Dataset Information

ClustScan: an integrated program package for the semi-automatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures.

ABSTRACT: The program package 'ClustScan' (Cluster Scanner) is designed for rapid, semi-automatic, annotation of DNA sequences encoding modular biosynthetic enzymes including polyketide synthases (PKS), non-ribosomal peptide synthetases (NRPS) and hybrid (PKS/NRPS) enzymes. The program displays the predicted chemical structures of products as well as allowing export of the structures in a standard format for analyses with other programs. Recent advances in understanding of enzyme function are incorporated to make knowledge-based predictions about the stereochemistry of products. The program structure allows easy incorporation of additional knowledge about domain specificities and function. The results of analyses are presented to the user in a graphical interface, which also allows easy editing of the predictions to incorporate user experience. The versatility of this program package has been demonstrated by annotating biochemical pathways in microbial, invertebrate animal and metagenomic datasets. The speed and convenience of the package allows the annotation of all PKS and NRPS clusters in a complete Actinobacteria genome in 2-3 man hours. The open architecture of ClustScan allows easy integration with other programs, facilitating further analyses of results, which is useful for a broad range of researchers in the chemical and biological sciences.

SUBMITTER: Starcevic A

PROVIDER: S-EPMC2588505 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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ClustScan: an integrated program package for the semi-automatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures.

Starcevic Antonio A Zucko Jurica J Simunkovic Jurica J Long Paul F PF Cullum John J Hranueli Daslav D

Nucleic acids research 20081031 21

The program package 'ClustScan' (Cluster Scanner) is designed for rapid, semi-automatic, annotation of DNA sequences encoding modular biosynthetic enzymes including polyketide synthases (PKS), non-ribosomal peptide synthetases (NRPS) and hybrid (PKS/NRPS) enzymes. The program displays the predicted chemical structures of products as well as allowing export of the structures in a standard format for analyses with other programs. Recent advances in understanding of enzyme function are incorporated ...[more]

PMID: 18978015

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Project description:BackgroundA wide range of bioactive compounds is produced by enzymes and enzymatic complexes encoded in biosynthetic gene clusters (BGCs). These BGCs can be identified and functionally annotated based on their DNA sequence. Candidates for further research and development may be prioritized based on properties such as their functional annotation, (dis)similarity to known BGCs, and bioactivity assays. Production of the target compound in the native strain is often not achievable, rendering heterologous expression in an optimized host strain as a promising alternative. Genome-scale metabolic models are frequently used to guide strain development, but large-scale incorporation and testing of heterologous production of complex natural products in this framework is hampered by the amount of manual work required to translate annotated BGCs to metabolic pathways. To this end, we have developed a pipeline for an automated reconstruction of BGC associated metabolic pathways responsible for the synthesis of non-ribosomal peptides and polyketides, two of the dominant classes of bioactive compounds.ResultsThe developed pipeline correctly predicts 72.8% of the metabolic reactions in a detailed evaluation of 8 different BGCs comprising 228 functional domains. By introducing the reconstructed pathways into a genome-scale metabolic model we demonstrate that this level of accuracy is sufficient to make reliable in silico predictions with respect to production rate and gene knockout targets. Furthermore, we apply the pipeline to a large BGC database and reconstruct 943 metabolic pathways. We identify 17 enzymatic reactions using high-throughput assessment of potential knockout targets for increasing the production of any of the associated compounds. However, the targets only provide a relative increase of up to 6% compared to wild-type production rates.ConclusionWith this pipeline we pave the way for an extended use of genome-scale metabolic models in strain design of heterologous expression hosts. In this context, we identified generic knockout targets for the increased production of heterologous compounds. However, as the predicted increase is minor for any of the single-reaction knockout targets, these results indicate that more sophisticated strain-engineering strategies are necessary for the development of efficient BGC expression hosts.

Dataset Information

ClustScan: an integrated program package for the semi-automatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures.

Publications

ClustScan: an integrated program package for the semi-automatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures.

Similar Datasets

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