Discovery of Pyranoviolin A and Its Biosynthetic Gene Cluster in Aspergillus violaceofuscus

Biosynthetic Characterization, Heterologous Production, and Genomics-Guided Discovery of GABA-Containing Fungal Heptapeptides

The biosynthetic gene cluster of γ-aminobutyric acid (GABA)-containing fungal cyclic heptapeptides unguisins A (1) and B (2) was identified in the fungus Aspergillus violaceofuscus CBS 115571. In vitro enzymatic reactions and gene deletion experiments revealed that the unguisin pathway involves the alanine racemase UngC to provide d-alanine, which is then accepted by the first adenylation domain of the nonribosomal peptide synthetase (NRPS) UngA. Intriguingly, the hydrolase UngD was found to transform unguisins into previously undescribed linear peptides. Subsequently, heterologous production of these peptides in Aspergillus oryzae was achieved, in which we established a methodology to readily introduce a large NRPS gene into the fungal host. Finally, genome mining revealed new unguisin congeners, each containing a (2R,3R)-β-methylphenylalanine residue.

Mining and characterization of the PKS-NRPS hybrid for epicoccamide A: a mannosylated tetramate derivative from Epicoccum sp. CPCC 400996

BACKGROUND

Genomic analysis indicated that the genomes of ascomycetes might carry dozens of biosynthetic gene clusters (BGCs), yet many clusters have remained enigmatic. The ascomycete genus Epicoccum, belonging to the family Didymellaceae, is ubiquitous that colonizes different types of substrates and is associated with phyllosphere or decaying vegetation. Species of this genus are prolific producers of bioactive substances. The epicoccamides, as biosynthetically distinct mannosylated tetramate, were first isolated in 2003 from Epicoccum sp. In this study, using a combination of genome mining, chemical identification, genetic deletion, and bioinformatic analysis, we identified the required BGC epi responsible for epicoccamide A biosynthesis in Epicoccum sp. CPCC 400996.

RESULTS

The unconventional biosynthetic gene cluster epi was obtained from an endophyte Epicoccum sp. CPCC 400996 through AntiSMASH-based genome mining. The cluster epi includes six putative open reading frames (epiA-epiF) altogether, in which the epiA encodes a tetramate-forming polyketide synthase and nonribosomal peptide synthetases (PKS-NRPS hybrid). Sequence alignments and bioinformatic analysis to other metabolic pathways of fungal tetramates, we proposed that the gene cluster epi could be involved in generating epicoccamides. Genetic knockout of epiA completely abolished the biosynthesis of epicoccamide A (1), thereby establishing the correlation between the BGC epi and biosynthesis of epicoccamide A. Bioinformatic adenylation domain signature analysis of EpiA and other fungal PKS-NRPSs (NRPs) indicated that the EpiA is L-alanine incorporating tetramates megasynthase. Furthermore, based on the molecular structures of epicoccamide A and deduced gene functions of the cluster epi, a hypothetic metabolic pathway for biosynthesizing compound 1 was proposed. The corresponding tetramates releasing during epicoccamide A biosynthesis was catalyzed through Dieckmann-type cyclization, in which the reductive (R) domain residing in terminal module of EpiA accomplished the conversion. These results unveiled the underlying mechanism of epicoccamides biosynthesis and these findings might provide opportunities for derivatization of epicoccamides or generation of new chemical entities.

CONCLUSION

Genome mining and genetic inactivation experiments unveiled a previously uncharacterized PKS - NRPS hybrid-based BGC epi responsible for the generation of epicoccamide A (1) in endophyte Epicoccum sp. CPCC 400996. In addition, based on the gene cluster data, a hypothetical biosynthetic pathway of epicoccamide A was proposed.

Biosynthesis of fungal polyketides by collaborating and trans-acting enzymes

Covering: 1999 up to 2021Fungal polyketides encompass a range of structurally diverse molecules with a wide variety of biological activities. The giant multifunctional enzymes that synthesize polyketide backbones remain enigmatic, as do many of the tailoring enzymes involved in functional modifications. Recent advances in elucidating biosynthetic gene clusters (BGCs) have revealed numerous examples of fungal polyketide synthases that require the action of collaborating enzymes to synthesize the carbon backbone. This review will discuss collaborating and trans-acting enzymes involved in loading, extending, and releasing polyketide intermediates from fungal polyketide synthases, and additional modifications introduced by trans-acting enzymes demonstrating the complexity encountered when investigating natural product biosynthesis in fungi.

Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi

Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.