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Transcriptome analysis of A. nidulans growing in different carbon sources

ABSTRACT: Aspergillus nidulans is a model organism for aspergilli, 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 both in connection with their biotechnological application as well as their interaction with other cells (humans or plants), it is valuable to understand how their metabolism is regulated. We therefore performed genome-wide transcription analysis of A. nidulans grown on three different carbon sources (glucose, glycerol, and ethanol) with the objective to identify global regulatory structures. We furthermore reconstructed the complete metabolic network of this organism, and this resulted in linking of 666 genes with metabolic functions, as well as assigning metabolic roles to 472 genes that had not been annotated earlier. Through combinations of the reconstructed metabolic network and the transcription data, we identified subnetwork structures that pointed to coordinated regulation of genes involved in many different parts of the metabolism. Keywords: carbon sources, metabolism, comparative genomics

ORGANISM(S): Aspergillus nidulans

PROVIDER: GSE4578 | GEO | 2006/05/30

SECONDARY ACCESSION(S): PRJNA94419

REPOSITORIES: GEO

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Project description:David2008 - Genome-scale metabolic network of Aspergillus nidulans (iHD666) This model is described in the article: Analysis of Aspergillus nidulans metabolism at the genome-scale. David H, Ozçelik IS, Hofmann G, Nielsen J. BMC Genomics 2008; 9: 163 Abstract: BACKGROUND: Aspergillus 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. RESULTS: In 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. CONCLUSION: We 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. This model is hosted on BioModels Database and identified by: MODEL1507180016. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Transcriptome analysis of A. nidulans growing in different carbon sources

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