Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.
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ABSTRACT:
SUBMITTER: Albright JC
PROVIDER: S-EPMC4475433 | biostudies-literature | 2015 Jun
REPOSITORIES: biostudies-literature
Publications
Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.
Albright Jessica C JC Henke Matthew T MT Soukup Alexandra A AA McClure Ryan A RA Thomson Regan J RJ Keller Nancy P NP Kelleher Neil L NL
ACS chemical biology 20150403 6
The microbial world offers a rich source of bioactive compounds for those able to sift through it. Technologies capable of quantitatively detecting natural products while simultaneously identifying known compounds would expedite the search for new pharmaceutical leads. Prior efforts have targeted histone deacetylases in fungi to globally activate the production of new secondary metabolites, yet no study has directly assessed its effects with minimal bias at the metabolomic level. Using untargete ...[more]
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Project description:The b-Zip transcription factor AtfA plays a key role in regulating stress responses in the filamentous fungus Aspergillus nidulans. To identify the core regulons of AtfA, we examined genome-wide expression changes caused by various stresses in the presence/absence of AtfA using A. nidulans microarrays. We also intended to address the intriguing question regarding the existence of core environmental stress response in this important model eukaryote.Examination of the genome wide expression changes caused by five different oxidative stress conditions in wild type and the atfA null mutant has identified a significant number of stereotypically regulated genes (Core Oxidative Stress Response genes). The deletion of atfA increased the oxidative stress sensitivity of A. nidulans and affected mRNA accumulation of several genes under both unstressed and stressed conditions. The numbers of genes under the AtfA control appear to be specific to a stress-type. We also found that both oxidative and salt stresses induced expression of some secondary metabolite gene clusters and the deletion of atfA enhanced the stress responsiveness of additional clusters. Moreover, certain clusters were down-regulated by the stresses tested.Our data suggest that the observed co-regulations were most likely consequences of the overlapping physiological effects of the stressors and not of the existence of a general environmental stress response. The function of AtfA in governing various stress responses is much smaller than anticipated and/or other regulators may play a redundant or overlapping role with AtfA. Both stress inducible and stress repressive regulations of secondary metabolism seem to be frequent features in A. nidulans.
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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.
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Project description:SUMOylation, covalent attachment of the small ubiquitin-like modifier protein SUMO to proteins, regulates protein interactions and activity and plays a crucial role in the regulation of many key cellular processes. Understanding the roles of SUMO in these processes ultimately requires identification of the proteins that are SUMOylated in the organism under study. The filamentous fungus Aspergillus nidulans serves as an excellent model for many aspects of fungal biology, and it would be of great value to determine the proteins that are SUMOylated in this organism (i.e. its SUMOylome). We have developed a new and effective approach for identifying SUMOylated proteins in this organism in which we lock proteins in their SUMOylated state, affinity purify SUMOylated proteins using the high affinity S-tag, and identify them using sensitive Orbitrap mass spectroscopy. This approach allows us to distinguish proteins that are SUMOylated from proteins that are binding partners of SUMOylated proteins or are bound non-covalently to SUMO. This approach has allowed us to identify 149 proteins that are SUMOylated in A. nidulans. Of these, 67 are predicted to be involved in transcription and particularly in the regulation of transcription, 21 are predicted to be involved in RNA processing and 16 are predicted to function in DNA replication or repair.
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