Literature DB >> 23065606

Bioinformatics approaches and software for detection of secondary metabolic gene clusters.

Natalie D Fedorova1, Venkatesh Moktali, Marnix H Medema.   

Abstract

The accelerating pace of microbial genomics is sparking a renaissance in the field of natural products research. Researchers can now get a preview of the organism's secondary metabolome by analyzing its genomic sequence. Combined with other -omics data, this approach may provide a cost-effective alternative to industrial high-throughput screening in drug discovery. In the last few years, several computational tools have been developed to facilitate this process by identifying genes involved in secondary metabolite biosynthesis in bacterial and fungal genomes. Here, we review seven software programs that are available for this purpose, with an emphasis on antibiotics & Secondary Metabolite Analysis SHell (antiSMASH) and Secondary Metabolite Unknown Regions Finder (SMURF), the only tools that can comprehensively detect complete secondary metabolite biosynthesis gene clusters. We also discuss five related software packages-CLUster SEquence ANalyzer (CLUSEAN), ClustScan, Structure Based Sequence Analysis of Polyketide Synthases (SBSPKS), NRPSPredictor, and Natural Product searcher (NP.searcher)-that identify secondary metabolite backbone biosynthesis genes. This chapter offers detailed protocols, suggestions, and caveats to assist researchers in using these tools most effectively.

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Year:  2012        PMID: 23065606     DOI: 10.1007/978-1-62703-122-6_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  23 in total

Review 1.  Strategies for mining fungal natural products.

Authors:  Philipp Wiemann; Nancy P Keller
Journal:  J Ind Microbiol Biotechnol       Date:  2013-10-22       Impact factor: 3.346

Review 2.  DNA assembly techniques for next-generation combinatorial biosynthesis of natural products.

Authors:  Ryan E Cobb; Jonathan C Ning; Huimin Zhao
Journal:  J Ind Microbiol Biotechnol       Date:  2013-10-15       Impact factor: 3.346

Review 3.  Merging chemical ecology with bacterial genome mining for secondary metabolite discovery.

Authors:  Maria I Vizcaino; Xun Guo; Jason M Crawford
Journal:  J Ind Microbiol Biotechnol       Date:  2013-10-15       Impact factor: 3.346

Review 4.  Bioinformatics tools for the identification of gene clusters that biosynthesize specialized metabolites.

Authors:  Arvind K Chavali; Seung Y Rhee
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

5.  On being an honorary member of Arny's army: some musings about fungal fermentations, secondary metabolism, and scientific communities.

Authors:  Joan Wennstrom Bennett
Journal:  J Ind Microbiol Biotechnol       Date:  2017-05       Impact factor: 3.346

Review 6.  New tools for reconstruction and heterologous expression of natural product biosynthetic gene clusters.

Authors:  Yunzi Luo; Behnam Enghiad; Huimin Zhao
Journal:  Nat Prod Rep       Date:  2016-02       Impact factor: 13.423

7.  Genome mining reveals unlocked bioactive potential of marine Gram-negative bacteria.

Authors:  Henrique Machado; Eva C Sonnenschein; Jette Melchiorsen; Lone Gram
Journal:  BMC Genomics       Date:  2015-03-07       Impact factor: 3.969

8.  Evolution of Chemical Diversity in a Group of Non-Reduced Polyketide Gene Clusters: Using Phylogenetics to Inform the Search for Novel Fungal Natural Products.

Authors:  Kurt Throckmorton; Philipp Wiemann; Nancy P Keller
Journal:  Toxins (Basel)       Date:  2015-09-10       Impact factor: 4.546

9.  antiSMASH 2.0--a versatile platform for genome mining of secondary metabolite producers.

Authors:  Kai Blin; Marnix H Medema; Daniyal Kazempour; Michael A Fischbach; Rainer Breitling; Eriko Takano; Tilmann Weber
Journal:  Nucleic Acids Res       Date:  2013-06-03       Impact factor: 16.971

10.  Genomics-driven discovery of the pneumocandin biosynthetic gene cluster in the fungus Glarea lozoyensis.

Authors:  Li Chen; Qun Yue; Xinyu Zhang; Meichun Xiang; Chengshu Wang; Shaojie Li; Yongsheng Che; Francisco Javier Ortiz-López; Gerald F Bills; Xingzhong Liu; Zhiqiang An
Journal:  BMC Genomics       Date:  2013-05-20       Impact factor: 3.969

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