Biokinetic models for representing the complete inhibition of microbial activity at high substrate concentrations.
This paper reintroduces the Wayman and Tseng model for representing substrate inhibition effects on specific growth rate by further documenting its potential predictive capabilities. It also introduces a modification to this model in which an Andrews inhibition function is used in place of the Monod noninhibitory substrate function. This modification better represents the relationship between specific growth rate and substrate concentration for those substrates that show Andrews type inhibition at lower substrate concentrations, rather than the Monod type noninhibitory behavior described in the model of Wayman and Tseng. Results from nonlinear, least squares regression analysis are used to evaluate the ability of these models to empirically represent experimental data (both new and from the literature). The statistical goodness of fit is evaluated by comparing the regression results against those obtained using other empirical models. Finally, possible mechanisms of toxicity responsible for the observed inhibition trends are used to further justify use of these empirical models. The dominant mechanism considered to be relevant for conceptually explaining complete inhibition at high concentrations of solvents is the deterioration of cell membrane integrity. Literature citations are used to support this argument. This work should lead to improvements in the mathematical modeling of contaminant fate and transport in the environment and in the simulation of microbial growth and organic compound biodegradation in engineered systems.
Alagappan
G
G
Department of Environmental Sciences, 14 College Farm Road, Cook College, Rutgers--The State University of New Jersey, New Brunswick, NJ 08901, USA.
Cowan
R M
RM
D019117:Burkholderia / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism*; D003198:Computer Simulation; D007700:Kinetics; D008433:Mathematics; D010101:Oxygen Consumption / Q000187:drug effects; D016958:Pseudomonas putida / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism*; D012044:Regression Analysis; D014050:Toluene / Q000494:pharmacology*
D014050:Toluene