Before even stepping a foot in a lab, in silico modeling techniques can shed light on the possible best designs and how to obtain them. Genome-scale metabolic modeling [1] allows us to assess if a design is theoretically possible, is it worth pursuing and how to obtain it. Therefore, genome-scale metabolic modeling can be a critical part for the design stages in synthetic biology.

Genome-scale metabolic modeling

Rhodotorula toruloides has a published genome scale metabolic model (GSMM) [2]. This is a constraint based model and only describes the stoichiometry of metabolism. Using this model we determined the best possible outcome and the possibility of growth coupling.


GSMMs can help growth-couple a product [3]. Because GSMMs include all possible reaction stoichiometry, it can be determined which reactions must be deleted to make growth without production of a desired metabolite infeasible. However, for secondary metabolites that are not involved in the energy metabolism, usually this is impossible. Multiple computational methods have been made to determine knockouts that guarantee growth-coupling of a product. We used three methods - CellNetAnalyzer [4], optDesign [5] and optEnvelope [publication pending]. None of these methods could achieve growth-coupling of crocin. These findings suggest that growth-coupling of crocin using GSMMs in R. toruloides is impossible.

access our genome scale metabolic model here