Kinetic parameters of phosphatase: A quantitative synthesis

Background/Question/Methods

Phosphatases play an important role in mineralization of organic phosphorus, soil phosphorus availability and global phosphorus cycling. Release of phosphorus in different ecosystems is important for plant growth and microbial function, and may be simulated by modeling organic phosphate mineralization. The half-saturation constant (K_m) and the maximum enzyme activity (V_max) in the Michaelis-Menten equation are the two important kinetic parameters in these models, but their values have not been systematically investigated. In this study, we compiled a database of kinetic parameters of phosphatase from 139 publications, estimated the means, variations and distributions of the kinetic parameters, and tested the differences in kinetic parameters of phosphatases of different types, origins and under different incubation conditions. We also analyzed the activation energy (Ea), temperature sensitivity (Q₁₀), optimum pH (pH_opt) and sensitivity of pH (pH_sen) of phosphatase activity. 

Results/Conclusions

Our results indicated that: 1) Both V_max and K_m were log-normal distributed with large variations; 2) There was no significant difference in K_m between the acid or alkaline phosphatases, but a significantly higher V_max for acid phosphatases was found compared with alkaline phosphatases; 3) K_m and V_max varied with the origins of enzymes and under different incubation conditions. Plant originated enzymes had the highest V_max while soil originated enzymes had the lowest V_max. Larger variation in V_max was found among the incubation times than among the incubation temperatures; 4) The mean values of E_a for acid and alkaline phosphatases were 36.30 and 23.61 KJ mol^-1, respectively, with an overall mean of 34.40 KJ mol^-1. The mean value of estimated pH_opt for acid phosphatase was 5.2 while that for alkaline phosphatase was 9.5. The information generated in this study will be useful for phosphorus mineralization modeling and uncertainty analysis.