16S rRNA molecular profiling of heavy metal tolerant bacterial communities isolated from soil contaminated by electronic waste

Unlocking soil revival: the role of sulfate-reducing bacteria in mitigating heavy metal contamination

Soil contamination with heavy metals from industrial and mining activities poses significant environmental and public health risks, necessitating effective remediation strategies. This review examines the utilization of sulfate-reducing bacteria (SRB) for bioremediation of heavy metal-contaminated soils. Specifically, it focuses on SRB metabolic pathways for heavy metal immobilization, interactions with other microorganisms, and integration with complementary remediation techniques such as soil amendments and phytoremediation. We explore the mechanisms of SRB action, their synergistic relationships within soil ecosystems, and the effectiveness of combined remediation approaches. Our findings indicate that SRB can effectively immobilize heavy metals by converting sulfate to sulfide, forming stable metal sulfides, thereby reducing the bioavailability and toxicity of heavy metals. Nevertheless, challenges persist, including the need to optimize environmental conditions for SRB activity, address their sensitivity to acidic conditions and high heavy metal concentrations, and mitigate the risk of secondary pollution from excessive carbon sources. This study underscores the necessity for innovative and sustainable SRB-based bioremediation strategies that integrate multiple techniques to address the complex issue of heavy metal soil contamination. Such advancements are crucial for promoting green mining practices and environmental restoration.

Assessment of heavy metals at mangrove ecosystem, applying multiple approaches using in-situ and remote sensing techniques, Red Sea, Egypt

Mangrove areas are considered the most retention zone for heavy metal pollution as it work as an edge that aggregates land and sea sediments. This study aims to examine if the heavy metals' existence in the mangrove sediment is related to contamination or natural resources. In addition, it gives an interpretation of the origin of these metals along the Egyptian Red Sea coast. Twenty-two samples of mangrove sediments were collected and then, analyzed for metals (Mn, Ni, Cu, Fe, Cd, Ag, and Pb) using inductively coupled plasma mass spectroscopy (ICP-MS). Integration between the in-situ data, contamination indices, and remote sensing and geographical information science (GIS), and multivariate statistical analysis techniques (PCA) were analyzed to assess and clarify the spatial origin of heavy metals in sediment at a regional scale. The average concentration of heavy metals from mangrove sediments were shown to be substantially lower than the referenced value, ranging from moderate to significant except the levels of Ag were very high. The heavy metals concentrations were expected to be naturally origin rather than anthropogenic and that be confirmed by mapping of Red Sea alteration zones spots. These alteration zones are parallel to mangrove sites and rich by several mineralization types including heavy metals that are carried by flooding to the coastline. Remote sensing and GIS techniques successfully contributed to interpreting the pattern of the origin of heavy metals and discharging systems that control the heavy metals concentration along the Red Sea coast.

Assessment of Heavy Metals at Mangrove Ecosystem, Applying Multiple Approaches using in-situ and Remote Sensing Techniques, Red Sea, Egypt.. [DOI: 10.21203/rs.3.rs-2581939/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Heavy metal pollution is one of the threats that impact on Mangrove ecosystem. This study aims to examine if the heavy metals in the mangrove sediment contamination status along the Red Sea coast, and give an interpretation of the origin of these metals. Twenty-two samples were collected and then, analyzed for metals (Mn, Ni, Cu, Fe, Cd, Ag, and Pb) using Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). Integration between the in-situ data, contamination indices, and remote sensing and geographical information science (GIS), and multivariate statistical analysis techniques (PCA) to assess and clarify the spatial origin of heavy metals in sediment at a regional scale. The average concentration is shown to be substantially lower than the referenced value. The heavy metals are naturally origin not anthropogenic origin and, ranging from moderate to significant except the levels of Ag were very high. According to Ag levels, should be exploited economically. Remote sensing and GIS technique successfully contributed to interpreting the pattern of the origin of heavy metals and discharging systems along the red sea coast.

Cadmium phytoremediation potential of Deenanath grass (Pennisetum pedicellatum) and the assessment of bacterial communities in the rhizospheric soil

Phytoremediation technology is gaining excessive consideration as a promising method for heavy metal remediation from contaminated soil. In the present research study, a greenhouse trial was performed to assess the proficiency of Pennisetum pedicellatum as a potential plant species for the remediation of cadmium from the soil. Four sets of treatments i.e., (T_o) control, (T₁) 25 ppm, (T₂) 50 ppm, and (T₃) 100 ppm were studied till 60 days. Soil and plant samples were collected at a regular interval of 15 days after the seed sowing and analysed for different physicochemical properties and Cd concentrations from each treatment. The cadmium uptake was studied in the roots and shoots independently to examine the cadmium accumulation in P. pedicellatum. The present study showed that P. pedicellatum accumulated cadmium mostly in their roots compared to the shoots resulting in the accumulation of Cd from the soil. The finding indicates that P. pedicellatum is a virtuous plant species to restore cadmium-contaminated soil. It effectively banished 83% of Cd from the 100 ppm spiked soil at the end of 60 days. The microbial characterization of rhizospheric soil was also done using serial dilution and spread plate procedures to determine the presence of bacterial species in the rhizospheric soil. Seven bacterial strains were isolated from the soil and were further assessed for their biochemical, molecular, and phylogenic characteristics. The 16S rRNA sequencing analysis confirmed the presence of different bacterial species such as Alcaligenes sp., Bacillus drentensis, Bacillus subtilis, Bacillus foraminis, Bacillus wudalianchiensis, Bacillus amyloliquefaciens, and Planococcus ruber. This study concluded that phytoremediation using P. pedicellatum is a fascinating and compelling green technology for the remediation of cadmium from soil.

Monitoring and molecular characterization of bacterial species in heavy metals contaminated roadside soil of selected region along NH 8A, Gujarat

Heavy metal contamination is a universal concern due to health risks associated with metal pollution. Soil contamination by heavy metals is known to affect microbial activities at elevated concentrations adversely. However, indigenous soil bacterial populations' response to added heavy metal and metal combinations is poorly understood. Microbes prevailing in the soil are the driving factors. Their properties are recognized as sensitive indicators of soil quality and health. Moreover, these microscopic organisms are accountable for the fertility and aeration of the soil that forms fundamental aspects of soil function. The current study was performed to explore the diversity of bacterial species in heavy metal polluted roadside soil. The roadside soil samples were collected from diverse sites and processed for physicochemical properties, microbial characterization, and heavy metals distribution in the selected locations. Serial dilution and spread plate techniques were used for the isolation of bacterial species. The 16S-rRNA gene sequencing identified bacterial species in roadside soil as Bacillus drentensis (MK217088), Bacillus safensis (MK774729), Bacillus haynesii (MK192808), Bacillus subtilis (MK217089), and Bacillus cereus (MK801278). In addition, the 16S rRNA sequences of isolated bacterial strains were aligned to generate a phylogenetic tree. Thus, the current research study provides a platform for efficiently investigating roadside soils by microbial profiling that may discover novel microbes of scientific significance and improved potential.