Dataset Information

Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.

ABSTRACT: 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 untargeted metabolomics, we monitored changes in >1000 small molecules secreted from the model fungus, Aspergillus nidulans, following genetic or chemical reductions in histone deacetylase activity (HDACi). Through quantitative, differential analyses, we found that nearly equal numbers of compounds were up- and down-regulated by >100 fold. We detected products from both known and unknown biosynthetic pathways and discovered that A. nidulans is capable of producing fellutamides, proteasome inhibitors whose expression was induced by ?100 fold or greater upon HDACi. This work adds momentum to an "omics"-driven resurgence in natural products research, where direct detection replaces bioactivity as the primary screen for new pharmacophores.

SUBMITTER: Albright JC

PROVIDER: S-EPMC4475433 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

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]

PMID: 25815712

Similar Datasets

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.

Dataset Information

Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.

Publications

Large-scale metabolomics reveals a complex response of Aspergillus nidulans to epigenetic perturbation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets