Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species


Filamentous fungi produce a wide range of bioactive compounds with important pharmaceutical applications, such as antibiotic penicillins and cholesterol-lowering statins. However, less attention has been paid to fungal secondary metabolites compared to those from bacteria. In this study, we sequenced the genomes of 9 Penicillium species and, together with 15 published genomes, we investigated the secondary metabolism of Penicillium and identified an immense, unexploited potential for producing secondary metabolites by this genus. A total of 1,317 putative biosynthetic gene clusters (BGCs) were identified, and polyketide synthase and non-ribosomal peptide synthetase based BGCs were grouped into gene cluster families and mapped to known pathways. The grouping of BGCs allowed us to study the evolutionary trajectory of pathways based on 6-methylsalicylic acid (6-MSA) synthases. Finally, we cross-referenced the predicted pathways with published data on the production of secondary metabolites and experimentally validated the production of antibiotic yanuthones in Penicillia and identified a previously undescribed compound from the yanuthone pathway. This study is the first genus-wide analysis of the genomic diversity of Penicillia and highlights the potential of these species as a source of new antibiotics and other pharmaceuticals.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Maximum likelihood phylogram and genome statistics of Penicillium species analysed in this study.
Figure 2: Functional analysis of Penicillium species.
Figure 3: Overview of the similarity of PKS and NRPS BGCs in Penicillium species.
Figure 4: Patulin and yanuthone D biosynthesis and BGCs.


  1. 1

    Aminov, R. I. A brief history of the antibiotic era: lessons learned and challenges for the future. Front. Microbiol. 1, 134 (2010).

    PubMed  PubMed Central  Google Scholar 

  2. 2

    Keller, N. P., Turner, G. & Bennett, J. W. Fungal secondary metabolism—from biochemistry to genomics. Nat. Rev. Microbiol. 3, 937–947 (2005).

    CAS  PubMed  Google Scholar 

  3. 3

    Nielsen, J. C. & Nielsen, J. Development of fungal cell factories for the production of secondary metabolites: linking genomics and metabolism. Synth. Syst. Biotechnol. (2017).

  4. 4

    Ziemert, N., Alanjary, M. & Weber, T. The evolution of genome mining in microbes—a review. Nat. Prod. Rep. 33, 988–1005 (2016).

    CAS  PubMed  Google Scholar 

  5. 5

    Medema, M. H. & Fischbach, M. A. Computational approaches to natural product discovery. Nat. Chem. Biol. 11, 639–648 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6

    Visagie, C. M. et al. Identification and nomenclature of the genus Penicillium. Stud. Mycol. 78, 343–371 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Barrios-González, J. & Miranda, R. U. Biotechnological production and applications of statins. Appl. Microbiol. Biotechnol. 85, 869–883 (2010).

    PubMed  Google Scholar 

  8. 8

    Fang, X., Shen, Y., Zhao, J., Bao, X. & Qu, Y. Status and prospect of lignocellulosic bioethanol production in China. Bioresour. Technol. 101, 4814–4819 (2010).

    CAS  PubMed  Google Scholar 

  9. 9

    García-Estrada, C. & Martín, J.-F. Biosynthetic gene clusters for relevant secondary metabolites produced by Penicillium roqueforti in blue cheeses. Appl. Microbiol. Biotechnol. 100, 8303–8313 (2016).

    PubMed  Google Scholar 

  10. 10

    Chai, B., Wu, Y., Liu, P., Liu, B. & Gao, M. Isolation and phosphate-solubilizing ability of a fungus, Penicillium sp. from soil of an alum mine. J. Basic Microbiol. 51, 5–14 (2011).

    CAS  PubMed  Google Scholar 

  11. 11

    Richardson, A. E. & Simpson, R. J. Soil microorganisms mediating phosphorus availability update on microbial phosphorus. Plant Physiol. 156, 989–996 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Puel, O., Galtier, P. & Oswald, I. P. Biosynthesis and toxicological effects of patulin. Toxins 2, 613–631 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Grijseels, S . et al. Penicillium arizonense, a new, genome sequenced fungal species, reveals a high chemical diversity in secreted metabolites. Sci. Rep. 6, 35112 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14

    Park, M. S., Lee, E. J., Fong, J. J., Sohn, J. H. & Lim, Y. W. A new record of Penicillium antarcticum from marine environments in Korea. Mycobiology 42, 109–113 (2014).

