Phylogenetic and Structural Analysis of Polyketide Synthases in Aspergilli

Polyketide synthases (PKSs) of Aspergillus species are multidomain and multifunctional megaenzymes that play an important role in the synthesis of diverse polyketide compounds. Putative PKS protein sequences from Aspergillus species representing medically, agriculturally, and industrially important Aspergillus species were chosen and screened for in silico studies. Six candidate Aspergillus species, Aspergillus fumigatus Af293, Aspergillus flavus NRRL3357, Aspergillus niger CBS 513.88, Aspergillus terreus NIH2624, Aspergillus oryzae RIB40, and Aspergillus clavatus NRRL1, were selected to study the PKS phylogeny. Full-length PKS proteins and only ketosynthase (KS) domain sequence were retrieved for independent phylogenetic analysis from the aforementioned species, and phylogenetic analysis was performed with characterized fungal PKS. This resulted into grouping of Aspergilli PKSs into nonreducing (NR), partially reducing (PR), and highly reducing (HR) PKS enzymes. Eight distinct clades with unique domain arrangements were classified based on homology with functionally characterized PKS enzymes. Conserved motif signatures corresponding to each type of PKS were observed. Three proteins from Protein Data Bank corresponding to NR, PR, and HR type of PKS (XP_002384329.1, XP_753141.2, and XP_001402408.2, respectively) were selected for mapping of conserved motifs on three-dimensional structures of KS domain. Structural variations were found at the active sites on modeled NR, PR, and HR enzymes of Aspergillus. It was observed that the number of iteration cycles was dependent on the size of the cavity in the active site of the PKS enzyme correlating with a type with reducing or NR products, such as pigment, 6MSA, and lovastatin. The current study reports the grouping and classification of PKS proteins of Aspergilli for possible exploration of novel polyketides based on sequence homology; this information can be useful for selection of PKS for polyketide exploration and specific detection of Aspergilli.

A resource for the in silico identification of fungal polyketide synthases from predicted fungal proteomes

The goal of this study was to develop a tool specifically designed to identify iterative polyketide synthases (iPKSs) from predicted fungal proteomes. A fungi-based PKS prediction model, specifically for fungal iPKSs, was developed using profile hidden Markov models (pHMMs) based on two essential iPKS domains, the β-ketoacyl synthase (KS) domain and acyltransferase (AT) domain, derived from fungal iPKSs. This fungi-based PKS prediction model was initially tested on the well-annotated proteome of Fusarium graminearum, identifying 15 iPKSs that matched previous predictions and gene disruption studies. These fungi-based pHMMs were subsequently applied to the predicted fungal proteomes of Alternaria brassicicola, Fusarium oxysporum f.sp. lycopersici, Verticillium albo-atrum and Verticillium dahliae. The iPKSs predicted were compared against those predicted by the currently available mixed-kingdom PKS models that include both bacterial and fungal sequences. These mixed-kingdom models have been proven previously by others to be better in predicting true iPKSs from non-iPKSs compared with other available models (e.g. Pfam and TIGRFAM). The fungi-based model was found to perform significantly better on fungal proteomes than the mixed-kingdom PKS model in accuracy, sensitivity, specificity and precision. In addition, the model was capable of predicting the reducing nature of fungal iPKSs by comparison of the bit scores obtained from two separate reducing and nonreducing pHMMs for each domain, which was confirmed by phylogenetic analysis of the KS domain. Biological confirmation of the predictions was obtained by polymerase chain reaction (PCR) amplification of the KS and AT domains of predicted iPKSs from V. dahliae using domain-specific primers and genomic DNA, followed by sequencing of the PCR products. It is expected that the fungi-based PKS model will prove to be a useful tool for the identification and annotation of fungal PKSs from predicted proteomes.

Predicted roles of the uncharacterized clustered genes in aflatoxin biosynthesis

Biosynthesis of the toxic and carcinogenic aflatoxins (AFs) requires the activity of more than 27 enzymes. The roles in biosynthesis of newly described enzymes are discussed in this review. We suggest that HypC catalyzes the oxidation of norsolorinic acid anthrone; AvfA (AflI), the ring-closure step in formation of hydroxyversicolorone; HypB, the second oxidation step in conversion of O-methylsterigmatocystin to AF; and HypE and NorA (AflE), the final two steps in AFB(1) formation. HypD, an integral membrane protein, affects fungal development and lowers AF production while AflJ (AflS), has a partial methyltransferase domain that may be important in its function as a transcriptional co-activator.