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Growth Control of the Eukaryote Cell: a Systems Biology

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Growth Control of the Eukaryote Cell: a Systems Biology BioMed Central Open Access Research article Growth control of the eukaryote cell: a systems biology study in yeast Juan I Castrillo1¤, Leo A Zeef1¤, David C Hoyle2¤, Nianshu Zhang1, Andrew Hayes1, David CJ Gardner1, Michael J Cornell1,3, June Petty1, Luke Hakes1, Leanne Wardleworth1, Bharat Rash1, Marie Brown4, Warwick B Dunn6, David Broadhurst4,6, Kerry O’Donoghue5, Svenja S Hester5, Tom PJ Dunkley5, Sarah R Hart4, Neil Swainston6, Peter Li6, Simon J Gaskell4,6, Norman W Paton3,6, Kathryn S Lilley5, Douglas B Kell4,6 and Stephen G Oliver1,6 Addresses: 1Faculty of Life Sciences, Michael Smith Building, University of Manchester, Oxford Road, Manchester M13 9PT, UK. 2Northwest Institute for Bio-Health Informatics (NIBHI), School of Medicine, Stopford Building, University of Manchester, Oxford Road, Manchester M13 9PT, UK. 3School of Computer Science, Kilburn Building, University of Manchester, Oxford Road, Manchester M13 9PL, UK. 4School of Chemistry, Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess St, Manchester M1 7DN, UK. 5Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Downing Site, Cambridge CB2 1QW, UK. 6Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, 131 Princess St, Manchester M1 7DN, UK. ¤These authors contributed equally to this work. Correspondence: Stephen G Oliver. E-mail: [email protected] Published: 30 April 2007 Received: 21 July 2006 Revised: 20 November 2006 Journal of Biology 2007, 6:4 Accepted: 7 February 2007 The electronic version of this article is the complete one and can be found online at http://jbiol.com/content/6/2/4 © 2007 Castrillo et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Cell growth underlies many key cellular and developmental processes, yet a limited number of studies have been carried out on cell-growth regulation. Comprehensive studies at the transcriptional, proteomic and metabolic levels under defined controlled conditions are currently lacking. Results: Metabolic control analysis is being exploited in a systems biology study of the eukaryotic cell. Using chemostat culture, we have measured the impact of changes in flux (growth rate) on the transcriptome, proteome, endometabolome and exometabolome of the yeast Saccharomyces cerevisiae. Each functional genomic level shows clear growth-rate- associated trends and discriminates between carbon-sufficient and carbon-limited conditions. Genes consistently and significantly upregulated with increasing growth rate are frequently Journal of Biology 2007, 6:4 4.2 Journal of Biology 2007, Volume 6, Article 4 Castrillo et al. http://jbiol.com/content/6/2/4 essential and encode evolutionarily conserved proteins of known function that participate in many protein-protein interactions. In contrast, more unknown, and fewer essential, genes are downregulated with increasing growth rate; their protein products rarely interact with one another. A large proportion of yeast genes under positive growth-rate control share orthologs with other eukaryotes, including humans. Significantly, transcription of genes encoding components of the TOR complex (a major controller of eukaryotic cell growth) is not subject to growth-rate regulation. Moreover, integrative studies reveal the extent and importance of post-transcriptional control, patterns of control of metabolic fluxes at the level of enzyme synthesis, and the relevance of specific enzymatic reactions in the control of metabolic fluxes during cell growth. Conclusions: This work constitutes a first comprehensive systems biology study on growth- rate control in the eukaryotic cell. The results have direct implications for advanced studies on cell growth, in vivo regulation of metabolic fluxes for comprehensive metabolic engineering, and for the design of genome-scale systems biology models of the eukaryotic cell. Background under controlled environmental conditions [14-17]. How- Metabolic control analysis [1] is a conceptual and mathe- ever, the majority of chemostat studies have mainly focused matical formalism that models the relative contributions of on the characterization of environmental responses at a individual effectors in a pathway to both the flux through single growth rate [18-20], and so the mechanisms involved the pathway and the concentrations of intermediates within in the regulation of growth-rate-related genes are still poorly it. To exploit metabolic control analysis in an initial systems understood. Previous investigations have been confined to biology analysis of the