    PubMed  PubMed Central  Google Scholar 

  15. 15

    Houbraken, J., Wang, L., Lee, H. B. & Frisvad, J. C. New sections in Penicillium containing novel species producing patulin, pyripyropens or other bioactive compounds. Persoonia 36, 299–314 (2015).

    Google Scholar 

  16. 16

    Weber, T. et al. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters. Nucleic Acids Res. 43, W237–W243 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Kroken, S., Glass, N. L., Taylor, J. W., Yoder, O. C. & Turgeon, B. G. Phylogenomic analysis of type I polyketide synthase genes in pathogenic and saprobic ascomycetes. Proc. Natl Acad. Sci. USA 100, 15670–15675 (2003).

    CAS  PubMed  Google Scholar 

  18. 18

    Rausch, C., Hoof, I., Weber, T., Wohlleben, W. & Huson, D. H. Phylogenetic analysis of condensation domains in NRPS sheds light on their functional evolution. BMC Evol. Biol. 7, 78 (2007).

    PubMed  PubMed Central  Google Scholar 

  19. 19

    Ziemert, N. et al. Diversity and evolution of secondary metabolism in the marine Actinomycete genus Salinispora. Proc. Natl Acad. Sci. USA 111, E1130–E1139 (2014).

    CAS  PubMed  Google Scholar 

  20. 20

    Medema, M. H. et al. Minimum information about a biosynthetic gene cluster. Nat. Chem. Biol. 11, 625–631 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Klejnstrup, M. L. et al. Genetics of polyketide metabolism in Aspergillus nidulans. Metabolites 2, 100–133 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22

    Artigot, M. P. et al. Molecular cloning and functional characterization of two CYP619 cytochrome P450s involved in biosynthesis of patulin in Aspergillus clavatus. Microbiology 155, 1738–1747 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23

    Holm, D. K. et al. Molecular and chemical characterization of the biosynthesis of the 6-MSA-derived meroterpenoid yanuthone D in Aspergillus niger. Chem. Biol. 21, 519–529 (2014).

    CAS  PubMed  Google Scholar 

  24. 24

    Frisvad, J. C., Smedsgaard, J., Larsen, T. O. & Samson, R. A. Mycotoxins, drugs and other extrolites produced by species in Penicillium subgenus penicillium. Stud. Mycol. 49, 201–241 (2004).

    Google Scholar 

  25. 25

    Vansteelandt, M. et al. Patulin and secondary metabolite production by marine-derived Penicillium strains. Fungal Biol. 116, 954–961 (2012).

    CAS  PubMed  Google Scholar 

  26. 26

    Boysen, M., Skouboe, P., Frisvad, J. & Rossen, L. Reclassification of the Penicillium roqueforti group into three species on the basis of molecular genetic and biochemical profiles. Microbiology 142, 541–549 (1996).

    CAS  PubMed  Google Scholar 

  27. 27

    Ballester, A. et al. Genome, transcriptome, and functional analyses of Penicillium expansum provide new insights into secondary metabolism and pathogenicity. Mol. Plant–Microbe Interact. 28, 232–248 (2015).

    CAS  PubMed  Google Scholar 

  28. 28

    Medema, M. H., Cimermancic, P., Sali, A., Takano, E. & Fischbach, M. A. A systematic computational analysis of biosynthetic gene cluster evolution: lessons for engineering biosynthesis. PLoS Comput. Biol. 10, e1004016 (2014).

    PubMed  PubMed Central  Google Scholar 

  29. 29

    Banani, H. et al. Genome sequencing and secondary metabolism of the postharvest pathogen Penicillium griseofulvum. BMC Genomics 17, 19 (2016).

    PubMed  PubMed Central  Google Scholar 

  30. 30

    Itoh, T. et al. Reconstitution of a fungal meroterpenoid biosynthesis reveals the involvement of a novel family of terpene cyclases. Nat. Chem. 2, 858–864 (2010).

    CAS  PubMed  Google Scholar 

  31. 31

    Petersen, L. M., Holm, D. K., Gotfredsen, C. H., Mortensen, U. H. & Larsen, T. O. Investigation of a 6-MSA synthase gene cluster in Aspergillus aculeatus reveals 6-MSA-derived aculinic acid, aculins A-B and Epi-Aculin A. ChemBioChem 16, 2200–2204 (2015).

    CAS  PubMed  Google Scholar 

  32. 32

    Guo, C.-J., Sun, W.-W., Bruno, K. S. & Wang, C. C. C. Molecular genetic characterization of terreic acid pathway in Aspergillus terreus. Org. Lett. 16, 5250–5253 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. 33

    Bacha, N. et al. Cloning and characterization of novel methylsalicylic acid synthase gene involved in the biosynthesis of isoasperlactone and asperlactone in Aspergillus westerdijkiae. Fungal Genet. Biol. 46, 742–749 (2009).

    CAS  PubMed  Google Scholar 

  34. 34

    Brakhage, A. A. Regulation of fungal secondary metabolism. Nat. Rev. Microbiol. 11, 21–32 (2013).

    CAS  PubMed  Google Scholar 

  35. 35

    Wisecaver, J. H. & Rokas, A. Fungal metabolic gene clusters—caravans traveling across genomes and environments. Front. Microbiol. 6, 161 (2015).

  36. 36

    Chae, L., Kim, T., Nilo-Poyanco, R. & Rhee, S. Y. Genomic signatures of specialized metabolism in plants. Science 344, 510–513 (2014).

    CAS  PubMed  Google Scholar 

  37. 37

    Li, Y. F. et al. Comprehensive curation and analysis of fungal biosynthetic gene clusters of published natural products. Fungal Genet. Biol. 89, 18–28 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    Gao, X. et al. Fungal indole alkaloid biosynthesis: genetic and biochemical investigation of the tryptoquialanine pathway in Penicillium aethiopicum. J. Am. Chem. Soc. 133, 2729–2741 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Chooi, Y.-H., Cacho, R. & Tang, Y. Identification of the viridicatumtoxin and griseofulvin gene clusters from Penicillium aethiopicum. Chem. Biol. 17, 483–494 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    Petersen, L. M. et al. Characterization of four new antifungal yanuthones from Aspergillus niger. J. Antibiot. 68, 201–205 (2015).

    CAS  PubMed  Google Scholar 

  41. 41

    Li, X., Choi, H. D., Kang, J. S., Lee, C.-O. & Son, B. W. New polyoxygenated farnesylcyclohexenones, deacetoxyyanuthone A and its hydro derivative from the marine-derived fungus Penicillium sp. J. Natural Prod. 66, 1499–1500 (2003).

    CAS  Google Scholar 

  42. 42

    Maskey, R. P., Grün-Wollny, I. & Laatsch, H. Sorbicillin analogues and related dimeric compounds from Penicillium notatum. J. Natural Prod. 68, 865–870 (2005).

    CAS  Google Scholar 

  43. 43

    Simpson, J. et al. ABySS: a parallel assembler for short read sequence data. Genome Res. 19, 1117–1123 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Luo, R. et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1, 18 (2012).

    PubMed  PubMed Central  Google Scholar 

  45. 45

    Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Chevreux, B., Thomas, W. & Suhai, S. Genome sequence assembly using trace signals and additional sequence information. Comp. Sci. Biol. 99, 45–56 (1999).

    Google Scholar 

  47. 47

    Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48

    Vezzi, F., Narzisi, G. & Mishra, B. Reevaluating assembly evaluations with feature response curves: gAGE and assemblathons. PLoS ONE 7, e52210 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Smit, A., Hubley, R. & Green, P. RepeatMasker Open-4.0 (2015);

  50. 50

    Smit, A. & Hubley, R. RepeatModeler Open-1.0 (2015);

  51. 51

    The UniProt consortium. UniProt: a hub for protein information. Nucleic Acids Res. 43, D204–D212 (2014).

  52. 52

    Lomsadze, A., Burns, P. D. & Borodovsky, M. Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm. Nucleic Acids Res. 42, e119 (2014).

    PubMed  PubMed Central  Google Scholar 

  53. 53

    Kim, D. et al. Tophat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).

    PubMed  PubMed Central  Google Scholar 

  54. 54

    Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Holt, C. & Yandell, M. MAKER2: an annotation pipeline and genome-database management tool for second-generation genome projects. BMC Bioinformatics 12, 491 (2011).

    PubMed  PubMed Central  Google Scholar 

  56. 56

    Zdobnov, E. M. & Apweiler, R. InterProScan—an integration platform for the signature-recognition methods in InterPro. Bioinformatics 17, 847–848 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57

    Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015).

