Cometabolism of chlorinated solvents and binary chlorinated solvent mixtures using M. trichosporium OB3b PP358.
The mutant methanotroph, Methylosinus trichosporium OB3b PP358, which constitutively expresses soluble methane monooxygenase (sMMO), was used to study the degradation kinetics of individual chlorinated solvents and binary solvent mixtures. Although sMMO's broad specificity permits a wide range of chlorinated solvents to be degraded, it creates the potential for competitive inhibition of degradation rates in mixtures because multiple chemicals are simultaneously available to the enzyme. To effectively design both ex-situ and in-situ groundwater bioremediation systems using strain PP358, kinetic parameters for chlorinated solvent degradation and accurate kinetic expressions to account for inhibition in mixtures are required. Toward this end, the degradation parameters for six prevalent chlorinated solvents and the verification of enzyme competition model for binary mixtures were the focus of this investigation. M. trichosporium OB3b PP358 degraded trichloroethylene (TCE), chloroform, cis-1,2-dichloroethylene (c-DCE), trans-1,2-dichloroethylene (t-DCE), and 1, 1-dichloroethylene (1,1-DCE) rapidly, with maximum substrate transformation rates of >20.8, 3.1, 9.5 24.8, and >7.5 mg/mg-day, respectively. 1,1,1-trichloroethane (TCA) was not significantly degraded. Half-saturation coefficients ranged from 1 to greater than 10 mg/L. Competition experiments were carried out to observe the effect of a second solvent on degradation rates and to verify the applicability of the Monod model adjusted for competitive inhibition. Binary mixtures of 0.3->0.5 mg/L TCE with up to 5 mg/L c-DCE and up to 7 mg/L 1,1,1-TCA were studied with 20 mM of formate and no growth substrate. No competition was observed at any of these concentrations. Additional competition experiments, using binary mixtures of t-DCE with TCE and t-DCE with c-DCE, were conducted at higher concentrations (i.e., 7-18 mg/L) and enzyme competition was observed. Predictions from a competitive inhibition model compared well with experimental data for these mixtures.
Aziz
C E
CE
Department of Civil Engineering, University of Texas at Austin, Austin, Texas 78712, USA.
Georgiou
G
G
Speitel
G E
GE
D001419:Bacteria / Q000235:genetics / Q000378:metabolism*; D001673:Biodegradation, Environmental; D001709:Biotechnology; D004000:Dichloroethylenes / Q000737:chemistry / Q000378:metabolism; D006843:Hydrocarbons, Chlorinated / Q000378:metabolism*; D007700:Kinetics; D008954:Models, Biological; D009154:Mutation; D010105:Oxygenases / Q000235:genetics / Q000378:metabolism; D012997:Solvents / Q000378:metabolism*; D013237:Stereoisomerism; D014240:Trichloroethanes / Q000378:metabolism; D014241:Trichloroethylene / Q000378:metabolism; D014874:Water Pollutants, Chemical / Q000378:metabolism
D004000:Dichloroethylenes; D006843:Hydrocarbons, Chlorinated; D012997:Solvents; D014240:Trichloroethanes; D014874:Water Pollutants, Chemical; C024566:1,1,1-trichloroethane; C029297:vinylidene chloride; D014241:Trichloroethylene; D010105:Oxygenases; C021555:methane monooxygenase; C035384:1,2-dichloroethylene