Mechanism of Microbial Degradation of Slow-Release Fertilizers

Methyleneureas are condensation products of urea and formaldehyde of different molecular mass and solubility; they are used in large amounts both as resins, binders, and insulating materials for industrial applications, as well as a slow-release nitrogen fertilizer for greens, lawns, or in bioremediation processes. In the present study, the microbial breakdown of these products was investigated. The nitrogen was released as ammonia and urea, and the formaldehyde released immediately oxidized via formiate to carbon dioxide. The enzymatic mechanism of metabolization of methyleneureas was studied in microorganisms isolated from soil, which were able to use these compounds as the sole source of nitrogen for growth. A strain of the Gram-negative bacterium Ralstonia paucula (formerly Alcaligenes sp. CDC group IVc-2) completely degraded methylenediurea and dimethylenetriurea to urea, ammonia, formaldehyde, and carbon dioxide. The enzyme initiating this degradation (methylenediurease) was purified and turned out to be different from the previously described enzyme from Ochrobactrum anthropi with regard to its regulation of expression and physicobiochemical properties. Fungal degradation of methyleneureas may occur via the formation of organic acids, thus leading to a nonenzymatic degradation of methyleneureas, which are unstable under acidic conditions.     

Methodological scheme for designing the monitoring of genetically modified crops at the regional scale

According to EC regulations the deliberate release of genetically modified (GM) crops into the agro-environment needs to be accompanied by environmental monitoring to detect potential adverse effects, e.g.unacceptable levels of gene flow from GM to non-GM crops, or adverse effects on single species or species groups thus reducing biodiversity. There is, however, considerable scientific and public debate on how GM crops should be monitored with sufficient accuracy, discussing questions of potential adverse effects, agro-environmental variables or indicators to be monitored and respective detection methods; Another basic component, the appropriate number and location of monitoring sites, is hardly considered. Currently, no consistent GM crop monitoring approach combines these components systematically. This study focuses on and integrates spatial agro-environmental aspects at a landscape level in order to design monitoring networks. Based on examples of environmental variables associated with the cropping of Bt-Maize (Zea maize L.), herbicide-tolerant (HT) winter oilseed rape (Brassica napus L.), HT sugar beet (Beta vulgaris L.), and starch-modified potato (Solanum tuberosum L.), we develop a transferable framework and assessment scheme that comprises anticipated adverse environmental effects, variables to be measured and monitoring methods.These we integrate with a rule-based GIS (geographic information system) analysis, applying widely available spatial area and point information from existing environmental networks. This is used todevelop scenarios with optimised regional GM crop monitoring networks.