776 © 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim Biotechnol. J. 2014, 9, 776–790 DOI 10.1002/biot.201300242 www.biotechnology-journal.com Biotechnology Journal 1 Introduction Genome-scale metabolic models are now established tools utilized in a wide range of biotechnological applica- tions, such as metabolic engineering of microbes or drug targeting [1–6]. Although a large majority of the available models are those of prokaryotes, the number of models for eukaryotic organisms has been increasing rapidly (www.optflux.org/models). In recent years, some steps have been taken to stan- dardize the methodology for the reconstruction of genome- scale metabolic models, for instance the publication of a detailed protocol by Thiele and Palsson [7] for the develop- ment of a standard that determines the minimum informa- tion required for the annotation of biochemical models (MIRIAM) [8]. Nevertheless, the reconstruction of the meta- bolic network of an organism is still a complex procedure. The same process may, in theory, be applied for recon- structing eukaryotic and prokaryotic metabolic models [7]. Nevertheless, eukaryotic models are more demanding due to their larger knowledge base and genomes, as well as the various compartments within the cells. Correspondence: Dr. Oscar Dias, CEB – Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, 4710-057, Braga, Portugal E-mail: odias@deb.uminho.pt Abbreviations: EC, enzyme commission; FBA, flux balance analysis; GPR, gene-protein-reaction; KEGG, Kyoto encyclopedia of genes and genomes; MIRIAM, minimum information required for the annotation of biochemical models; P/O, phosphorus to oxygen; SBML, systems biology markup language; TCDB, Transporters Classification Database Biotechnology Journal Research Article iOD907, the first genome-scale metabolic model for the milk yeast Kluyveromyces lactis Oscar Dias 1 , Rui Pereira 1 , Andreas K. Gombert 2 , Eugénio C. Ferreira 1 and Isabel Rocha 1 1 CEB – Centre of Biological Engineering, Universidade do Minho, Campus de Gualtar, Braga, Portugal 2 Faculty of Food Engineering and Bioenergy Laboratory, University of Campinas (UNICAMP), Campinas, SP, Brazil We describe here the first genome-scale metabolic model of Kluyveromyces lactis, iOD907. It is par- tially compartmentalized (four compartments), composed of 1867 reactions and 1476 metabo- lites. The iOD907 model performed well when comparing 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-associat- ed energy requirements, and the model proved accurate when predicting the biomass, oxygen and carbon dioxide yields. When compared to published experiments, in silico knockouts accurately predicted in vivo phenotypes. The iOD907 genome-scale metabolic model complies with the MIRIAM (minimum information required for the annotation of biochemical models) standards for the annotation of enzymes, transporters, metabolites and reactions. Moreover, it contains direct links to Kyoto encyclopedia of genes and genomes (KEGG; for enzymes, metabolites and reac- tions) and to the Transporters Classification Database (TCDB) for transporters, allowing easy comparisons to other models. Furthermore, this model is provided in the well-established systems biology markup language (SBML) format, which means that it can be used in most metabolic engi- neering 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, by performing simulations and optimizations, it can 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 improving the production of products of interest. Keywords: Bioinformatics · Fungi · Genome-scale metabolic model · Metabolic engineering · Systems biology Received 14 JAN 2014 Revised 07 APR 2014 Accepted 23 APR 2014 Accepted article online 28 APR 2014 Supporting information available online