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Project: STREAM6

Abstract (Expand)

Background The transition from exponential to stationary phase in Streptomyces coelicolor is accompanied by a major metabolic switch and results in a strong activation of secondary metabolism. Here we have explored the underlying reorganization of the metabolome by combining computational predictions based on constraint-based modeling and detailed transcriptomics time course observations. Results We reconstructed the stoichiometric matrix of S. coelicolor, including the major antibiotic biosynthesis pathways, and performed flux balance analysis to predict flux changes that occur when the cell switches from biomass to antibiotic production. We defined the model input based on observed fermenter culture data and used a dynamically varying objective function to represent the metabolic switch. The predicted fluxes of many genes show highly significant correlation to the time series of the corresponding gene expression data. Individual mispredictions identify novel links between antibiotic production and primary metabolism. Conclusion Our results show the usefulness of constraint-based modeling for providing a detailed interpretation of time course gene expression data. Other Sections▼

Authors: , , The STREAM Consortium (stream), , , ,

Date Published: 2010

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples. RESULTS: Surprisingly, we find that the metabolic switch actually consists of multiple finely orchestrated switching events. Strongly coherent clusters of genes show drastic changes in gene expression already many hours before the classically defined transition phase where the switch from primary to secondary metabolism was expected. The main switch in gene expression takes only 2 hours, and changes in antibiotic biosynthesis genes are delayed relative to the metabolic rearrangements. Furthermore, global variation in morphogenesis genes indicates an involvement of cell differentiation pathways in the decision phase leading up to the commitment to antibiotic biosynthesis. CONCLUSIONS: Our study provides the first detailed insights into the complex sequence of early regulatory events during and preceding the major metabolic switch in S. coelicolor, which will form the starting point for future attempts at engineering antibiotic production in a biotechnological setting.

Authors: , Florian Battke, Alexander Herbig, , , , , , , , , Edward R Morrissey, Miguel A Juarez-Hermosillo, , Merle Nentwich, , Mudassar Iqbal, , , , , , , , Michael Bonin, , , , , , , , , ,

Date Published: 28th May 2009

Publication Type: Not specified

Abstract (Expand)

MOTIVATION: High-accuracy mass spectrometry is a popular technology for high-throughput measurements of cellular metabolites (metabolomics). One of the major challenges is the correct identification of the observed mass peaks, including the assignment of their empirical formula, based on the measured mass. RESULTS: We propose a novel probabilistic method for the assignment of empirical formulas to mass peaks in high-throughput metabolomics mass spectrometry measurements. The method incorporates information about possible biochemical transformations between the empirical formulas to assign higher probability to formulas that could be created from other metabolites in the sample. In a series of experiments, we show that the method performs well and provides greater insight than assignments based on mass alone. In addition, we extend the model to incorporate isotope information to achieve even more reliable formula identification. AVAILABILITY: A supplementary document, Matlab code, data and further information are available from http://www.dcs.gla.ac.uk/inference/metsamp.

Authors: Simon Rogers, Richard A Scheltema, Mark Girolami,

Date Published: 18th Dec 2008

Publication Type: Not specified

Abstract (Expand)

With the advent of a new generation of high-resolution mass spectrometers, the fields of proteomics and metabolomics have gained powerful new tools. In this paper, we demonstrate a novel computational method that improves the mass accuracy of the LTQ-Orbitrap mass spectrometer from an initial +/- 1-2 ppm, obtained by the standard software, to an absolute median of 0.21 ppm (SD 0.21 ppm). With the increased mass accuracy it becomes much easier to match mass chromatograms in replicates and different sample types, even if compounds are detected at very low intensities. The proposed method exploits the ubiquitous presence of background ions in LC-MS profiles for accurate alignment and internal mass calibration, making it applicable for all types of MS equipment. The accuracy of this approach will facilitate many downstream systems biology applications, including mass-based molecule identification, ab initio metabolic network reconstruction, and untargeted metabolomics in general.

Authors: Richard A Scheltema, Anas Kamleh, David Wildridge, Charles Ebikeme, David G Watson, Michael P Barrett, ,

Date Published: 22nd Oct 2008

Publication Type: Not specified

Abstract (Expand)

The computational reconstruction and analysis of cellular models of microbial metabolism is one of the great success stories of systems biology. The extent and quality of metabolic network reconstructions is, however, limited by the current state of biochemical knowledge. Can experimental high-throughput data be used to improve and expand network reconstructions to include unexplored areas of metabolism? Recent advances in experimental technology and analytical methods bring this aim an important step closer to realization. Data integration will play a particularly important part in exploiting the new experimental opportunities.

Authors: , Dennis Vitkup, Michael P Barrett

Date Published: 21st Nov 2007

Publication Type: Not specified

Abstract (Expand)

SUMMARY: We present a Cytoscape plugin for the inference and visualization of networks from high-resolution mass spectrometry metabolomic data. The software also provides access to basic topological analysis. This open source, multi-platform software has been successfully used to interpret metabolomic experiments and will enable others using filtered, high mass accuracy mass spectrometric data sets to build and analyse networks. AVAILABILITY: http://compbio.dcs.gla.ac.uk/fabien/abinitio/abinitio.html

Authors: Fabien Jourdan, , Michael P Barrett, David Gilbert

Date Published: 14th Nov 2007

Publication Type: Not specified

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