Modeling
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.
Maximum crocin production
To the model we added 9 reactions , which included the reactions from Crocus sativus for crocin production pathway, exchange reactions of end products, and a reaction which converts NADH to reduced ferredoxin. The last reaction was needed, because although the model has reactions which involve ferredoxin, the GSMM wasn’t able to produce any ferredoxin. Seeing that this might be a possible inaccuracy from reality, a simplified reaction for ferredoxin cycling was introduced. The maximum growth rate for the GSMM is set at 0.39 (1/h). To determine the maximum possible crocin production we fixed the growth rate to half the maximum - 0.2 (1/h). This allows for the excess substrate to go to crocin production instead of biomass. By doing this, with a glucose uptake rate of 5 mmol/gDW/h the maximum crocin production is 0.1691 mmol/gDW/h. Converting, this means a yield of crocin per glucose of 0.1836 g/g. This shows that R. toruloides is capable of crocin synthesis when 3 genes are introdoced. Furthermore, it shows that a realistic maximum crocin production yield on glucose can be almost 0.2 g/g.
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
Refrences:
[1] https://doi.org/10.1038/s41596-018-0098-2 [2] https://doi.org/10.1002/bit.27162 [3] https://doi.org/10.1038/ncomms15956 [4] https://doi.org/10.1016/j.jbiotec.2017.05.001 [5] https://doi.org/10.1021/acssynbio.1c00610