Molecular genetic analysis reveals that a nonribosomal peptide synthetase-like (NRPS-like) gene in Aspergillus nidulans is responsible for microperfuranone biosynthesis

Yeh, Hsu Hua; Chiang, Yi‐Ming; Entwistle, Ruth; Ahuja, Manmeet; Lee, Kuan Han; Bruno, Kenneth S.; Wu, Tung‐Kung; Oakley, Berl R; Wang, Clay C. C.

doi:10.1007/s00253-012-4098-9

Cited by 50 publications

(40 citation statements)

References 36 publications

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“…Although not always successful, this approach has led to the identification of aspyridone A [67], apicidins [45, 68], microperfuranone [69], pyranonigrin E [70], and hexadehydroastechrome [71] and has confirmed the enzymes responsible for fumitremorgin [38], apicidin [45], fusarin C [19], and cytochalasin [72, 73] production.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Nonribosomal Peptide Biosynthesis in Filamentous Fungi

Soukup

Keller

Wiemann

2016

Methods in Molecular Biology

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Filamentous fungi are historically known as rich sources for production of biologically active natural products, so-called secondary metabolites. One particularly pharmaceutically relevant chemical group of secondary metabolites is the nonribosomal peptides synthesized by nonribosomal peptide synthetases (NRPSs). As most of the fungal NRPS gene clusters leading to production of the desired molecules are not expressed under laboratory conditions, efforts to overcome this impediment are crucial to unlock the full chemical potential of each fungal species. One way to activate these silent clusters is by overexpressing and deleting global regulators of secondary metabolism. The conserved fungal-specific regulator of secondary metabolism, LaeA, was shown to be a valuable target for sleuthing of novel gene clusters and metabolites. Additionally, modulation of chromatin structures by either chemical or genetic manipulation has been shown to activate cryptic metabolites. Furthermore, NRPS-derived molecules seem to be affected by cross talk between the specific gene clusters and some of these metabolites have a tissue- or developmental-specific regulation. This chapter summarizes how this knowledge of different tiers of regulation can be combined to increase production of NRPS-derived metabolites in fungal species.

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Section: Introductionmentioning

confidence: 99%

Enhancing Nonribosomal Peptide Biosynthesis in Filamentous Fungi

Soukup

Keller

Wiemann

2016

Methods in Molecular Biology

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“…This was demonstrated by systematically targeting nonribosomal peptide synthetase (NRPS)-like genes for promoter replacement, resulting in the discovery that one of the NRPS-like genes, micA , is the sole gene responsible for the biosynthesis of the metabolite microperfuranone [59]. …”

Section: Introductionmentioning

confidence: 99%

Recent advances in genome mining of secondary metabolite biosynthetic gene clusters and the development of heterologous expression systems in Aspergillus nidulans

Yaegashi

Oakley

Wang

2014

Journal of Industrial Microbiology and Biotechnology

116

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Fungi are prolific producers of secondary metabolites (SMs) that show a variety of biological activities. Recent advances in genome sequencing have shown that fungal genomes harbor far more SM gene clusters than are expressed under conventional laboratory conditions. Activation of these “silent” gene clusters is a major challenge, and many approaches have been taken to attempt to activate them and, thus, unlock the vast treasure chest of fungal SMs. This review will cover recent advances in genome mining of SMs in Aspergillus nidulans. We will also discuss current updates in gene annotation of A. nidulans and recent developments in A. nidulans as a molecular genetic system, both of which are essential for rapid and efficient experimental verification of SM gene clusters on a genome-wide scale. Finally, we will describe advances in the use of A. nidulans as a heterologous expression system to aid in the analysis of SM gene clusters from other fungal species that do not have an established molecular genetic system.

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“…The difference is due to the absence of two of the genes on the legacy microarray data, which removes them from the prediction. † Yeh et al (29), who examined this cluster, found increased transcription of the two extra genes we predict, but they found them to be nonessential for microperfuranone production. (25).…”

Section: Clustering Of Synthase Expression Profiles Identifies Supercmentioning

confidence: 99%

Accurate prediction of secondary metabolite gene clusters in filamentous fungi

Andersen

Nielsen

Klitgaard

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

213

185

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Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.aspergilli | natural products | secondary metabolism | polyketide synthases N o other group of biochemical compounds holds as much promise for drug development as the secondary (nongrowth associated) metabolites (SMs). A review from 2012 (1) found that for small-molecule pharmaceuticals, 68% of the anticancer agents and 52% of the antiinfective agents are natural products, or derived from natural products. The fact that SMs are often synthesized as polymer backbones that are subsequently diversified greatly via the actions of tailoring enzymes sets the stage for combinatorial biochemistry (2), because their biosynthesis is modular.Major groups of SMs include polyketides (PKs) consisting of -CH 2 -(C = O)-units, ribosomal and nonribosomomal peptides (NRPs), and terpenoids made from C 5 isoprene units. These polymer backbones are, with the exception of ribosomal peptides, made by synthases or synthetases and are modified by a plethora of tailoring enzymes, including (de)hydratases, oxygenases, hydrolases, methylases, and others.In fungi, these biosynthetic genes of secondary metabolism are organized in discrete clusters around the synthase genes. Although quite accurate algorithms are available for identification of possible SM biosynthetic genes, particularly PK synthases (PKSs), NRP synthetases (NRPSs), and dimethylallyl tryptophan synthases (DMATSs) (3, 4), the assignment and prediction of the members of the individual clusters solely from the genome sequence have not been accurate. Relevant protein domains can be predicted for some of the genes (e....

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Molecular genetic analysis reveals that a nonribosomal peptide synthetase-like (NRPS-like) gene in Aspergillus nidulans is responsible for microperfuranone biosynthesis

Cited by 50 publications

References 36 publications

Enhancing Nonribosomal Peptide Biosynthesis in Filamentous Fungi

Enhancing Nonribosomal Peptide Biosynthesis in Filamentous Fungi

Recent advances in genome mining of secondary metabolite biosynthetic gene clusters and the development of heterologous expression systems in Aspergillus nidulans

Accurate prediction of secondary metabolite gene clusters in filamentous fungi

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