eukaryotic cell, two categories of the RNA level; however, an increasing number of studies experiments are required. In category 1, flux is changed and demonstrate the importance of post-transcriptional (trans- the impact on the levels of the direct and indirect products lational and post-translational) mechanisms [21-24]. This of gene action is measured. In category 2, the levels of indi- evidence for control being exerted at multiple levels empha- vidual gene products are altered, and the impact on the flux sizes the need to extend metabolic control analysis to is measured. In this category 1 study, we have measured the include the concept of modular control [25]. impact of changing the flux on the transcriptome, pro- teome, and metabolome of Saccharomyces cerevisiae. In this Comprehensive high-throughput analyses at the levels of whole-cell analysis, flux equates to growth rate. mRNAs, proteins, and metabolites, and studies on gene expression patterns are required for systems biology studies Cell growth (the increase in cell mass through macromolec- of cell growth [4,26-29]. Although such comprehensive data ular synthesis) requires the synthesis of cellular components sets are lacking, many studies have pointed to a central role in precise, stoichiometric quantities, and must be subject to for the target-of-rapamycin (TOR) signal transduction tight coordinate control [2-6]. Cell growth underpins many pathway in growth control. TOR is a serine/threonine kinase critical cellular and developmental processes, yet compre- that has been conserved from yeasts to mammals; it inte- hensive studies on growth rate and its control have lagged grates signals from nutrients or growth factors to regulate cell behind those on cell-cycle progression [7,8], cell prolifera- growth and cell-cycle progression coordinately [3,30-33]. tion [4,6] and coupling between cell growth and division [9,10]. A limited number of studies in batch (flask) cultures We have studied the control of the yeast transcriptome, pro- in complex media have been reported for the important teome, and metabolome in a manner that allows the sepa- model eukaryote Saccharomyces cerevisiae. These showed that ration of growth-rate effects from nutritional effects, and the coordinate expression of ribosomal protein genes with have paid particular attention to the role of the rapamycin- growth rate appeared regulated almost entirely at the tran- sensitive TOR complex 1 (TORC1) [32] in mediating scriptional level [11-13]. However, these batch studies growth-rate control. Both the concepts and the data gener- could not separate growth rate from nutritional effects [14]. ated by these experiments should provide a useful founda- Chemostat cultures in defined media constitute an adequate tion for the construction of dynamic models of the yeast cell alternative, allowing the study of physiological patterns in systems biology [26-28]. Journal of Biology 2007, 6:4 http://jbiol.com/content/6/2/4 Journal of Biology 2007, Volume 6, Article 4 Castrillo et al. 4.3 Results and discussion yeast cells are well-adapted to growth under carbon-limited Growth-rate effects revealed at all ‘omic’ levels conditions and are able to adjust the individual fluxes We wished to study the impact of growth rate on the total through their metabolic network to regulate overflow complement of mRNA molecules, proteins, and metabo- metabolism whatever overall flux is imposed by the external lites in S. cerevisiae, independent of any nutritional or other supply of carbon substrate. This result is congruent with our physiological effects. To achieve this, we carried out our data from category 2 experiments (D. Delneri and S.G.O., analyses on yeast grown in steady-state chemostat culture unpublished work) in which we have examined the effect under four different nutrient limitations (glucose, ammo- that reducing the copy number of individual genes in nium, phosphate, and sulfate) at three different dilution diploid cells has on flux by performing competition experi- (that is, growth) rates (D = µ = 0.07, 0.1, and 0.2/hour, ments, in chemostat cultures, between yeast strains het- equivalent to population doubling times (Td) of 10 hours, erozygous for individual gene deletions. 7 hours, and 3.5 hours, respectively; µ = specific growth rate defined as grams of biomass generated per gram of For all three levels of ‘omic analysis, the data show a clear biomass present per unit time). We then looked for distinction between carbon-limited and carbon-sufficient changes that correlated with growth rate under all four cells (Figure 1). Once the data from the carbon-limited nutrient-limiting conditions,
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