Literature DB >> 15162456

Effect of ethanol, acetate, and phenol on toluene degradation activity and tod-lux expression in Pseudomonas putida TOD102: evaluation of the metabolic flux dilution model.

Nanh Lovanh1, Pedro J J Alvarez.   

Abstract

The reporter strain Pseudomonas putida TOD102 (with a tod-lux fusion) was used in chemostat experiments with binary substrate mixtures to investigate the effect of potentially occurring cosubstrates on toluene degradation activity. Although toluene was simultaneously utilized with other cosubstrates, its metabolic flux (defined as the toluene utilization rate per cell) decreased with increasing influent concentrations of ethanol, acetate, or phenol. Three inhibitory mechanisms were considered to explain these trends: (1) repression of the tod gene (coding for toluene dioxygenase) by acetate and ethanol, which was quantified by a decrease in specific bioluminescence; (2) competitive inhibition of toluene dioxygenase by phenol; and (3) metabolic flux dilution (MFD) by all three cosubstrates. Based on experimental observations, MFD was modeled without any fitting parameters by assuming that the metabolic flux of a substrate in a mixture is proportional to its relative availability (expressed as a fraction of the influent total organic carbon). Thus, increasing concentrations of alternative carbon sources "dilute" the metabolic flux of toluene without necessarily repressing tod, as observed with phenol (a known tod inducer). For all cosubstrates, the MFD model slightly overpredicted 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 cosubstrate 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. Copyright 2004 Wiley Periodicals, Inc.

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Year:  2004        PMID: 15162456     DOI: 10.1002/bit.20090

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


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