Dataset Information

Reconstruction and evaluation of the synthetic bacterial MEP pathway in Saccharomyces cerevisiae.

ABSTRACT: Isoprenoids, which are a large group of natural and chemical compounds with a variety of applications as e.g. fragrances, pharmaceuticals and potential biofuels, are produced via two different metabolic pathways, the mevalonate (MVA) pathway and the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway. Here, we attempted to replace the endogenous MVA pathway in Saccharomyces cerevisiae by a synthetic bacterial MEP pathway integrated into the genome to benefit from its superior properties in terms of energy consumption and productivity at defined growth conditions. It was shown that the growth of a MVA pathway deficient S. cerevisiae strain could not be restored by the heterologous MEP pathway even when accompanied by the co-expression of genes erpA, hISCA1 and CpIscA involved in the Fe-S trafficking routes leading to maturation of IspG and IspH and E. coli genes fldA and fpr encoding flavodoxin and flavodoxin reductase believed to be responsible for electron transfer to IspG and IspH.

SUBMITTER: Partow S

PROVIDER: S-EPMC3532213 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Reconstruction and evaluation of the synthetic bacterial MEP pathway in Saccharomyces cerevisiae.

Partow Siavash S Siewers Verena V Daviet Laurent L Schalk Michel M Nielsen Jens J

PloS one 20121228 12

Isoprenoids, which are a large group of natural and chemical compounds with a variety of applications as e.g. fragrances, pharmaceuticals and potential biofuels, are produced via two different metabolic pathways, the mevalonate (MVA) pathway and the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway. Here, we attempted to replace the endogenous MVA pathway in Saccharomyces cerevisiae by a synthetic bacterial MEP pathway integrated into the genome to benefit from its superior properties in terms o ...[more]

PMID: 23285068

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Project description:BackgroundCurrent advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC).ResultsOur goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure.ConclusionWe propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

Project description:BACKGROUND: Fungal polyketides include commercially important pharmaceuticals and food additives, e.g. the cholesterol-lowering statins and the red and orange monascus pigments. Presently, production relies on isolation of the compounds from the natural producers, and systems for heterologous production in easily fermentable and genetically engineerable organisms, such as Saccharomyces cerevisiae and Escherichia coli are desirable. Rubrofusarin is an orange polyketide pigment that is a common intermediate in many different fungal biosynthetic pathways. RESULTS: In this study, we established a biosynthetic pathway for rubrofusarin in S. cerevisiae. First, the Fusarium graminearum gene encoding polyketide synthase 12 (PKS12) was heterologously co-expressed with the Aspergillus fumigatus gene encoding phosphopantetheinyl transferase (npgA) resulting in production of YWA1. This aromatic heptaketide intermediate was converted into nor-rubrofusarin upon expression of the dehydratase gene aurZ from the aurofusarin gene cluster of F. graminearum. Final conversion into rubrofusarin was achieved by expression of the O-methyltransferase encoding gene aurJ, also obtained from the aurofusarin gene cluster, resulting in a titer of 1.1 mg/L. Reduced levels of rubrofusarin were detected when expressing PKS12, npgA, and aurJ alone, presumably due to spontaneous conversion of YWA1 to nor-rubrofusarin. However, the co-expression of aurZ resulted in an approx. six-fold increase in rubrofusarin production. CONCLUSIONS: The reconstructed pathway for rubrofusarin in S. cerevisiae allows the production of a core scaffold molecule with a branch-point role in several fungal polyketide pathways, thus paving the way for production of further natural pigments and bioactive molecules. Furthermore, the reconstruction verifies the suggested pathway, and as such, it is the first example of utilizing a synthetic biological "bottom up" approach for the validation of a complex fungal polyketide pathway.

Project description:BackgroundEfforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature.ResultsYeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model's predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3.ConclusionsYeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible.

Dataset Information

Reconstruction and evaluation of the synthetic bacterial MEP pathway in Saccharomyces cerevisiae.

Publications

Reconstruction and evaluation of the synthetic bacterial MEP pathway in Saccharomyces cerevisiae.

Similar Datasets

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