In particular, constraint-based modelling techniques on genome scale models, such as flux balance analysis (FBA) are successfully applied to consortia of well-studied organisms (see a recent review of classical methods and available tools ). Moreover, networks exploring the dynamic FBA (dFBA), have been developed and successfully applied to study the emergent properties of subpopulations of a monoculture , predict the optimal partner to form a consortium via pairing experiments , or explain steady-state population distributions of a three-species consortium . However, despite knowledge regarding microbial interactions that these methods provide, they do not yet provide a rational approach for a new design of an artificial organism within an artificial community. Whether it is a production of a completely novel compound, or just a more efficient production of a known one, computational models should inform the choice of molecular modules, e.g., by providing quantitative predictions regarding the performance of the end product. Ideally, computational frameworks could provide guidance as in the work by Schwander et al., where using theoretical tools and simple laws of thermodynamics, new enzymatic steps have been proposed to be included into the carbon fixation pathway, guiding the creation of a more efficient, synthetic CO 2 fixing pathway .