Soil enzyme kinetics indicate ecotoxicity of long-term arsenic pollution in the soil at field scale.

ABSTRACT

Information on the kinetic characteristics of soil enzymes under long-term arsenic (As) pollution in field soils is scarce. We investigated Michaelis-Menten kinetic properties of four soil enzymes including ß-glucosidase (BG), acid phosphatase (ACP), alkaline phosphatase (ALP), and dehydrogenase (DHA) in field soils contaminated by As resulting from long-term realgar mining activity. The kinetic parameters, namely the maximum reaction velocity (Vmax), enzyme-substrate affinity (Km) and catalytic efficiency (Vmax/Km) were calculated. Results revealed that the enzyme kinetic characteristics varied in soils and were significantly influenced by total nitrogen (N) and total As, which explained 31.8% and 30.7% of the variance in enzyme kinetics respectively. Enzyme pools (Vmax) and catalytic efficiency (Vmax/Km) of BG, ACP and DHA decreased with elevated As pollution, while the enzyme affinity for substrate (Km) was less affected. Redundancy analysis and stepwise regression suggested that the adverse influence of As on enzyme kinetics may offset or weakened by soil total N and soil organic matter (SOM). Concentration-response fitting revealed that the specific kinetic parameters expressed as the absolute enzyme kinetic parameters multiplied by normalized soil total N and SOM were more relevant than the absolute ones to soil total As. The arsenic ecological dose values that cause 10% decrease (ED10) in the specific enzyme kinetics were 20-49 mg kg-1, with a mean value of 35 mg kg-1, indicating a practical range of threshold for As contamination at field level. This study concluded that soil enzymes exhibited functional adaptation to long-term As stress mainly through the reduction of enzyme pools (Vmax) or maintenance of enzyme-substrate affinity (Km). Further, this study demonstrates that the specific enzyme kinetics are the better indicators of As ecotoxicity at field-scale compared with the absolute enzyme parameters.