1. Greg Challis Department of Chemistry Lecture 1: Methods for in silico analysis of cryptic natural product biosynthetic gene clusters Microbial Genomics and Secondary Metabolites Summer School, MedILS, Split, Croatia, 25-29 June 2007

2. Overview Introduction cryptic (orphan) gene clusters in microbial genomes Clusters encoding nonribosomal peptide synthetases (NRPSs) domains, modules, substrate specificity, predicting products Clusters encoding modular polyketide synthases (PKSs) domains, modules, substrate specificity, predicting products Clusters encoding other biosynthetic systems terpene synthases, iterative PKSs

3. Introduction

4. ‘Cryptic’ (orphan) biosynthetic gene clusters Present in many of the 300 or so sequenced microbial genomes e.g. Streptomyces avermitilis Streptomyces coelicolor Bacillus subtilis Pseudomonas fluorescens Pseudomonas syringae Nostoc punctiforme Aspergillus nidulans May prove a valuable new source of bioactive metabolites Polyketide synthases Nonribosomal peptide synthetases Terpene synthases

5. Genome sequence of the model antibiotic- producer Streptomyces coelicolor M145

6. Gene clusters directing complex metabolite biosynthesis in the S. coelicolor genome Bentley et al. Nature (2002) 417, 141-147

7. Part 1: Nonribosomal peptide synthetase analysis

8. Recap of NRPS organisation and function: the gramicidin S synthetase as an example AECAAACCCATE module 1 module 2 module 3 module 4 module 5 grsAgrsBgrsT synthetase 1synthetase 2 PCP A = Adenylation PCP = peptidyl carrier protein C = Condensation E = Epimerisation TE = Thioesterase

9. Recap of NRPS organisation and function: the gramicidin S synthetase as an example TE PCP For further information see Lars Robbel’s poster

10. Nonribosomal peptide synthetases encoded by the S. coelicolor genome

11. A new S. coelicolor NRPS gene cluster cchAcchBcchH Flavin-dependent monooxygenase (cchB) Non-ribosomal peptide synthetase (cchH) Formyl-tetrahydrofolate-dependent formyl transferase (cchA) MbtH-like protein (cchK) Esterase (cchJ) Challis and Ravel FEMS Microbiol. Lett. (2000) 187, 111-114 Export functions Ferric-siderophore import cchJcchI

12. Prediction of domain and module structure Conserved Domain (CD) search (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) Deduced domain and module organization

13. Prediction of A-domain selectivity pocket residues GrsA DASVWEMFMALLTGASLYIILKDTINDFVKFEQYINQKEITVITLPPTYVVHL-----DPERILSIQTLITAGSATSPSLVNKWKEK--VTYINAYGPTETTI Ncs1-M1 DIAVWELLAAFVGGARLVIAEHRLRGVVPHLPELMTDHRVTVAHFVPSVLEELLGWMADGGRVG-LRLVVCGGEAVPPSQRDRLLALSGARMVHAYGPTETTI GrsA D A W T I A A I Ncs1-M1 D I W H V G A I Stachelhaus, Mootz and Marahiel Chem. Biol. (1999) 6, 493-505 Challis, Ravel and Townsend Chem. Biol. (2000) 7, 211-224

14. Empirical correlation between specificity pocket residues and substrate Challis, Ravel and Townsend Chem. Biol. (2000) 7, 211-224

15. Prediction of substrates and possible products for the S. coelicolor cryptic NRPS Challis and Ravel FEMS Microbiol. Lett. (2000) 187, 111-114

16. Part 2: Modular polyketide synthase analysis

17. Three large modular enzymes (DEBS 1- 3), encoded by eryAI, eryAII, and eryAIII, assemble 6-DEB Each module performs one chain extension Recap of modular PKS organisation and function: the erythromycin synthase as an example

18. -CO 2

19. Three large modular enzymes (DEBS 1- 3), encoded by eryAI, eryAII, and eryAIII, assemble 6-DEB Each module performs one chain extension Recap of modular PKS organisation and function: the erythromycin synthase as an example

20. Gene clusters directing complex metabolite biosynthesis in the S. coelicolor genome Bentley et al. Nature (2002) 417, 141-147

21. A new S. coelicolor modular PKS cluster Genes encoding a modular PKS

22. Prediction of domain and modules in CpkA Conserved Domain (CD) search (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi)

23. Prediction of domain and modules in CpkB

24. Prediction of domain and modules in CpkC

25. Prediction of domains and modules in CpkABC Pawlik, Kotowska, Chater, Kuczek and Takano Arch. Microbiol. (2007) 187, 87-99

26. Prediction of AT domain substrate selectivity Haydock et al. FEBS Lett. (1995) 374, 246-248 Banskota et al. J. Antibiot. (2006) 59, 168-176

27. Prediction of KR domain stereoselectivity

28. Caffrey ChemBioChem (2003) 4, 654-657 Reid et al. Biochemistry (2003) 42, 72-79

29. Prediction of substrates and possible products for the S. coelicolor cryptic PKS

30. Non-linear enzymatic logic can complicate things! Haynes and Challis, Curr. Op. Drug Discov. Develop. (2007) 10, 203-218

31. Non-linear enzymatic logic can complicate things! Haynes and Challis, Curr. Op. Drug Discov. Develop. (2007) 10, 203-218

32. Part 3: Analysis of other biosynthetic systems

33. Terpene synthases

34. Iterative polyketide synthases – type III PKSs

35. Conclusions Reasonably confident in silico predictions of domain / module organisation and substrate specificity of modular PKS / NRPS can be made Non-linear enzymatic logic can complicate the reliable prediction of product structure(s) For other types of biosynthetic system, reasonably confident predictions of substrate specificity can sometimes be made Prediction of chain length and substrate specificity in some iterative PKS systems, especially type III and fungal type I, remains difficult