    PubMed  Google Scholar 

  58. 58

    Li, L., Stoeckert, C. J. J. & Roos, D. S. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 13, 2178–2189 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Agren, R. et al. The RAVEN toolbox and its use for generating a genome-scale metabolic model for Penicillium chrysogenum. PLoS Comput. Biol. 9, e1002980 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60

    Yin, Y. et al. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 40, W445–W451 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Felsenstein, J. PHYLIP—phylogeny inference package (version 3.2). Cladistics 5, 164–166 (1989).

    Google Scholar 

  64. 64

    Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. Prottest 3: fast selection of best-fit models of protein evolution. Bioinformatics 27, 1164–1165 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Stamatakis, A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 22, 2688–2690 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Guindon, S. et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321 (2010).

    CAS  Google Scholar 

  68. 68

    Huerta-Cepas, J., Serra, F. & Bork, P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69

    Ziemert, N . et al. The natural product domain seeker NaPDoS: a phylogeny based bioinformatic tool to classify secondary metabolite gene diversity. PLoS ONE 7, e34064 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70

    Smith, T. F. & Waterman, M. S. Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197 (1981).

    CAS  PubMed  Google Scholar 

  71. 71

    Cock, P. J. A. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. 72

    Medema, M. H., Takano, E. & Breitling, R. Detecting sequence homology at the gene cluster level with multigeneblast. Mol. Biol. Evol. 30, 1218–1223 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Kildgaard, S. et al. Accurate dereplication of bioactive secondary metabolites from marine-derived fungi by UHPLC-DAD-QTOFMS and a MS/HRMS library. Mar. Drugs 12, 3681–3705 (2014).

    PubMed  PubMed Central  Google Scholar 

  74. 74

    Klitgaard, A., Nielsen, J. B., Frandsen, R. J. N., Andersen, M. R. & Nielsen, K. F. Combining stable isotope labeling and molecular networking for biosynthetic pathway characterization. Anal. Chem. 87, 6520–6526 (2015).

    CAS  PubMed  Google Scholar 

  75. 75

    Nielsen, K. F., Månsson, M., Rank, C., Frisvad, J. C. & Larsen, T. O. Dereplication of microbial natural products by LC-DAD-TOFMS. J. Natural Prod. 74, 2338–2348 (2011).

    CAS  Google Scholar 

  76. 76

    Tannous, J. et al. Sequencing, physical organization and kinetic expression of the patulin biosynthetic gene cluster from Penicillium expansum. Int. J. Food Microbiol. 189, 51–60 (2014).

    CAS  PubMed  Google Scholar 

Download references


This work was supported by the European Commission Marie Curie Initial Training Network Quantfung (FP7-People-2013-ITN, grant no. 607332), the Novo Nordisk Foundation and the Knut and Alice Wallenberg Foundation. The computations were performed using resources at the Chalmers Centre for Computational Science and Engineering (C3SE) provided by the Swedish National Infrastructure for Computing (SNIC). Sequencing support was provided by the Science for Life Laboratory (SciLifeLab), National Genomics Infrastructure (NGI) and UPPMAX (UPPNEX project ID no. b2014081). Support on genome annotation by the National Bioinformatics Infrastructure Sweden (NBIS) is acknowledged. Agilent Technologies is acknowledged for the Thought Leader Donation of the 6545 UHPLC-QTOF. The authors thank H. Wang for comments on the manuscript.

Author information




J.C.N., J.C.F., M.W. and J.N. conceived the study. J.C.N. designed and performed the bioinformatics computations, and analysed and interpreted the data. S.P. and B.J. assisted with bioinformatics design and interpretation. J.D. carried out the annotation of the genomes. S.G. and K.F.N. generated culture extracts and performed LC–MS analysis. J.C.N., S.G. and J.N. wrote the manuscript. All authors read and approved the final version of the manuscript.

Corresponding author

Correspondence to Jens Nielsen.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Figures 1–12, Supplementary Table 1, Supplementary References. (PDF 13841 kb)

Supplementary Data 1 and 2

Supplementary Data 1: Detected PKS containing BGCs mapped to BGCs in the MIBiG database. Supplementary Data 2: Detected NRPS containing BGCs mapped to BGCs in the MIBiG database. (XLSX 51 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Nielsen, J., Grijseels, S., Prigent, S. et al. Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species. Nat Microbiol 2, 17044 (2017).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing