Arsenic pollution remediation mechanism and preliminary application of arsenic-oxidizing bacteria isolated from industrial wastewater

Reduction of Toxic Metal Ions and Production of Bioelectricity through Microbial Fuel Cells Using Bacillus marisflavi as a Biocatalyst

Industrialization has brought many environmental problems since its expansion, including heavy metal contamination in water used for agricultural irrigation. This research uses microbial fuel cell technology to generate bioelectricity and remove arsenic, copper, and iron, using contaminated agricultural water as a substrate and Bacillus marisflavi as a biocatalyst. The results obtained for electrical potential and current were 0.798 V and 3.519 mA, respectively, on the sixth day of operation and the pH value was 6.54 with an EC equal to 198.72 mS/cm, with a removal of 99.08, 56.08, and 91.39% of the concentrations of As, Cu, and Fe, respectively, obtained in 72 h. Likewise, total nitrogen concentrations, organic carbon, loss on ignition, dissolved organic carbon, and chemical oxygen demand were reduced by 69.047, 86.922, 85.378, 88.458, and 90.771%, respectively. At the same time, the PDMAX shown was 376.20 ± 15.478 mW/cm2, with a calculated internal resistance of 42.550 ± 12.353 Ω. This technique presents an essential advance in overcoming existing technical barriers because the engineered microbial fuel cells are accessible and scalable. It will generate important value by naturally reducing toxic metals and electrical energy, producing electric currents in a sustainable and affordable way.

Contrasting response strategies of sulfate-reducing bacteria in a microbial consortium to As3+ stress under anaerobic and aerobic environments

The sulfate-reducing efficiency of sulfate-reducing bacteria (SRB) is strongly influenced by the presence of oxygen, but little is known about the oxygen tolerance mechanism of SRB and the effect of oxygen on the metalliferous immobilization by SRB. The performance evaluation, identification of bioprecipitates, and microbial and metabolic process analyses were used here to investigate the As3+ immobilization mechanisms and survival strategies of the SRB1 consortium under different oxygen-containing environments. Results indicated that the sulfate reduction efficiency was significantly decreased under aerobic (47.37%) compared with anaerobic conditions (66.72%). SEM analysis showed that under anaerobic and aerobic conditions, the morphologies of mineral particles were different, whereas XRD and XPS analyses showed that the most of As3+ bioprecipitates under both conditions were arsenic minerals such as AsS and As4S4. The abundances of Clostridium_sensu_stricto_1, Desulfovibrio, and Thiomonas anaerobic bacteria were significantly higher under anaerobic than aerobic conditions, whereas the aerobic Pseudomonas showed an opposite trend. Network analysis revealed that Desulfovibrio was positively correlated with Pseudomonas. Metabolic process analysis confirmed that under aerobic conditions the SRB1 consortium generated additional extracellular polymeric substances (rich in functionalities such as Fe-O, SO, CO, and -OH) and the anti-oxidative enzyme superoxide dismutase to resist As3+ stress and oxygen toxicity. New insights are provided here into the oxygen tolerance and detoxification mechanism of SRB and provide a basis for the future remediation of heavy metal(loid)-contaminated environments.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Analysis and pollution evaluation of heavy metal content in soil of the Yellow River Wetland Reserve in Henan

Objective

This study aims to assess the contamination levels of six heavy metals, namely arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), and lead (Pb), in the soil of the Henan Yellow River Wetland Reserve. It seeks to reveal the spatial distribution and trends of heavy metal pollution, providing a scientific basis for the rational utilization and effective protection of soil. Additionally, it aims to propose targeted management and remediation recommendations to mitigate or prevent soil pollution.

Method

A total of 706 soil samples were collected in this area in combination with the land use type map. As and Hg were determined by atomic fluorescence spectrometry, and Cr, Cu, Pb and Cd were determined by inductively coupled plasma mass spectrometry. Taking the soil pollution risk screening value of agricultural land (GB15618-2018) as a reference value, the sample data were statistically analyzed, and the Nemerow comprehensive pollution index method combined with ArcGIS technology was used to evaluate the soil environmental quality.

Result

The comprehensive pollution index of the soil in the Yellow River Wetland Reserve was 0.42, ranging from 0.17 to 2.38, which was safe and not polluted (I grade). Out of 706 sampling locations, 674 remained uncontaminated, while 26 exhibited cleanliness. Although they were in the warning line, they did not exceed the standard, accounting for 3.68% of the total number of sampling points. Five sample points were slightly polluted, accounting for 0.71% of the total sample points, and one sample point was moderately polluted, accounting for 0.14% of the total sample points. It can be seen that there are few agricultural land pollution points in the Yellow River Wetland Reserve, and the soil environment quality is generally good.

Conclusion

The soil in the Yellow River Wetland Reserve in Henan has a very small amount of mild and moderate pollution, and there is no severe pollution. The cleanliness is currently high.

Rapid arsenite oxidation by Paenarthrobacter nicotinovorans strain SSBW5: unravelling the role of GlpF, aioAB and aioE genes

A novel arsenite resistant bacterial strain SSBW5 was isolated from the battery waste site of Corlim, Goa, India. This strain interestingly exhibited rapid arsenite oxidation with an accumulation of 5 mM arsenate within 24 h and a minimum inhibitory concentration (MIC) of 18 mM. The strain SSBW5 was identified as Paenarthrobacter nicotinovorans using 16S rDNA sequence analysis. Fourier-transformed infrared (FTIR) spectroscopy of arsenite-exposed cells revealed the interaction of arsenite with several important functional groups present on the cell surface, possibly involved in the resistance mechanism. Interestingly, the whole genome sequence analysis also clearly elucidated the presence of genes, such as GlpF, aioAB and aioE encoding transporter, arsenite oxidase and oxidoreductase enzyme, respectively, conferring their role in arsenite resistance. Furthermore, this strain also revealed the presence of several other genes conferring resistance to various metals, drugs, antibiotics and disinfectants. Further suggesting the probable direct or indirect involvement of these genes in the detoxification of arsenite thereby increasing its tolerance limit. In addition, clumping of bacterial cells was observed through microscopic analysis which could also be a strategy to reduce arsenite toxicity thus indicating the existence of multiple resistance mechanisms in strain SSBW5. In the present communication, we are reporting for the first time the potential of P. nicotinovorans strain SSBW5 to be used in the bioremediation of arsenite via arsenite oxidation along with other toxic metals and metalloids.