Dataset Information

The genome-scale metabolic model iIN800 of Saccharomyces cerevisiae and its validation: a scaffold to query lipid metabolism.

ABSTRACT: BACKGROUND: Up to now, there have been three published versions of a yeast genome-scale metabolic model: iFF708, iND750 and iLL672. All three models, however, lack a detailed description of lipid metabolism and thus are unable to be used as integrated scaffolds for gaining insights into lipid metabolism from multilevel omic measurement technologies (e.g. genome-wide mRNA levels). To overcome this limitation, we reconstructed a new version of the Saccharomyces cerevisiae genome-scale model, iIN800 that includes a more rigorous and detailed description of lipid metabolism. RESULTS: The reconstructed metabolic model comprises 1446 reactions and 1013 metabolites. Beyond incorporating new reactions involved in lipid metabolism, we also present new biomass equations that improve the predictive power of flux balance analysis simulations. Predictions of both growth capability and large scale in silico single gene deletions by iIN800 were consistent with experimental data. In addition, 13C-labeling experiments validated the new biomass equations and calculated intracellular fluxes. To demonstrate the applicability of iIN800, we show that the model can be used as a scaffold to reveal the regulatory importance of lipid metabolism precursors and intermediates that would have been missed in previous models from transcriptome datasets. CONCLUSION: Performing integrated analyses using iIN800 as a network scaffold is shown to be a valuable tool for elucidating the behavior of complex metabolic networks, particularly for identifying regulatory targets in lipid metabolism that can be used for industrial applications or for understanding lipid disease states.

SUBMITTER: Nookaew I

PROVIDER: S-EPMC2542360 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The genome-scale metabolic model iIN800 of Saccharomyces cerevisiae and its validation: a scaffold to query lipid metabolism.

Nookaew Intawat I Jewett Michael C MC Meechai Asawin A Thammarongtham Chinae C Laoteng Kobkul K Cheevadhanarak Supapon S Nielsen Jens J Bhumiratana Sakarindr S

BMC systems biology 20080807

<h4>Background</h4>Up to now, there have been three published versions of a yeast genome-scale metabolic model: iFF708, iND750 and iLL672. All three models, however, lack a detailed description of lipid metabolism and thus are unable to be used as integrated scaffolds for gaining insights into lipid metabolism from multilevel omic measurement technologies (e.g. genome-wide mRNA levels). To overcome this limitation, we reconstructed a new version of the Saccharomyces cerevisiae genome-scale model ...[more]

PMID: 18687109

Similar Datasets

Project description:BackgroundThe yeast Saccharomyces cerevisiae plays an essential role in the fermentation of lignocellulosic hydrolysates. Weak organic acids in lignocellulosic hydrolysate can hamper the use of this renewable resource for fuel and chemical production. Plasma-membrane remodeling has recently been found to be involved in acquiring tolerance to organic acids, but the mechanisms responsible remain largely unknown. Therefore, it is essential to understand the underlying mechanisms of acid tolerance of S. cerevisiae for developing robust industrial strains.ResultsWe have performed a comparative analysis of lipids and fatty acids in S. cerevisiae grown in the presence of four different weak acids. The general response of the yeast to acid stress was found to be the accumulation of triacylglycerols and the degradation of steryl esters. In addition, a decrease in phosphatidic acid, phosphatidylcholine, phosphatidylserine and phosphatidylethanolamine, and an increase in phosphatidylinositol were observed. Loss of cardiolipin in the mitochondria membrane may be responsible for the dysfunction of mitochondria and the dramatic decrease in the rate of respiration of S. cerevisiae under acid stress. Interestingly, the accumulation of ergosterol was found to be a protective mechanism of yeast exposed to organic acids, and the ERG1 gene in ergosterol biosynthesis played a key in ergosterol-mediated acid tolerance, as perturbing the expression of this gene caused rapid loss of viability. Interestingly, overexpressing OLE1 resulted in the increased levels of oleic acid (18:1n-9) and an increase in the unsaturation index of fatty acids in the plasma membrane, resulting in higher tolerance to acetic, formic and levulinic acid, while this change was found to be detrimental to cells exposed to lipophilic cinnamic acid.ConclusionsComparison of lipid profiles revealed different remodeling of lipids, FAs and the unsaturation index of the FAs in the cell membrane in response of S. cerevisiae to acetic, formic, levulinic and cinnamic acid, depending on the properties of the acid. In future work, it will be necessary to combine lipidome and transcriptome analysis to gain a better understanding of the underlying regulation network and interactions between central carbon metabolism (e.g., glycolysis, TCA cycle) and lipid biosynthesis.

Project description:BackgroundTo engineer Saccharomyces cerevisiae for efficient xylose utilization, a fungal pathway consisting of xylose reductase, xylitol dehydrogenase, and xylulose kinase is often introduced to the host strain. Despite extensive in vitro studies on the xylose pathway, the intracellular metabolism rewiring in response to the heterologous xylose pathway remains largely unknown. In this study, we applied 13C metabolic flux analysis and stoichiometric modeling to systemically investigate the flux distributions in a series of xylose utilizing S. cerevisiae strains.ResultsAs revealed by 13C metabolic flux analysis, the oxidative pentose phosphate pathway was actively used for producing NADPH required by the fungal xylose pathway during xylose utilization of recombinant S. cerevisiae strains. The TCA cycle activity was found to be tightly correlated with the requirements of maintenance energy and biomass yield. Based on in silico simulations of metabolic fluxes, reducing the cell maintenance energy was found crucial to achieve the optimal xylose-based ethanol production. The stoichiometric modeling also suggested that both the cofactor-imbalanced and cofactor-balanced pathways could lead to optimal ethanol production, by flexibly adjusting the metabolic fluxes in futile cycle. However, compared to the cofactor-imbalanced pathway, the cofactor-balanced xylose pathway can lead to optimal ethanol production in a wider range of fermentation conditions.ConclusionsBy applying 13C-MFA and in silico flux balance analysis to a series of recombinant xylose-utilizing S. cerevisiae strains, this work brings new knowledge about xylose utilization in two aspects. First, the interplays between the fungal xylose pathway and the native host metabolism were uncovered. Specifically, we found that the high cell maintenance energy was one of the key factors involved in xylose utilization. Potential strategies to reduce the cell maintenance energy, such as adding exogenous nutrients and evolutionary adaptation, were suggested based on the in vivo and in silico flux analysis in this study. In addition, the impacts of cofactor balance issues on xylose utilization were systemically investigated. The futile pathways were identified as the key factor to adapt to different degrees of cofactor imbalances and suggested as the targets for further engineering to tackle cofactor-balance issues.

Dataset Information

The genome-scale metabolic model iIN800 of Saccharomyces cerevisiae and its validation: a scaffold to query lipid metabolism.

Publications

The genome-scale metabolic model iIN800 of Saccharomyces cerevisiae and its validation: a scaffold to query lipid metabolism.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets