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TransfactomeDB: a resource for exploring the nucleotide sequence specificity and condition-specific regulatory activity of trans-acting factors.

ABSTRACT: Accurate and comprehensive information about the nucleotide sequence specificity of trans-acting factors (TFs) is essential for computational and experimental analyses of gene regulatory networks. We present the Yeast Transfactome Database, a repository of sequence specificity models and condition-specific regulatory activities for a large number of DNA- and RNA-binding proteins in Saccharomyces cerevisiae. The sequence specificities in TransfactomeDB, represented as position-specific affinity matrices (PSAMs), are directly estimated from genomewide measurements of TF-binding using our previously published MatrixREDUCE algorithm, which is based on a biophysical model. For each mRNA expression profile in the NCBI Gene Expression Omnibus, we used sequence-based regression analysis to estimate the post-translational regulatory activity of each TF for which a PSAM is available. The trans-factor activity profiles across multiple experiments available in TransfactomeDB allow the user to explore potential regulatory roles of hundreds of TFs in any of thousands of microarray experiments. Our resource is freely available at http://bussemakerlab.org/TransfactomeDB/

SUBMITTER: Foat BC

PROVIDER: S-EPMC2238954 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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TransfactomeDB: a resource for exploring the nucleotide sequence specificity and condition-specific regulatory activity of trans-acting factors.

Foat Barrett C BC Tepper Ronald G RG Bussemaker Harmen J HJ

Nucleic acids research 20071018 Database issue

Accurate and comprehensive information about the nucleotide sequence specificity of trans-acting factors (TFs) is essential for computational and experimental analyses of gene regulatory networks. We present the Yeast Transfactome Database, a repository of sequence specificity models and condition-specific regulatory activities for a large number of DNA- and RNA-binding proteins in Saccharomyces cerevisiae. The sequence specificities in TransfactomeDB, represented as position-specific affinity m ...[more]

PMID: 17947326

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Project description:The field of secondary metabolism has greatly benefitted from computational advances in recent years. This has been particularly true for fungal natural product studies. Strides in genome mining have led to the identification of an extraordinary number of secondary metabolite biosynthetic gene clusters (BGCs) across the fungal Kingdom and metabologenomic platforms can group BGCs into gene cluster families and link them to initial chemical structures. Missing are computational applications focused on identifying BGC regulatory networks. Here, we applied the new online gene regulatory network resource, GRAsp (Gene Regulation of Aspergillus fumigatus), to identify unknown and unpredictable BGC trans-acting transcriptional/metabolite production modules. GRAsp correctly predicted a two-component regulatory module composed of the transcription factors (TFs), RogA (regulation of gliotoxin) and HsfA, which negatively regulate the gliotoxin BGC and are also involved in gliotoxin self-protection. RogA functions through the repression of gliZ, the pathway-specific gliotoxin TF, and HsfA functions by activating rogA expression. Furthermore, GRAsp identified TFs that regulate the production of two BGCs lacking pathway-specific TFs, the helvolic acid and fumitremorgin BGCs, respectively. Finally, the known TF, NsdD, was predicted and found to regulate the hexadehydroastechrome BGC. These advances highlight the power of inference algorithms to uncover unpredictable networks in specialized metabolite synthesis.IMPORTANCEToxic secondary metabolites are virulence factors of the opportunistic fungal pathogen Aspergillus fumigatus, yet the transcriptional networks regulating secondary metabolite production remain elusive. Uncovering novel regulators without any prior information is challenging. Computational programs have gained prominence in the field of secondary metabolite research due to their accuracy and ability to handle vast amounts of data, including DNA, RNA, and protein data. In this study, a newly developed online computer platform, Gene Regulation of A. fumigatus, was used to identify five regulators involved in the production of several A. fumigatus toxins, including gliotoxin, helvolic acid, fumitremorgin, and hexadehydroastechrome. This work illustrates the potential for discovering new trans-acting regulators and mechanisms of secondary metabolite regulation through the examination of computational gene regulatory networks.

Dataset Information

TransfactomeDB: a resource for exploring the nucleotide sequence specificity and condition-specific regulatory activity of trans-acting factors.

Publications

TransfactomeDB: a resource for exploring the nucleotide sequence specificity and condition-specific regulatory activity of trans-acting factors.

Similar Datasets

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