Mohd Izuan Effendi Halmi

Kinetics of Molybdenum Reduction to Molybdenum Blue by Bacillus sp. Strain A.rzi

Molybdenum is very toxic to agricultural animals. Mo-reducing bacterium can be used to immobilize soluble molybdenum to insoluble forms, reducing its toxicity in the process. In this work the isolation of a novel molybdate-reducing Gram positive bacterium tentatively identified as Bacillus sp. strain A.rzi from a metal-contaminated soil is reported. The cellular reduction of molybdate to molybdenum blue occurred optimally at 4 mM phosphate, using 1% (w/v) glucose, 50 mM molybdate, between 28 and 30°C and at pH 7.3. The spectrum of the Mo-blue product showed a maximum peak at 865 nm and a shoulder at 700 nm. Inhibitors of bacterial electron transport system (ETS) such as rotenone, sodium azide, antimycin A, and potassium cyanide could not inhibit the molybdenum-reducing activity. At 0.1 mM, mercury, copper, cadmium, arsenic, lead, chromium, cobalt, and zinc showed strong inhibition on molybdate reduction by crude enzyme. The best model that fitted the experimental data well was Luong followed by Haldane and Monod. The calculated value for Luongs constants p max, K s, S m, and n was 5.88 μmole Mo-blue hr−1, 70.36 mM, 108.22 mM, and 0.74, respectively. The characteristics of this bacterium make it an ideal tool for bioremediation of molybdenum pollution.

Molybdenum reduction to molybdenum blue in Serratia sp. Strain DRY5 is catalyzed by a novel molybdenum-reducing enzyme.

The first purification of the Mo-reducing enzyme from Serratia sp. strain DRY5 that is responsible for molybdenum reduction to molybdenum blue in the bacterium is reported. The monomeric enzyme has an apparent molecular weight of 105 kDalton. The isoelectric point of this enzyme was 7.55. The enzyme has an optimum pH of 6.0 and maximum activity between 25 and 35°C. The Mo-reducing enzyme was extremely sensitive to temperatures above 50°C (between 54 and 70°C). A plot of initial rates against substrate concentrations at 15 mM 12-MP registered a V max for NADH at 12.0 nmole Mo blue/min/mg protein. The apparent K m for NADH was 0.79 mM. At 5 mM NADH, the apparent V max and apparent K m values for 12-MP of 12.05 nmole/min/mg protein and 3.87 mM, respectively, were obtained. The catalytic efficiency (k cat/K m) of the Mo-reducing enzyme was 5.47 M−1 s−1. The purification of this enzyme could probably help to solve the phenomenon of molybdenum reduction to molybdenum blue first reported in 1896 and would be useful for the understanding of the underlying mechanism in molybdenum bioremediation involving bioreduction.

Hexavalent Molybdenum Reduction to Mo-Blue by a Sodium-Dodecyl-Sulfate-Degrading Klebsiella oxytoca Strain DRY14

Bacteria with the ability to tolerate, remove, and/or degrade several xenobiotics simultaneously are urgently needed for remediation of polluted sites. A previously isolated bacterium with sodium dodecyl sulfate- (SDS-) degrading capacity was found to be able to reduce molybdenum to the nontoxic molybdenum blue. The optimal pH, carbon source, molybdate concentration, and temperature supporting molybdate reduction were pH 7.0, glucose at 1.5% (w/v), between 25 and 30 mM, and 25°C, respectively. The optimum phosphate concentration for molybdate reduction was 5 mM. The Mo-blue produced exhibits an absorption spectrum with a maximum peak at 865 nm and a shoulder at 700 nm. None of the respiratory inhibitors tested showed any inhibition to the molybdenum-reducing activity suggesting that the electron transport system of this bacterium is not the site of molybdenum reduction. Chromium, cadmium, silver, copper, mercury, and lead caused approximately 77, 65, 77, 89, 80, and 80% inhibition of the molybdenum-reducing activity, respectively. Ferrous and stannous ions markedly increased the activity of molybdenum-reducing activity in this bacterium. The maximum tolerable concentration of SDS as a cocontaminant was 3 g/L. The characteristics of this bacterium make it a suitable candidate for molybdenum bioremediation of sites cocontaminated with detergent pollutant.

Comparison of Microtox and Xenoassay light as a near real time river monitoring assay for heavy metals

Luminescence-based assays for toxicants such as Microtox, ToxAlert, and Biotox have been used extensively worldwide. However, the use of these assays in near real time conditions is limited due to nonoptimal assay temperature for the tropical climate. An isolate that exhibits a high luminescence activity in a broad range of temperatures was successfully isolated from the mackerel, Rastrelliger kanagurta. This isolate was tentatively identified as Photobacterium sp. strain MIE, based on partial 16S rDNA molecular phylogeny. Optimum conditions that support high bioluminescence activity occurred between 24 and 30°C, with pH 5.5 to 7.5, 10 to 20 g/L of sodium chloride, 30 to 50 g/L of tryptone, and 4 g/L of glycerol as the carbon source. Assessment of near real time capability of this bacterial system, Xenoassay light to monitor heavy metals from a contaminated river running through the Juru River Basin shows near real time capability with assaying time of less than 30 minutes per samples. Samples returned to the lab were tested with a standard Microtox assay using Vibrio fishceri. Similar results were obtained to Xenoassay light that show temporal variation of copper concentration. Thus, this strain is suitable for near real time river monitoring of toxicants especially in the tropics.

Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN)

ABSTRACT In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg−1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.