Heterologous production of fungal secondary metabolites in Aspergilli

Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites.org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms.

Fungi produce an impressive array of secondary metabolites (SMs) including mycotoxins, antibiotics and pharmaceuticals. The genes responsible for their biosynthesis, export, and transcriptional regulation are often found in contiguous gene clusters. To facilitate annotation of these clusters in sequenced fungal genomes, we developed the web-based software SMURF (www.jcvi.org/smurf/) to systematically predict clustered SM genes based on their genomic context and domain content. We applied SMURF to catalog putative clusters in 27 publicly available fungal genomes. Comparison with genetically characterized clusters from six fungal species showed that SMURF accurately recovered all clusters and detected additional potential clusters. Subsequent comparative analysis revealed the striking biosynthetic capacity and variability of the fungal SM pathways and the correlation between unicellularity and the absence of SMs. Further genetics studies are needed to experimentally confirm these clusters. 2010 Elsevier Inc. All rights reserved.

Aspergillus nidulans is an important experimental organism, and it is a model organism for the genus Aspergillus that includes serious pathogens as well as commercially important organisms. Gene targeting by homologous recombination during transformation is possible in A. nidulans, but the frequency of correct gene targeting is variable and often low. We have identified the A. nidulans homolog (nkuA) of the human KU70 gene that is essential for nonhomologous end joining of DNA in double-strand break repair. Deletion of nkuA (nkuA delta) greatly reduces the frequency of nonhomologous integration of transforming DNA fragments, leading to dramatically improved gene targeting. We have also developed heterologous markers that are selectable in A. nidulans but do not direct integration at any site in the A. nidulans genome. In combination, nkuA delta and the heterologous selectable markers make up a very efficient gene-targeting system. In experiments involving scores of genes, 90% or more of the transformants carried a single insertion of the transforming DNA at the correct site. The system works with linear and circular transforming molecules and it works for tagging genes with fluorescent moieties, replacing genes, and replacing promoters. This system is efficient enough to make genomewide gene-targeting projects feasible.