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9 Publications visible to you, out of a total of 9

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)

Antibiotic production is regulated by numerous signals, including the so-called bacterial hormones found in antibiotic producing organisms such as Streptomyces. These signals, the gamma-butyrolactones, are produced in very small quantities, which has hindered their structural elucidation and made it difficult to assess whether they are being produced. In this chapter, we describe a rapid small-scale extraction method from either solid or liquid cultures in scales of one plate or 50 ml of medium. Also described is a bioassay to detect the gamma-butyrolactones by determining either the production of pigmented antibiotic of Streptomyces coelicolor or kanamycin resistant growth on addition of the gamma-butyrolactones. We also describe some insights into the identification of the gamma-butyrolactone receptor and its targets and also the gel retardation conditions with three differently labeled probes.

Authors: Nai-Hua Hsiao, Marco Gottelt,

Date Published: 21st Apr 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)

Metabolic models have the potential to impact on genome annotation and on the interpretation of gene expression and other high throughput genome data. The genome of Streptomyces coelicolor genome has been sequenced and some 30% of the open reading frames (ORFs) lack any functional annotation. A recently constructed metabolic network model for S. coelicolor highlights biochemical functions which should exist to make the metabolic model complete and consistent. These include 205 reactions for which no ORF is associated. Here we combine protein functional predictions for the unannotated open reading frames in the genome with \'missing but expected\' functions inferred from the metabolic model. The approach allows function predictions to be evaluated in the context of the biochemical pathway reconstruction, and feed back iteratively into the metabolic model. We describe the approach and discuss a few illustrative examples.

Authors: Mansoor Saqi, Richard J B Dobson, Preben Kraben, ,

Date Published: 13th Nov 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)

Many microorganisms, including bacteria of the class Streptomycetes, produce various secondary metabolites including antibiotics to gain a competitive advantage in their natural habitat. The production of these compounds is highly coordinated in a population to expedite accumulation to an effective concentration. Furthermore, as antibiotics are often toxic even to their producers, a coordinated production allows microbes to first arm themselves with a defense mechanism to resist their own antibiotics before production commences. One possible mechanism of coordination among individuals is through the production of signaling molecules. The gamma-butyrolactone system in Streptomyces coelicolor is a model of such a signaling system for secondary metabolite production. The accumulation of these signaling molecules triggers antibiotic production in the population. A pair of repressor-amplifier proteins encoded by scbA and scbR mediates the production and action of one particular gamma-butyrolactone, SCB1. Based on the proposed interactions of scbA and scbR, a mathematical model was constructed and used to explore the ability of this system to act as a robust genetic switch. Stability analysis shows that the butyrolactone system exhibits bistability and, in response to a threshold SCB1 concentration, can switch from an OFF state to an ON state corresponding to the activation of genes in the cryptic type I polyketide synthase gene cluster, which are responsible for production of the hypothetical polyketide. The switching time is inversely related to the inducer concentration above the threshold, such that short pulses of low inducer concentration cannot switch on the system, suggesting its possible role in noise filtering. In contrast, secondary metabolite production can be triggered rapidly in a population of cells producing the butyrolactone signal due to the presence of an amplification loop in the system. S. coelicolor was perturbed experimentally by varying concentrations of SCB1, and the model simulations match the experimental data well. Deciphering the complexity of this butyrolactone switch will provide valuable insights into how robust and efficient systems can be designed using "simple" two-protein networks.

Authors: Sarika Mehra, Salim Charaniya, , Wei-Shou Hu

Date Published: 2nd May 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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