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Parameter estimation for models of ligninolytic and cellulolytic enzyme kinetics

While soil enzymes have been explicitly included in the soil organic carbon (SOC) decomposition models, there is a serious lack of suitable data for model parameterization. This study provides well-documented enzymatic parameters for application in enzyme-driven SOC decomposition models from a compilation and analysis of published measurements. In particular, we developed appropriate kinetic parameters for five typical ligninolytic and cellulolytic enzymes (b-glucosidase, cellobiohydrolase, endo-glucanase, peroxidase, and phenol oxidase). The kinetic parameters included the maximum specific enzyme activity (Vmax) and half-saturation constant (Km) in the MichaeliseMenten equation. The activation energy (Ea) and the pH optimum and sensitivity (pHopt and pHsen) were also analyzed. pHsen was estimated by fitting an exponential-quadratic function. The Vmax values, often presented in different units under various measurement conditions, were converted into the same units at a reference temperature (20 C) and pHopt. Major conclusions are: (i) Both Vmax and Km were log-normal distributed, with no significant difference in Vmax exhibited between enzymes originating from bacteria or fungi. (ii) No significant difference in Vmax was found between cellulases and ligninases; however, there was significant difference in Km between them. (iii) Ligninases had higher Ea values and lower pHopt than cellulases; average ratio of pHsen to pHopt ranged 0.3e0.4 for the five enzymes, which means that an increase or decrease of 1.1e1.7 pH units from pHopt would reduce Vmax by 50%. (iv) Our analysis indicated that the Vmax values from lab measurements with purified enzymes were 1e2 orders of magnitude higher than those for use in SOC decomposition models under field conditions.

Author(s)
Gangsheng Wang
Contact Person
Gangsheng Wang
Contact Organization
ORNL, Environmental Sciences Division
Contact Phone
Contact Email
Bioenergy Category
Publication Date
DOI
10.1016/j.soilbio.2012.01.011
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 Wang_Enzymes_SBB_2012.pdf 617.39 KB