As the world recognizes the need for more sustainable practices, greater effort has been put into improving the economic viability of bioprocesses. Fields like metabolic engineering explore strategies to improve the production of bioproducts of industrial relevance, such as the use of alternative carbon sources. Regarding the performance assessment of a bioprocess, the product yield can be helpful, but other parameters like product titer and productivity (rate of production) are just as important. Furthermore, the highest performance may not come from a scenario with the highest yield, titer or productivity, but from a titer, rate, yield (TRY) set that maximizes profitability when the production costs are considered. Our previous work introduced the DySEEP approach, which uses an economic metric based on TRY parameters for evaluation of the potential of bioprocesses. This work expands the DySEEP program in key areas such as adding the possibility of exploring fed-batch processes and using strain design algorithms. Taking batch and fed-batch poly-3-hydroxybutyrate (PHB) production with E. coli as the case study, the scenarios that would lead to economic viability and the theoretical maximum performance for three different carbon sources, glucose, glycerol, and xylose, were identified. The results were then set in a strain design algorithm using Minimal Cut Sets (MCS) to find genetic interventions that could achieve the desired performance. The genetic interventions found with the MCS algorithm successfully led to strains that achieve the economic viability scenario, based on in silico simulations. This work illustrates how the expanded approach can be used to guide metabolic engineering strategies to improve the production of important bioproducts.
Santos et al. (Wed,) studied this question.