Journal of Industrial Microbiology & Biotechnology

, Volume 38, Issue 9, pp 1295–1304 | Cite as

A novel docking domain interface model predicting recombination between homoeologous modular biosynthetic gene clusters

  • Antonio Starcevic
  • Janko Diminic
  • Jurica Zucko
  • Mouhsine Elbekali
  • Tobias Schlosser
  • Mohamed Lisfi
  • Ana Vukelic
  • Paul F. Long
  • Daslav Hranueli
  • John Cullum
Original Paper

Abstract

An in silico model for homoeologous recombination between gene clusters encoding modular polyketide synthases (PKS) or non-ribosomal peptide synthetases (NRPS) was developed. This model was used to analyze recombination between 12 PKS clusters from Streptomyces species and related genera to predict if new clusters might give rise to new products. In many cases, there were only a limited number of recombination sites (about 13 per cluster pair), suggesting that recombination may pose constraints on the evolution of PKS clusters. Most recombination events occurred between pairs of ketosynthase (KS) domains, allowing the biosynthetic outcome of the recombinant modules to be predicted. About 30% of recombinants were predicted to produce polyketides. Four NRPS clusters from Streptomyces strains were also used for in silico recombination. They yielded a comparable number of recombinants to PKS clusters, but the adenylation (A) domains contained the largest proportion of recombination events; this might be a mechanism for producing new substrate specificities. The extreme G + C-content, the presence of linear chromosomes and plasmids, as well as the lack of a mutSL-mismatch repair system should favor production of recombinants in Streptomyces species.

Keywords

Polyketide synthase Non-ribosomal peptide synthetase Streptomyces Bacillus Chi sequence 

Supplementary material

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Supplementary material 1 (XLS 643 kb)
10295_2010_909_MOESM2_ESM.xls (34 kb)
Supplementary material 2 (XLS 33 kb)
10295_2010_909_MOESM3_ESM.xls (28 kb)
Supplementary material 3 (XLS 28 kb)

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Copyright information

© Society for Industrial Microbiology 2010

Authors and Affiliations

  • Antonio Starcevic
    • 1
    • 2
  • Janko Diminic
    • 2
  • Jurica Zucko
    • 1
    • 2
  • Mouhsine Elbekali
    • 1
  • Tobias Schlosser
    • 1
  • Mohamed Lisfi
    • 1
  • Ana Vukelic
    • 3
  • Paul F. Long
    • 4
  • Daslav Hranueli
    • 2
  • John Cullum
    • 1
  1. 1.LB GenetikUniversity of KaiserslauternKaiserslauternGermany
  2. 2.Section for Bioinformatics, Faculty of Food Technology and BiotechnologyUniversity of ZagrebZagrebCroatia
  3. 3.Section for Mathematics, Faculty of Food Technology and BiotechnologyUniversity of ZagrebZagrebCroatia
  4. 4.Pharmaceutical Science InstituteKing’s College LondonLondonUK

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