifts in metabolism of L. lactis (Thomas et al, 1979) (C) and S. cerevisiae (van Hoek et al, 1998) (D). L. lactis shifts from the metabolically efficient mixed-acid fermentation at low growth rates to lactic acid fermentation at high growth rates, whereas S. cerevisiae shifts from respiratory metabolism to partial ethanol fermentation.
Figure 5
Figure 5
The effect of limitation by a second substrate on metabolic switching. (A) A second substrate, N, is introduced in the model that has to be taken up by a separate transporter and combined by the ribosome in a bimolecular reaction with the Precursor during the synthesis of protein. (B) The result from numerical simulations at low and high availability of N is shown. The switch from metabolically efficient to catalytically efficient C-metabolism takes place at lower growth rates under N-limitation.
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