Bioreduction and mineralization of Cr(VI) by Sporosarcina saromensis W5 induced carbonate precipitation

Harnessing microbes for heavy metal remediation: mechanisms and prospects

Contamination by heavy metals (HMs) poses a significant threat to the ecosystem and its associated micro and macroorganisms, leading to ill effects on humans which necessitate the requirement of effective remediation strategies. Microbial remediation leverages the natural metabolic abilities of microbes to overcome heavy metal pollution effectively. Some of the mechanisms that aids in the removal of heavy metals includes bioaccumulation, biosorption, and biomineralization. Metals such as Cd, Pb, As, Hg, and Cr are passively adsorbed by energy independent process onto the surface by exopolysaccharide sequestration or utilizing energy to transfer metals into the cell and interact with the biomolecules to be sequestered, or being converted into its various valencies, thereby reducing the toxicity. Application of hyperaccumulators has shown to be effective in the removal of HMs especially while augmented with microbes to the rhizosphere region. Omics studies which include metabolomics and metagenomics provide significant information about the microbial diversities and metabolic processes involved in heavy metal remediation, allowing the development of more reliable and sustainable bioremediation approaches. This review also summarizes the recent advancements in microbial remediation, including genetic engineering and nanotechnology that has revolutionized and offered an unprecedented control and precision in the removal of HMs. These innovations hold a promising stand for enhancing remediation efficiency, scalability, and cost-effectiveness.

Exploring bio-remediation strategies by a novel bacteria Micrococcus sp. strain HX in Cr(VI)-contaminated groundwater from long-term industrial polluted

Hexavalent chromium (Cr(VI)) has emerged as a contaminant of heavy metal, owing to its wide use in industry. This study focuses on elucidating the interaction between microbial communities and environmental parameters in Cr(VI)-contaminated groundwater near a factory in Henan Province, and evaluating the bio-remediation potential of microorganisms toward Cr(VI) reduction. The highest concentration of Cr(VI) in the groundwater is 208.08 mg/L. The dominant microbes were Proteobacteria and Bacteroidota, closely positively related to Cr(VI) and SO42-. Many of these genus have been proven to be chromium tolerant or have the ability to reduce Cr(VI). Two strains, Micrococcus sp. HX and Bacillus sp. HX-2, were isolated from contaminated groundwater, and Micrococcus sp. HX was used for the first time to reduce Cr(VI) in groundwater. The reduced ability of HX reached 90.18 % at a Cr(VI) concentration of 100 mg/L, while HX-2 achieved a reduction capacity of 63.8 %. Micrococcus sp. HX shows the best reduction efficiency in alkaline environments (ph=8), which is close to the tannery industry wastewater. The reduction efficiency by Micrococcus sp. HX reached 67.26 % in groundwater samples (Cr(VI)= 26.08 mg/L). Transcriptome analyses revealed oxidoreductase activity, ATP binding and the NAD(P) binding region protein-related gene expression were up-regulated. Binding reduction experiments indicated that most of the Cr(III) was detected extracellular, which suggests that the reduction of Cr(VI) by HX was mainly extracellular enzyme-catalyzed.

Deep-sea microorganisms-driven V5+ and Cd2+ removal from vanadium smelting wastewater: Bacterial screening, performance and mechanism

The disorderly discharge of industrial wastewater containing heavy metals has caused serious water pollution and ecological environmental risks, ultimately threatening human life and health. Biological treatment methods have obvious advantages, but the existing microorganisms exhibit issues such as poor resistance, adaptability, colonization ability, and low activity. However, a wide variety of microorganisms in deep-sea hydrothermal vent areas are tolerant to heavy metals, possessing the potential for efficient treatment of heavy metal wastewater. Based on this, the study obtained a group of deep-sea microbial communities dominated by Burkholderia-Caballeronia-Paraburkholderia through shake flask experiments from the sediments of deep-sea hydrothermal vents, which can simultaneously achieve the synchronous removal of vanadium and cadmium heavy metals through bioreduction, biosorption, and biomineralization. Through SEM-EDS, XRD, XPS, and FT-IR analyses, it was found that V(V) was reduced to V(IV) through a reduction process and subsequently precipitated. Glucose oxidation accelerated this process. Cd(II) underwent biomineralization to form precipitates such as cadmium hydroxide and cadmium carbonate. Functional groups on the microbial cell surface, such as -CH2, C=O, N-H, -COOH, phosphate groups, amino groups, and M-O moieties, participated in the bioadsorption processes of V(V) and Cd(II) heavy metals. Under optimal conditions, namely a temperature of 40 °C, pH value of 7.5, inoculation amount of 10%, salinity of 4%, COD concentration of 600 mg/L, V5+ concentration of 300 mg/L, and Cd2+ concentration of 40 mg/L, the OD600 can reach its highest at 72 h, with the removal efficiency of V5+, Cd2+, and COD in simulated vanadium smelting wastewater reaching 86.32%, 59.13%, and 61.63%, respectively. This study provides theoretical insights and practical evidence for understanding the dynamic changes in microbial community structure under heavy metal stress, as well as the resistance mechanisms of microbial treatment of industrial heavy metal wastewater.

