Chlorite Dismutase from perchlorate reducing bacteria. A potential biocatalyst to eliminate chlorinated species from polluted water resources and industrial wastes

Magnetospirillum (M.) sp. strain Lusitani, a perchlorate reducing bacteria (PRB), was previously isolated from a wastewater treatment plant and phylogenetic analysis was performed to classify the isolate. The DNA sequence of the genes responsible for perchlorate reduction and chlorite dismutation was determined and a model was designed based on the physiological roles of the proteins involved in the pcr-cld regulon. Chlorite dismutase (Cld) was purified from Magnetospirillum sp. strain Lusitani cells grown in anaerobiosis in the presence of perchlorate. The protein was purified up to electrophoretic grade using HPLC techniques as a 140 kDa homopentamer comprising five ~28 kDa monomers. Steady-state kinetic studies showed that the enzyme follows a Michaelis-Menten model with optimal pH and temperature of 6.0 and 5°C, respectively. The average values for the kinetic constants KM and Vmax were respectively 0.56 mM and 10.2 U, which correspond to a specific activity of 35470 U/mg and a turnover number of 16552 s-1. Cld from M. sp. strain Lusitani is inhibited by the product chloride, but not by dioxygen. Inhibition constants KiC= 460 mM and KiU= 480 mM indicated that sodium chloride is a weak mixed inhibitor of Cld, with a slightly stronger competitive character. The X-ray crystallography structure of M. sp. strain Lusitani Cld was solved at 3.0 Å resolution. In agreement with cofactor content biochemical analysis, the X-ray data showed that each Cld monomer harbors one heme b coordinated by a histidine residue (His188), hydrogen-bonded to a conserved glutamic acid residue (Glu238). The conserved neighboring arginine residue (Arg201) important for substrate positioning, was found in two different conformations in different monomers depending on the presence of the exogenous ligand thiocyanate. UV-Visible and CW-EPR spectroscopies were used to study the effect of redox agents, pH and exogenous ligands on the heme environment.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.