Vault packaged enzyme mediated degradation of amino-aromatic energetic compounds.

Amino-aromatic compounds, 2-amino-4-nitrotoluene (ANT), and 2,4-diaminotoluene (DAT) are carcinogens and environmentally persistent pollutants. In this study, we investigated their degradation by natural manganese peroxidase (nMnP) derived from Phanerochaete chrysosporium and recombinant manganese peroxidase packaged in vaults (vMnP). Encapsulation of manganese peroxidase (MnP) in ribonucleoprotein nanoparticle cages, called vaults, was achieved by creating recombinant vaults in yeast Pichia pastoris. Vault packaging increased the stability of MnP by locally sequestering multiple copies of the enzyme. Within 96  h, both vMnP and nMnP catalyzed over 72% removal of ANT in-vitro, which indicates that vault packaging did not limit substrate diffusion. It was observed that vMnP was more efficient than nMnP and P. chrysosporium for the catalysis of target contaminants. Only 57% of ANT was degraded by P. chrysosporium even when MnP activity reached about 480 U L-1 in cultures. At 1.5 U L-1 initial activity, vMnP achieved 38% of ANT and 51% of DAT degradation, whereas even 2.7 times higher activity of nMnP showed insignificant biodegradation of both compounds. These results imply that due to protection by vault cages, vMnP has lower inactivation rates. Thus, it works effectively at lower dosage for a longer duration compared to nMnP without requiring frequent replenishment. Collectively, these results indicate that fungal enzymes packaged in vault nanoparticles are more stable and active, and they would be effective in biodegradation of energetic compounds in industrial processes, waste treatment, and contaminated environments.

Development of model for prediction of Leachate Pollution Index (LPI) in absence of leachate parameters.

Leachate pollution index (LPI) is an environmental index which quantifies the pollution potential of leachate generated in landfill site. Calculation of Leachate pollution index (LPI) is based on concentration of 18 parameters present in leachate. However, in case of non-availability of all 18 parameters evaluation of actual values of LPI becomes difficult. In this study, a model has been developed to predict the actual values of LPI in case of partial availability of parameters. This model generates eleven equations that helps in determination of upper and lower limit of LPI. The geometric mean of these two values results in LPI value. Application of this model to three landfill site results in LPI value with an error of ±20% for ∑inwi⩾0.6.