Michael Jahn

Cupriavidus necator Genome Scale Model We recently prepared a genome scale metabolic model for Ralstonia eutropha a.k.a. Cupriavidus necator H16. The model was previously published in Park et al., 2011, but no defined genome scale model definition was published with this paper, except from a PDF description. The original model in PDF format was later parsed and converted to SBML standard in a publication by Peyraud et al., PLoS Pathogens, 12(10), 2016, discovering a resource allocation trade-Off between virulence and proliferation in the plant pathogen Ralstonia solanacearum.

Purpose of RBA models The resource balance analysis (RBA) model is an extension of a standard genome scale model (GSM) where the solution space is constrained by many additional parameters. The topology of the metabolic network and its gene and reaction annotations are taken from the GSM. In a next step, enzymes and cellular ‘machineries’ are built based on data retrieved from uniprot. The model simulates all cellular processes from DNA replication, to transcription, translation and protein folding. The protein pool is limited so that the optimization of gene expression towards a specific objective (e.g. growth) becomes dependent on environmental parameters but also rate limitations. Catalytic efficiency of enzymes links enzyme abundance to maximal rate so that flux through the metabolic network can not become infinitely high.

Purpose of the model In order to study the fundamental processes in photo-autotrophic bacteria, we developed a simplified cellular economy model for the simulation of these processes. The purpose of such models is not to reflect cellular behavior in its entire complexity, but rather to reduce complexity to an amount that still allows drawing significant conclusions while keeping the number of components and reactions as small as possible. The cellular economy model bundles fundamental processes in ‘super-enzymes’, single catalytic units that serve as proxies for similar pathways. Such coarse-grain models are useful to illustrate metabolic tradeoffs under different conditions without getting lost in details.