Expanding our Understanding of Sequence-Function Relationships of Type II Polyketide Biosynthetic Gene Clusters: Bioinformatics-Guided Identification of Frankiamicin A from Frankia sp. EAN1pec

Abstract

A large and rapidly increasing number of unstudied “orphan” natural product biosynthetic gene clusters are being uncovered in sequenced microbial genomes. An important goal of modern natural products research is to be able to accurately predict natural product structures and biosynthetic pathways from these gene cluster sequences. This requires both development of bioinformatic methods for global analysis of these gene clusters and experimental characterization of select products produced by gene clusters with divergent sequence characteristics. Here, we conduct global bioinformatic analysis of all available type II polyketide gene cluster sequences and identify a conserved set of gene clusters with unique ketosynthase α/β sequence characteristics in the genomes of Frankia species, a group of Actinobacteria with underexploited natural product biosynthetic potential. Through LC-MS profiling of extracts from several Frankia species grown under various conditions, we identified Frankia sp. EAN1pec as producing a compound with spectral characteristics consistent with the type II polyketide produced by this gene cluster. We isolated the compound, a pentangular polyketide which we named frankiamicin A, and elucidated its structure by NMR and labeled precursor feeding. We also propose biosynthetic and regulatory pathways for frankiamicin A based on comparative genomic analysis and literature precedent, and conduct bioactivity assays of the compound. Our findings provide new information linking this set of Frankia gene clusters with the compound they produce, and our approach has implications for accurate functional prediction of the many other type II polyketide clusters present in bacterial genomes.

Evolution of chemical diversity by coordinated gene swaps in type II polyketide gene clusters

“…4). We observe that the C19 KR was introduced into the ancestor of frankiamycin (32) and all other characterized clusters (ancestor 4).…”

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM)

“…Ogasawara et al . ( 86 ) developed Dynamite, a Python software package which uses a BLAST database to identify type I and type II PKS and NRPS gene clusters within the NCBI database, and conducted a global phylogenetic analysis of type II polyketide ketosynthases. However, at present, no software exists to predict the chemical structures of type II polyketides from genetic information.…”

“…Both the ketosynthase α (KSα) and chain length factor (CLF or KSβ) occupy distinct clades within ketosynthase phylogeny ( 87 ), and several studies ( 86 , 88 , 89 ) have reported that the length of the unreduced ketide chain produced by the minimal PKS can be reliably inferred from the primary sequence of the chain length factor. We therefore constructed new hidden Markov models for type II PKS KSα and CLF domains, and compiled a BLAST database of CLF domains annotated with the number of ketide chain extension cycles associated with the PKS.…”

“…We therefore constructed new hidden Markov models for type II PKS KSα and CLF domains, and compiled a BLAST database of CLF domains annotated with the number of ketide chain extension cycles associated with the PKS. Annotated sequences were collected based on a global phylogenetic analysis of type II polyketide ketosynthases performed with the software platform Dynamite ( 86 ), and manually supplemented with domains from known PKSs observed to be absent from this data set. Within PRISM, the extension length of a type II PKS is inferred based on the single most homologous CLF, and used to generate a linear poly-β-ketide chain with a corresponding number of iterative decarboxylative condensations of malonyl-CoA with the identified starter unit.…”

High-Quality Draft Genome Sequence of Actinobacterium Kibdelosporangium sp. MJ126-NF4, Producer of Type II Polyketide Azicemicins, Using Illumina and PacBio Technologies

“…Gene prediction and annotation were carried out using RAST ( 14 ), incorporating the Glimmer ( 15 ) algorithm, and identified 10,999 putative protein-coding genes, 7 rRNAs, and 63 tRNAs. Twenty-two polyketide and nonribosomal peptide natural-product biosynthetic gene clusters, all of which were intact, including the error-free azicemicin cluster, were identified using Dynamite ( 16 ) and confirmed using antiSMASH ( 17 ).…”