Fungal secondary metabolism has become an important research topic with great biomedical and biotechnological value. In the postgenomic era, understanding the diversity and the molecular control of secondary metabolites (SMs) are two challenging tasks addressed by the research community. Discovery of the LaeA methyltransferase 10 years ago opened up a new horizon on the control of SM research when it was found that expression of many SM gene clusters is controlled by LaeA. While the molecular function of LaeA remains an enigma, discovery of the velvet family proteins as interaction partners further extended the role of the LaeA beyond secondary metabolism. The heterotrimeric VelB–VeA–LaeA complex plays important roles in development, sporulation, secondary metabolism, and pathogenicity. Recently, three other methyltransferases have been found to associate with the velvet complex, the LaeA-like methyltransferase F and the methyltransferase heterodimers VipC–VapB. Interaction of VeA with at least four methyltransferase proteins indicates a molecular hub function for VeA that questions: Is there a VeA supercomplex or is VeA part of a highly dynamic cellular control network with many different partners?

Filamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here, we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed 5 general types of variation in SM gene clusters: nonfunctional gene polymorphisms; gene gain and loss polymorphisms; whole cluster gain and loss polymorphisms; allelic polymorphisms, in which different alleles corresponded to distinct, nonhomologous clusters; and location polymorphisms, in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms, the detection of which requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and nonhomologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, and genomic deletion and insertion events as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns.

The hallmark trait of fungal secondary-metabolite gene clusters is well established, consisting of contiguous enzymatic and often regulatory gene(s) devoted to the production of a metabolite of a specific chemical class. Unexpectedly, we have found a deviation from this motif in a subtelomeric region of Aspergillus fumigatus. This region, under the control of the master regulator of secondary metabolism, LaeA, contains, in its entirety, the genetic machinery for three natural products (fumitremorgin, fumagillin, and pseurotin), where genes for fumagillin and pseurotin are physically intertwined in a single supercluster. Deletions of 29 adjoining genes revealed that fumagillin and pseurotin are coregulated by the supercluster-embedded regulatory gene with biosynthetic genes belonging to one of the two metabolic pathways in a noncontiguous manner. Comparative genomics indicates the fumagillin/pseurotin supercluster is maintained in a rapidly evolving region of diverse fungal genomes. This blended design confounds predictions from established secondary-metabolite cluster search algorithms and provides an expanded view of natural product evolution.gene regulation | Zn(II) 2 Cys 6 transcription factor | FapR | biosynthesis | cluster evolution F ilamentous fungi are well known for their ability to produce a variety of natural products, so-called secondary metabolites that are not essential for growth under laboratory conditions (reviewed in refs. 1 and 2). However, the maintenance of the genetic information allowing fungi to produce secondary metabolites suggests that these small molecules provide essential benefits in environmental niches ranging from protection from fungivory (reviewed in ref.3) to chemical shields from UV radiation (4). Apart from providing evolutionary fitness to the producing organism in their natural habitat, many secondary metabolites are of major importance to humans because of their beneficial and deleterious effects as drugs and toxins, respectively.Fungal secondary metabolism has been characterized by physical linkage of the genes required for synthesis of specific metabolites and the distinct enzymatic machinery encoded by these genes (1, 2, 5). For instance, most fungal secondary metabolites belong to one of four chemical classes that are characterized based on the key or backbone enzymes that consist of polyketide synthases (PKSs), nonribosomal peptide synthetases (NRPSs), terpene cyclases (TCs), and prenyltransferases (PTs). Typically, cluster genes adjacent to these backbone genes code for accessory enzymes involved in either modification of the chemical scaffold, transcriptional control of cluster genes, transport of substrates and/or products, and resistance mechanisms. The most common regulatory genes of clusters encode fungal-specific C6 zinc binuclear cluster (Zn(II) 2 Cys 6 ) transcription factors (6), which, in general, exert positive transcriptional regulation of most of the genes within a single cluster (7). In addition to cluster-specific transcription factors, a higher order...

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer (ITS) amplicons, we created two ITS spike-in control mock communities composed of cloned DNA in plasmids: a biological mock community, consisting of ITS sequences from fungal taxa, and a synthetic mock community (SynMock), consisting of non-biological ITS-like sequences. Using these spike-in controls we show that: (1) a non-biological synthetic control (e.g., SynMock) is the best solution for parameterizing bioinformatics pipelines, (2) pre-clustering steps for variable length amplicons are critically important, (3) a major source of bias is attributed to the initial polymerase chain reaction (PCR) and thus HTAS read abundances are typically not representative of starting values. We developed AMPtk, a versatile software solution equipped to deal with variable length amplicons and quality filter HTAS data based on spike-in controls. While we describe herein a non-biological SynMock community for ITS sequences, the concept and AMPtk software can be widely applied to any HTAS dataset to improve data quality.