The effect of ethanol on aerobic BTEX biodegradation: The metabolic flux dilution model and continuous culture experiments.

摘要

The use of ethanol as an automotive fuel oxygenate represents potential economic and air-quality benefits. However, little is known about how ethanol may affect the natural attenuation of petroleum product releases. Chemostat experiments were conducted with four pure cultures (representing the archetypes of the known aerobic toluene degradation pathways) to determine how ethanol affects BTEX biodegradation kinetics. In all cases, the presence of ethanol decreased the metabolic flux of toluene (measured as the rate of toluene degradation per cell). This negative effect was counteracted by an ethanol-supported increase in biomass, which is conducive to faster degradation rates. Under carbon-limiting conditions, the metabolic flux of BTEX was proportional to its relative availability in the mixture, which decreases with increasing ethanol concentration. Metabolic flux dilution (MFD), a form of non-competitive inhibition that implies that the utilization of a carbon source in a mixture is proportional to its relative availability, was modeled without any fitting parameters based on the above finding. Thus, increasing concentrations of alternative carbon sources "dilute" the metabolic flux of toluene (or BTEX) without necessarily repressing tod, as observed with phenol (a known tod inducer) using a bioreporter strain, Pseudomonas putida TOD102. For all co-substrates, the MFD model slightly over-predicted the measured toluene metabolic flux. Incorporating catabolite repression (for experiments with acetate or ethanol) or competitive inhibition (for experiments with phenol) with independently obtained parameters resulted in more accurate fits of the observed decrease in toluene metabolic flux with increasing co-substrate concentration. These results imply that alternative carbon sources (including inducers) are likely to hinder toluene utilization per unit cell, and that these effects can be accurately predicted with simple mathematical models.