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      Shifts in growth strategies reflect tradeoffs in cellular economics

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          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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          Most cited references52

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          On the origin of cancer cells.

          O WARBURG (1956)
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            Exploring the metabolic and genetic control of gene expression on a genomic scale.

            DNA microarrays containing virtually every gene of Saccharomyces cerevisiae were used to carry out a comprehensive investigation of the temporal program of gene expression accompanying the metabolic shift from fermentation to respiration. The expression profiles observed for genes with known metabolic functions pointed to features of the metabolic reprogramming that occur during the diauxic shift, and the expression patterns of many previously uncharacterized genes provided clues to their possible functions. The same DNA microarrays were also used to identify genes whose expression was affected by deletion of the transcriptional co-repressor TUP1 or overexpression of the transcriptional activator YAP1. These results demonstrate the feasibility and utility of this approach to genomewide exploration of gene expression patterns.
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              Optimality and evolutionary tuning of the expression level of a protein.

              Different proteins have different expression levels. It is unclear to what extent these expression levels are optimized to their environment. Evolutionary theories suggest that protein expression levels maximize fitness, but the fitness as a function of protein level has seldom been directly measured. To address this, we studied the lac system of Escherichia coli, which allows the cell to use the sugar lactose for growth. We experimentally measured the growth burden due to production and maintenance of the Lac proteins (cost), as well as the growth advantage (benefit) conferred by the Lac proteins when lactose is present. The fitness function, given by the difference between the benefit and the cost, predicts that for each lactose environment there exists an optimal Lac expression level that maximizes growth rate. We then performed serial dilution evolution experiments at different lactose concentrations. In a few hundred generations, cells evolved to reach the predicted optimal expression levels. Thus, protein expression from the lac operon seems to be a solution of a cost-benefit optimization problem, and can be rapidly tuned by evolution to function optimally in new environments.
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                Author and article information

                Journal
                Mol Syst Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2009
                03 November 2009
                : 5
                : 323
                Affiliations
                [1 ]Centre for Integrative Bioinformatics (IBIVU), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
                [2 ]Information and Communication Theory Group, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
                [3 ]Top Institute Food and Nutrition, Wageningen, The Netherlands
                [4 ]Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands
                [5 ]Netherlands Consortium for Systems Biology, Amsterdam, The Netherlands
                Author notes
                [a ]Centre for Integrative Bioinformatics (IBIVU), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands. Tel.: +31 205 987738; Fax: +31 205 987229; E-mail: douwe.molenaar@ 123456falw.vu.nl
                Article
                msb200982
                10.1038/msb.2009.82
                2795476
                19888218
                c85df9df-3ca7-4dd2-aa06-2912d7e41547
                Copyright © 2009, EMBO and Nature Publishing Group

                This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits distribution and reproduction in any medium, provided the original author and source are credited. Creation of derivative works is permitted but the resulting work may be distributed only under the same or similar licence to this one. This licence does not permit commercial exploitation without specific permission.

                History
                : 23 April 2009
                : 5 October 2009
                Page count
                Pages: 1
                Categories
                Perspectives

                Quantitative & Systems biology
                overflow metabolism,metabolic efficiency,growth,ribosome content,warburg effect

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