Hy-Dynfba: A Software Platform to Build Large Models, Hybrid in Time Scale

Large scale dynamic simulation of (microbial) metabolism is of great interest within systems biology and metabolic engineering community, in several aspects, e.g. to obtain time traces of intermediates, to study regulation etc. This in turn, is one of the big challenges since such an endeavor requires a large amount of detail about the metabolic reaction networks and is hampered by e.g. the presence of multiple time-scales (from sub seconds e.g. covalent modifications, to hours e.g. protein synthesis), lack of knowledge in mechanisms of individual reactions, correlated kinetic parameters, lack of data to specify the parameters etc.

One of the approaches for genome scale modeling of microbial metabolism, namely flux balance analysis, enjoyed the simplification on time scale differences, and has proven to be very useful, supported by several applications in literature. Kinetic modeling, in contrast, despite much greater information it provides and a longer research history, is at its infancy with respect to the size of the models, chiefly because of the above mentioned challenges. Modeling strategies that would be high in coverage, yet manageable in complexity is therefore of immediate interest.  Resultingly, tools that would systematically integrate (preferably genome scale) flux models with much smaller kinetic models, whereby integrate multiple time scales is desired.

In this work, we present such a tool for simulation of large scale systems, making use of available software, built upon reliable stack of open source python libraries. Hy-DynFBA software uses COBRApie as an extension to construct, manipulate and import/export flux models. The software then allows selecting desired kinetics with corresponding parameters, for a subset of reactions, assigns convenience kinetics by default if the mechanism of the selected reactions are not known. The talk will introduce the concept, theoretical background, equations and will further focus on implementations on modeling yeast (Saccharomyces cerevisiae) response to weak acid stress.