iOD907, the first genome-scale metabolic model for the milk yeast Kluyveromyces lactis
We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is partially compartmentalized (4 compartments), composed of 1867 reactions and 1476 metabolites. The iOD907 model performed well when assessing the positive growth of K. lactis to Biolog experiments and to a...
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Veröffentlicht in: | Biotechnology journal 2014-06, Vol.9 (6), p.776-790 |
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Zusammenfassung: | We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is partially compartmentalized (4 compartments), composed of 1867 reactions and 1476 metabolites. The iOD907 model performed well when assessing the positive growth of K. lactis to Biolog experiments and to an online catalogue of strains that provides information on carbon sources in which K. lactis is able to grow. Chemostat experiments were used to adjust non-growth-associated energy requirements, and the model proved accurate when predicting the biomass, oxygen and carbon dioxide yields. In silico knockouts predicted in vivo phenotypes accurately when compared to published experiments. The iOD907 genome-scale metabolic model complies with the MIRIAM standards for the annotation of enzymes, transporters, metabolites and reactions. Moreover, it contains direct links to KEGG (for enzymes, metabolites and reactions) and to TCDB for transporters, allowing easy comparisons to other models. Furthermore, this model is provided in the well-established SBML format, which means that it can be used in most metabolic engineering platforms, such as OptFlux or Cobra. The model is able to predict the behavior of K. lactis under different environmental conditions and genetic perturbations. Furthermore, it can also be important in the design of minimal media and will allow insights on the milk yeast's metabolism, as well as identifying metabolic engineering targets for the improvement of the production of products of interest by performing simulations and optimizations.
The authors thank strategic Project PEst-OE/EQB/LA0023/2013 and project "BioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes, REF. NORTE-07-0124-FEDER-000028" co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER. The authors would also like to acknowledge Steve Sheridan for proof reading this manuscript. |
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ISSN: | 1860-6768 1860-7314 |
DOI: | 10.1002/biot.201300242 |