Automated structure prediction of trans-acyltransferase polyketide synthase products

Abstract

Bacterial trans-acyltransferase polyketide synthases (trans-AT PKSs) are among the most complex known enzymes from secondary metabolism and are responsible for the biosynthesis of highly diverse bioactive polyketides. However, most of these metabolites remain uncharacterized, since trans-AT PKSs frequently occur in poorly studied microbes and feature a remarkable array of non-canonical biosynthetic components with poorly understood functions. As a consequence, genome-guided natural product identification has been challenging. To enable de novo structural predictions for trans-AT PKS-derived polyketides, we developed the trans-AT PKS polyketide predictor (TransATor). TransATor is a versatile bio- and chemoinformatics web application that suggests informative chemical structures for even highly aberrant trans-AT PKS biosynthetic gene clusters, thus permitting hypothesis-based, targeted biotechnological discovery and biosynthetic studies. We demonstrate the applicative scope in several examples, including the characterization of new variants of bioactive natural products as well as structurally new polyketides from unusual bacterial sources.

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Fig. 1: Phylogenetic separation of trans-AT PKS KS domains into ketide clades.
Fig. 2: TransATor workflow.
Fig. 3: Example of a TransATor result.
Fig. 4: Model for leptolyngbyalide biosynthesis.
Fig. 5: Model for cuniculene biosynthesis.

Data availability

GenBank: the Aquimarina sp. Aq349 and Aq78 genome sequence harboring the cuniculene BGC has been submitted to the European Nucleotide Archive (accession codes OMKB01000001–OMKB01000022 and OMKF01000001–OMKF01000170). The leptolyngbyalide BGC (BK010645) from Leptolyngbyia sp. PCC 7375, and the tartrolon BGC (BK010667) from G. sunshinyii were deposited in GenBank. MIBiG: the lepolyngbyalide (BGC0001835), tartrolon (BGC0001836) and cuniculene (BGC0001855) BGCs were deposited in the MIBiG database. The TransATor web server is freely accessible at http://transator.ethz.ch. Code for TransATor pipeline/web application is available at https://github.com/pcm32/transator-container.

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Acknowledgements

J.P. acknowledges funding by the ERC (ERC Advanced Project SynPlex), the SNF (NRP 72 ‘Antimicrobial resistance’, no. 407240_167051) and the DFG Research Unit 854. R.C. acknowledges funding by the Portuguese Foundation for Science and Technology (FCT) through research grants (nos. PTDC/BIA-MIC/3865/2012 and PTDC/MAR-BIO/1547/2014). M.G. thanks the Institut Pasteur funding for the Action Ciblée-Collection. C.S. and P.M. acknowledge generous core funding by the European Molecular Biology Laboratory—European Bioinformatics Institute.

Author information

E.J.N.H., C.S., P.M. and J.P. designed the research. E.J.N.H., M.R., A.B., R.A.M. and J.P. performed bioinformatic analyses. E.J.N.H. performed statistical analyses, compiled the training dataset for TransATor, defined biosynthetic rules and generated biosynthetic models. P.M. designed the bioinformatics/chemoinformatics pipeline. P.M. and A.D. programmed TransATor. E.J.N.H. and A.D. validated TransATor and predicted compound structures. R.U. isolated compounds and performed structure elucidation. M.G., R.C. and G.C. provided genome sequences and bacterial strains. E.J.N.H. and J.P. wrote the manuscript with the help of all authors.

Correspondence to Pablo Moreno or Jörn Piel.

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Supplementary information

Supplementary Information

Supplementary Figures 1–12, Supplementary Tables 1–10

Reporting Summary

Supplementary Note

Synthetic Procedures

Supplementary Dataset 1

Maximum likelihood phylogenetic tree from a MUSCLE alignment of 655 KS sequences of all 54 characterized trans-AT PKS BGCs (as of December 2016).

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