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An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae.

ABSTRACT: Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations.We report a significantly improved version (v. 2) of a probabilistic functional gene network of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis.YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.

SUBMITTER: Lee I

PROVIDER: S-EPMC1991590 | biostudies-literature | 2007 Oct

REPOSITORIES: biostudies-literature

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An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae.

Lee Insuk I Li Zhihua Z Marcotte Edward M EM

PloS one 20071003 10

<h4>Background</h4>Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding sp ...[more]

PMID: 17912365

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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.

Project description:Folates are a group of B9 vitamins playing an important role in many metabolic processes such as methylation reactions, nucleotide synthesis or oxidation and reduction processes. However, humans are not able to synthesize folates de novo and thus rely on external sources thereof. Baker's yeast (Saccharomyces cerevisiae) has been shown to produce high amounts of this vitamin but extensive identification of its folate metabolism is still lacking. Therefore, we optimized and compared different sample preparation and purification procedures applying solid phase extraction (SPE). Strong anion exchange (SAX), C18 and hydrophilic-lipophilic-balanced (HLB) materials were tested for their applicability in future metabolomics studies. SAX turned out to be the preferred material for the quantitative purification of folates. Qualification of several folate vitamers was achieved by ultra-high pressure liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-ToF-MS) measurements and quantification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS) applying stable isotope dilution assays (SIDAs). The oxidation product s-pyrazino-triazine (MeFox) was included into the SIDA method for total folate determination and validation. Applying the best protocol (SAX) in regard to folate recovery, we analyzed 32 different vitamers in different polyglutamate states up to nonaglutamates, of which we could further identify 26 vitamers based on tandem-MS (MS2) spectra. Total folate quantification revealed differences in formyl folate contents depending on the cartridge chemistry used for purification. These are supposedly a result of interconversion reactions occurring during sample preparation due to variation in pH adjustments for the different purification protocols. The occurrence of interconversion and oxidation reactions should be taken into consideration in sample preparation procedures for metabolomics analyses with a focus on folates.

Dataset Information

An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae.

Publications

An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae.

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