Antonie van Leeuwenhoek

, Volume 102, Issue 3, pp 493–502 | Cite as

Reconstruction of the Saccharopolyspora erythraea genome-scale model and its use for enhancing erythromycin production

  • Cuauhtemoc Licona-Cassani
  • Esteban Marcellin
  • Lake-Ee Quek
  • Shana Jacob
  • Lars K. Nielsen
Original Paper


Genome-scale metabolic reconstructions are routinely used for the analysis and design of metabolic engineering strategies for production of primary metabolites. The use of such reconstructions for metabolic engineering of antibiotic production is not common due to the lack of simple design algorithms in the absence of a cellular growth objective function. Here, we present the metabolic network reconstruction for the erythromycin producer Saccharopolyspora erythraea NRRL23338. The model was manually curated for primary and secondary metabolism pathways and consists of 1,482 reactions (2,075 genes) and 1,646 metabolites. As part of the model validation, we explored the potential benefits of supplying amino acids and identified five amino acids “compatible” with erythromycin production, whereby if glucose is supplemented with this amino acid on a carbon mole basis, the in silico model predicts that high erythromycin yield is possible without lowering biomass yield. Increased erythromycin titre was confirmed for four of the five amino acids, namely valine, isoleucine, threonine and proline. In bioreactor experiments, supplementation with 2.5 % carbon mole of valine increased the growth rate by 20 % and simultaneously the erythromycin yield on biomass by 50 %. The model presented here can be used as a framework for the future integration of high-throughput biological data sets in S. erythraea and ultimately to realise strain designs capable of increasing erythromycin production closer to the theoretical yield.


S. erythraea Erythromycin Genome-scale metabolic reconstruction 



We gratefully acknowledge the financial support of the Mexican Council for Science and Technology (CONACyT) and the Australian Institute for Bioengineering and Nanotechnology (AIBN). We further would like to thank Michael Wang for support with HPLC analysis.

Conflict of interest

The authors have declared no conflict of interest.

Supplementary material

10482_2012_9783_MOESM1_ESM.xls (1 mb)
Supplementary material 1 (XLS 1074kb)
10482_2012_9783_MOESM2_ESM.pdf (65 kb)
Supplementary material 2 (PDF 65kb)
10482_2012_9783_MOESM3_ESM.pdf (50 kb)
Supplementary material 3 (PDF 49kb)
10482_2012_9783_MOESM4_ESM.xls (74 kb)
Supplementary material 4 (XLS 74kb)
10482_2012_9783_MOESM5_ESM.xls (74 kb)
Supplementary material 5 (XLS 74kb)


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Cuauhtemoc Licona-Cassani
    • 1
  • Esteban Marcellin
    • 1
  • Lake-Ee Quek
    • 1
  • Shana Jacob
    • 1
  • Lars K. Nielsen
    • 1
  1. 1.Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of QueenslandSt LuciaAustralia

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