(390a) Proteomic, Physiological, and In Silico Testing of Economic Tradeoffs In Metabolic Networks

Microbes conserve energy and perform carbon conversions using robust and often redundant networks of enzymatic machinery. Competition for resources in nature has likely selected for phenotypes wherein operational metabolic pathways optimize tradeoffs between catabolic efficiency of an enzyme set and the investment of anabolic nutrients required to synthesize the enzymes. An in silico economics-based analysis quantified molecular-level, resource allocation tradeoff strategies that permit competitive cellular functioning under a continuum of nutrient scarcities. The analysis decomposed a metabolic network into a complete listing of non-divisible, mathematically-defined biochemical pathways which were then used to identify all strategies for investing limiting resources like iron and nitrogen into the genome encoded metabolic machinery. Nitrogen, for example, is required for the synthesis of every enzyme; as nitrogen availability decreases, tradeoff analysis predicts a testable shift from catabolism optimized phenotypes to nitrogen investment-optimized phenotypes. In silico predictions were evaluated experimentally using physiological and proteomic data collected from iron- or nitrogen-limited Escherichia coli chemostat cultures. Experimental chemostat data trends were consistent with in silico theory and illustrated that under iron- and nitrogen-limited conditions E. coli regulates its metabolism to invest scarce resource competitively at the cost of optimal biomass yields on electron donor. The study highlights a fundamental evolutionary and metabolic design paradigm for competitive network structure and control with applications to bioprocess engineering, environmental microbiology and treatment of microbial pathogens.