Dynamic FBA with Global Constraints on Cellular Protein Fraction

In this presentation, I will first briefly discuss recently developed software in our group that aids in the process of model reconstruction and curation: (i) AutoKEGGRec [1], a COBRA toolbox pipline based on KEGG that creates first draft metabolic network reconstructions of single organisms, reconstructions based on a list of organisms, and finally a consolidated reconstruction for a list of organisms or strains. (ii) ModelExplorer [2], a visual software framework to assist the user in exploring and curating genome-scale metabolic models provided in the sbml format. ModelExplorer automatically visualizes a metabolic network as a graph with a distinct separation and delineation of cellular compartments. Additionally, ModelExplorer highlights reactions and species that are unable to carry flux or participate in flux generation (ie. blocked), with the use of several different consistency checking modes available.

Using high-quality models resulting from curation efforts, it is possible to apply a plethora of constraint-based methods to analyze the models' phenotypes. I will discuss a recently developed method that combines dynamic Flux Balance Analysis (dFBA) with a global constraint on cellular protein fraction [3]. We apply our method to a recent E. coli genome-scale reconstruction, finding that our method outperforms existing dFBA formulation. The globally-constrained dFBA method makes it possible to investigate cellular proteome composition in response to changing nutrient conditions.

[1] E. Karlsen, C. Schulz and E. Almaas. Submitted.

[2] N. Martyushenko and E. Almaas. Submitted.

[3] E. Karlsen and E. Almaas. In preparation.