Journal
MICROBIOLOGY-SGM
Volume 161, Issue -, Pages 1659-1670Publisher
MICROBIOLOGY SOC
DOI: 10.1099/mic.0.000118
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Funding
- National Institutes of Health [P20RR024237]
- National Science Foundation [DGE 0654336]
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Escherichia coli physiological, biomass elemental composition and proteome acclimations to ammonium-limited chemostat growth were measured at four levels of nutrient scarcity controlled via chemostat dilution rate. These data were compared with published iron- and glucose-limited growth data collected from the same strain and at the same dilution rates to quantify general and nutrient-specific responses. Severe nutrient scarcity resulted in an overflow metabolism with differing organic byproduct profiles based on limiting nutrient and dilution rate. Ammonium-limited cultures secreted up to 35 % of the metabolized glucose carbon as organic byproducts with acetate representing the largest fraction; in comparison, iron-limited cultures secreted up to 70 % of the metabolized glucose carbon as lactate, and glucose-limited cultures secreted up to 4 % of the metabolized glucose carbon as formate. Biomass elemental composition differed with nutrient limitation; biomass from ammonium-limited cultures had a lower nitrogen content than biomass from either iron- or glucose-limited cultures. Proteomic analysis of central metabolism enzymes revealed that ammonium- and iron-limited cultures had a lower abundance of key tricarboxylic acid (TCA) cycle enzymes and higher abundance of key glycolysis enzymes compared with glucose-limited cultures. The overall results are largely consistent with cellular economics concepts, including metabolic tradeoff theory where the limiting nutrient is invested into essential pathways such as glycolysis instead of higher ATP-yielding, but non-essential, pathways such as the TCA cycle. The data provide a detailed insight into ecologically competitive metabolic strategies selected by evolution, templates for controlling metabolism for bioprocesses and a comprehensive dataset for validating in silico representations of metabolism.
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