Molecular and geochemical basis of microbially induced carbonate precipitation for treating acid mine drainage: The case of a novel Sporosarcina genomospecies from mine tailings

Microbially induced carbonate precipitation (MICP) immobilizes toxic metals and reduces their bioavailability in aqueous systems. However, its application in the treatment of acid mine drainage (AMD) is poorly understood. In this study, the genomes of Sporosarcina sp. UB5 and UB10 were sequenced. Urease, carbonic anhydrases, and metal resistance genes were identified and enzymatic assays were performed for their validation. The geochemical mechanism of precipitation in AMD was elucidated through geo-mineralogical analysis. Sporosarcina sp. UB5 was shown to be a new genomospecies, with an average nucleotide identity < 95 % (ANI) and DNA-DNA hybridization < 70 % (DDH) whereas UB10 is close to S. pasteurii. UB5 contained two urease operons, whereas only one was identified in UB10. The ureolytic activities of UB5 and UB10 were 122.67 ± 15.74 and 131.70 ± 14.35 mM NH4+ min-1, respectively. Both strains feature several carbonic anhydrases of the α, β, or γ families, which catalyzed the precipitation of CaCO3. Only Sporosarcina sp. UB5 was able to immobilize metals and neutralize AMD. Geo-mineralogical analyses revealed that UB5 directly immobilized Fe (1-23 %), Mn (0.65-1.33 %) and Zn (0.8-3 %) in AMD via MICP and indirectly through adsorption to calcite and binding to bacterial cell walls. The MICP-treated AMD exhibited high removal rates (>67 %) for Ag, Al, As, Ca, Cd, Co, Cu, Fe, Mn, Pb, and Zn, and a removal rate of 15 % for Mg. This study provides new insights into the MICP process and its applications to AMD treatment using autochthonous strains.

β-tricalcium phosphate enhanced biomineralization of Cd2+ and Pb2+ by Sporosarcina ureilytica HJ1 and Sporosarcina pasteurii HJ2

Microbiologically induced CaCO3 precipitation (MICP) has been proposed as a potential bioremediation method to immobilize contaminating metals. In this study, carbonate mineralizing bacteria HJ1 and HJ2, isolated from heavy metal contaminated soil, was employed for Cd2+ and Pb2+ immobilization with or without β-tricalcium phosphate addition. Compared with the only treatments amended with strains, the combined application of β-tricalcium phosphate and HJ1 improved the immobilization rates of Cd and Pb by 1.49 and 1.70 times at 24 h, and the combined application of β-tricalcium phosphate and HJ2 increased the immobilization rates of Cd and Pb by 1.25 and 1.79 times. The characterization of biomineralization products revealed that Cd2+ and Pb2+ primarily immobilized from the liquid phase as CdCO3 and PbCO3, and the addition of β-tricalcium phosphate facilitated the formation of Ca4.03Cd0.97(PO4)3(OH) and Pb3(PO4)2. Also, the calcium source was related to the speciation of carbonate precipitation and improved the Cd and Pb remediation efficiency. This research demonstrated the feasibility and effectiveness of MICP combined with β-tricalcium phosphate in immobilization of Cd and Pb, which will provide a fundamental basis for future applications of MICP to mitigate soil heavy metal pollutions.

Two decades of research trends in microbial-induced carbonate precipitation for heavy metal removal: a bibliometric review and literature review

Amidst the increasing significance of innovative solutions for bioremediation of heavy metal removal, this paper offers a thorough bibliometric analysis of microbial-induced carbonate precipitation (MICP) for heavy metal removal, as a promising technology to tackle this urgent environmental issue. This study focused on articles published from 1999 to 2022 in the Scopus database. It assesses trends, participation, and key players within the MICP for heavy metal sequestration. Among the 930 identified articles, 74 countries participated in the field, with China being the most productive. Varenyam Achal, the Chinese Academy of Sciences, and Chemosphere are leaders in the research landscape. Using VOSviewer and R-Studio, keyword hotspots like "MICP", "urease", and "heavy metals" underscore the interdisciplinary nature of MICP research and its focus on addressing a wide array of environmental and soil-related challenges. VOSviewer emphasises essential terms like "calcium carbonate crystal", while R-Studio highlights ongoing themes such as "soil" and "organic" aspects. These analyses further showcase the interdisciplinary nature of MICP research, addressing a wide range of environmental challenges and indicating evolving trends in the field. This review also discusses the literature concerning the potential of MICP to immobilise contaminants, the evolution of the research outcome in the last two decades, MICP treatment techniques for heavy metal removal, and critical challenges when scaling from laboratory to field. Readers will find this analysis beneficial in gaining valuable insights into the evolving field and providing a solid foundation for future research and practical implementation.

Optimized kernel extreme learning machine using Sine Cosine Algorithm for prediction of unconfined compression strength of MICP cemented soil

Microbially induced calcite precipitation (MICP) is an eco-friendly bio-remediation technology. The unconfined compressive strength (UCS) of MICP cemented soil is an important indicator of repair effectiveness. This study proposes a machine learning technique utilizing the Sine Cosine Algorithm (SCA) to optimize the regularization coefficient C and kernel width γ of the kernel extreme learning machine (KELM) to predict the UCS of MICP cemented soil. To evaluate the performance of the proposed models, a dataset containing 180 groups of the UCS of MICP cemented soil was obtained. The results obtained by SCA-KELM were compared with those obtained by the Random Forest algorithm (RF), Support Vector Machine (SVM), and KELM. The performance of these models was evaluated by the scores of MAE, RMSE, and R2. The results indicate that the SCA-KELM algorithm exhibits optimal prediction performance (Total score: 21). After optimizing KELM with SCA, the total score improved by 110%, suggesting that SCA significantly enhances the KELM performance. After model development, the optimal population size for SCA-KELM was determined to be 50. Based on the mutual information test, an innovative method was developed for categorizing factor sensitivity by employing importance scores as the partitioning criterion. This method categorizes the influencing factors into three tiers: high (importance score: 8.03-11.14%), medium (importance score: 5.93-7.25%), and low (importance score: 3.23-5.18%). These results suggest that the proposed SCA-KELM algorithm can be regarded as a powerful tool for predicting the UCS of MICP cemented soil.