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Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans.

ABSTRACT: BACKGROUND: Aspergillus nidulans (the asexual form of Emericella nidulans) is a model organism for aspergilli, which are an important group of filamentous fungi that encompasses human and plant pathogens as well as industrial cell factories. Aspergilli have a highly diversified metabolism and, because of their medical, agricultural and biotechnological importance, it would be valuable to have an understanding of how their metabolism is regulated. We therefore conducted a genome-wide transcription analysis of A. nidulans grown on three different carbon sources (glucose, glycerol, and ethanol) with the objective of identifying global regulatory structures. Furthermore, we reconstructed the complete metabolic network of this organism, which resulted in linking 666 genes to metabolic functions, as well as assigning metabolic roles to 472 genes that were previously uncharacterized. RESULTS: Through combination of the reconstructed metabolic network and the transcription data, we identified subnetwork structures that pointed to coordinated regulation of genes that are involved in many different parts of the metabolism. Thus, for a shift from glucose to ethanol, we identified coordinated regulation of the complete pathway for oxidation of ethanol, as well as upregulation of gluconeogenesis and downregulation of glycolysis and the pentose phosphate pathway. Furthermore, on change in carbon source from glucose to ethanol, the cells shift from using the pentose phosphate pathway as the major source of NADPH (nicotinamide adenine dinucleotide phosphatase, reduced form) for biosynthesis to use of the malic enzyme. CONCLUSION: Our analysis indicates that some of the genes are regulated by common transcription factors, making it possible to establish new putative links between known transcription factors and genes through clustering.

SUBMITTER: David H

PROVIDER: S-EPMC1794588 | biostudies-literature | 2006

REPOSITORIES: biostudies-literature

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Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans.

David Helga H Hofmann Gerald G Oliveira Ana Paula AP Jarmer Hanne H Nielsen Jens J

Genome biology 20060101 11

<h4>Background</h4>Aspergillus nidulans (the asexual form of Emericella nidulans) is a model organism for aspergilli, which are an important group of filamentous fungi that encompasses human and plant pathogens as well as industrial cell factories. Aspergilli have a highly diversified metabolism and, because of their medical, agricultural and biotechnological importance, it would be valuable to have an understanding of how their metabolism is regulated. We therefore conducted a genome-wide trans ...[more]

PMID: 17107606

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Project description:BackgroundAspergillus nidulans is a member of a diverse group of filamentous fungi, sharing many of the properties of its close relatives with significance in the fields of medicine, agriculture and industry. Furthermore, A. nidulans has been a classical model organism for studies of development biology and gene regulation, and thus it has become one of the best-characterized filamentous fungi. It was the first Aspergillus species to have its genome sequenced, and automated gene prediction tools predicted 9,451 open reading frames (ORFs) in the genome, of which less than 10% were assigned a function.ResultsIn this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated, and to look for candidate ORFs in the genome of A. nidulans by comparing its sequence to sequences of well-characterized genes in other species encoding the function of interest. A classification system, based on defined criteria, was developed for evaluating and selecting the ORFs among the candidates, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene expression data concerning a study on glucose repression, thereby providing a means of upgrading the information content of experimental data and getting further insight into this phenomenon in A. nidulans.ConclusionWe demonstrate how pathway modeling of A. nidulans can be used as an approach to improve the functional annotation of the genome of this organism. Furthermore we show how the metabolic model establishes functional links between genes, enabling the upgrade of the information content of transcriptome data.

Project description:BackgroundAspergillus niger is an important fungus used in industrial applications for enzyme and acid production. To enable rational metabolic engineering of the species, available information can be collected and integrated in a genome-scale model to devise strategies for improving its performance as a host organism.ResultsIn this paper, we update an existing model of A. niger metabolism to include the information collected from 876 publications, thereby expanding the coverage of the model by 940 reactions, 777 metabolites and 454 genes. In the presented consensus genome-scale model of A. niger iJB1325 , we integrated experimental data from publications and patents, as well as our own experiments, into a consistent network. This information has been included in a standardized way, allowing for automated testing and continuous improvements in the future. This repository of experimental data allowed the definition of 471 individual test cases, of which the model complies with 373 of them. We further re-analyzed existing transcriptomics and quantitative physiology data to gain new insights on metabolism. Additionally, the model contains 3482 checks on the model structure, thereby representing the best validated genome-scale model on A. niger developed until now. Strain-specific model versions for strains ATCC 1015 and CBS 513.88 have been created containing all data used for model building, thereby allowing users to adopt the models and check the updated version against the experimental data. The resulting model is compliant with the SBML standard and therefore enables users to easily simulate it using their preferred software solution.ConclusionExperimental data on most organisms are scattered across hundreds of publications and several repositories.To allow for a systems level understanding of metabolism, the data must be integrated in a consistent knowledge network. The A. niger iJB1325 model presented here integrates the available data into a highly curated genome-scale model to facilitate the simulation of flux distributions, as well as the interpretation of other genome-scale data by providing the metabolic context.

Project description:The filamentous fungi are an ecologically important group of organisms which also have important industrial applications but devastating effects as pathogens and agents of food spoilage. Protein kinases have been implicated in the regulation of virtually all biological processes but how they regulate filamentous fungal specific processes is not understood. The filamentous fungus Aspergillus nidulans has long been utilized as a powerful molecular genetic system and recent technical advances have made systematic approaches to study large gene sets possible. To enhance A. nidulans functional genomics we have created gene deletion constructs for 9851 genes representing 93.3% of the encoding genome. To illustrate the utility of these constructs, and advance the understanding of fungal kinases, we have systematically generated deletion strains for 128 A. nidulans kinases including expanded groups of 15 histidine kinases, 7 SRPK (serine-arginine protein kinases) kinases and an interesting group of 11 filamentous fungal specific kinases. We defined the terminal phenotype of 23 of the 25 essential kinases by heterokaryon rescue and identified phenotypes for 43 of the 103 non-essential kinases. Uncovered phenotypes ranged from almost no growth for a small number of essential kinases implicated in processes such as ribosomal biosynthesis, to conditional defects in response to cellular stresses. The data provide experimental evidence that previously uncharacterized kinases function in the septation initiation network, the cell wall integrity and the morphogenesis Orb6 kinase signaling pathways, as well as in pathways regulating vesicular trafficking, sexual development and secondary metabolism. Finally, we identify ChkC as a third effector kinase functioning in the cellular response to genotoxic stress. The identification of many previously unknown functions for kinases through the functional analysis of the A. nidulans kinome illustrates the utility of the A. nidulans gene deletion constructs.

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Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans.

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Metabolic network driven analysis of genome-wide transcription data from Aspergillus nidulans.

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