Advanced bioremediation by an amalgamation of nanotechnology and modern artificial intelligence for efficient restoration of crude petroleum oil-contaminated sites: a prospective study

Investigating PCB degradation by indigenous fungal strains isolated from the transformer oil-contaminated site: degradation kinetics, Bayesian network, artificial neural networks, QSAR with DFT, molecular docking, and molecular dynamics simulation

The widespread prevalence of polychlorinated biphenyls (PCBs) in the environment has raised major concerns due to the associated risks to human health, wildlife, and ecological systems. Here, we investigated the degradation kinetics, Bayesian network (BN), quantitative structure-activity relationship-density functional theory (QSAR-DFT), artificial neural network (ANN), molecular docking (MD), and molecular dynamics stimulation (MS) of PCB biodegradation, i.e., PCB-10, PCB-28, PCB-52, PCB-138, PCB-153, and PCB-180 in the soil system using fungi isolated from the transformer oil-contaminated sites. Results revealed that the efficacy of PCB biodegradation best fits the first-order kinetics (R2 ≥ 0.93). The consortium treatment (29.44-74.49%) exhibited more efficient degradation of PCBs than those of Aspergillus tamarii sp. MN69 (27.09-71.25%), Corynespora cassiicola sp. MN69 (23.76-57.37%), and Corynespora cassiicola sp. MN70 (23.09-54.98%). 3'-Methoxy-2, 4, 4'-trichloro-biphenyl as an intermediate derivative was detected in the fungal consortium treatment. The BN analysis predicted that the biodegradation efficiency of PCBs ranged from 11.6 to 72.9%. The ANN approach showed the importance of chemical descriptors in decreasing order, i.e., LUMO > MW > IP > polarity no. > no. of chlorine > Wiener index > Zagreb index > HOMU > Pogliani index > APE in PCB removal. Furthermore, the QSAR-DFT model between the chemical descriptors and rate constant (log K) exhibited a high fit and good robustness of R2 = 99.12% in predicting ability. The MD and MS analyses showed the lowest binding energy through normal mode analysis (NMA), implying stability in the interactions of the docked complexes. These findings provide crucial insights for devising strategies focused on natural attenuation, holding substantial potential for mitigating PCB contamination within the environment.

Combined exposure of PVC-microplastic and mercury chloride (HgCl2) in sorghum (Pennisetum glaucum L.) when its seeds are primed titanium dioxide nanoparticles (TiO2-NPs)

The present work studied the impact of different levels of PVC-microplastics (PVC-MPs), namely 0 (no PVC-MPs), 2, and 4 mg L-1, along with mercury (Hg) levels of 0 (no Hg), 10, and 25 mg kg-1 in the soil, while concurrently applying titanium dioxide-nanoparticles (TiO2-NPs) at 0 (no TiO2-NPs), 50, and 100 µg mL-1 to sorghum (Pennisetum glaucum L.) plants. This study aimed to examine plant growth and biomass, photosynthetic pigments and gas exchange characteristics, oxidative stress indicators, and the response of various antioxidants (enzymatic and non-enzymatic) and their specific gene expression, proline metabolism, the AsA-GSH cycle, and cellular fractionation in the plants. The research outcomes indicated that elevated levels of PVC-MPs and Hg stress in the soil notably reduced plant growth and biomass, photosynthetic pigments, and gas exchange attributes. However, PVC-MPs and Hg stress also induced oxidative stress in the roots and shoots of the plants by increasing malondialdehyde (MDA), hydrogen peroxide (H2O2), and electrolyte leakage (EL) which also induced increased compounds of various enzymatic and non-enzymatic antioxidants and also the gene expression and sugar content. Furthermore, a significant increase in proline metabolism, the AsA-GSH cycle, and the pigmentation of cellular components was observed. Although, the application of TiO2-NPs showed a significant increase in plant growth and biomass, gas exchange characteristics, enzymatic and non-enzymatic compounds, and their gene expression and also decreased oxidative stress. In addition, the application of TiO2-NPs enhanced cellular fractionation and decreased the proline metabolism and AsA-GSH cycle in P. glaucum plants. These results open new insights for sustainable agriculture practices and hold immense promise in addressing the pressing challenges of heavy metal contamination in agricultural soils.

Soil Microbiome in Conditions of Oil Pollution of Subarctic Ecosystems

The present study aimed to investigate the recovery of soil quality and the bacterial and fungal communities following various recultivation methods in areas contaminated with oil. Oil spills are known to have severe impacts on ecosystems; thus, the restoration of contaminated soils has become a significant challenge nowadays. The study was conducted in the forest-tundra zone of the European North-East, where 39 soil samples from five oil-contaminated sites and reference sites were subjected to metagenomic analyses. The contaminated sites were treated with different biopreparations, and the recovery of soil quality and microbial communities were analyzed. The analysis of bacteria and fungi communities was carried out using 16S rDNA and ITS metabarcoding. It was found that 68% of bacterial OTUs and 64% of fungal OTUs were unique to the reference plot and not registered in any of the recultivated plots. However, the species diversity of recultivated sites was similar, with 50-80% of bacterial OTUs and 44-60% of fungal OTUs being common to all sites. New data obtained through soil metabarcoding confirm our earlier conclusions about the effectiveness of using biopreparations with indigenous oil-oxidizing micro-organisms also with mineral fertilizers, and herbaceous plant seeds for soil remediation. It is possible that the characteristics of microbial communities will be informative in the bioindication of soils reclaimed after oil pollution.