Heavy metals contaminate the environment and provide a threat to public health through drinking water and food chain. Microbial biosorption technology provides a more economical and competitive solution for bioremediation of toxicants such as heavy metals, and microbial genetic modification may modify microbes towards optimal sorption. It is very important to screen suitable strains for this purpose. In this study, three different types of microorganisms Escherichia coli, Bacillus subtilis and Saccharomyces cerevisiae were isolated and identified, from uncontaminated soils, and compared their sorption differences with respect to cadmium (Cd2+). We evaluated the effects of contact time and initial concentration on Cd2+ uptake, and found pseudo-second-order kinetic models were more suitable to describe biosorption processes. Adsorption isotherms were used to reflect their biosorption capacity. The maximum biosorption capacities of three strains calculated by the Langmuir model were 37.764, 56.497, and 22.437 mg Cd/g biomass, respectively. In bacteria, Cd2+ biosorption mainly occurred on cell wall, while the difference in biosorption between yeast inside and outside the cell was not significant. We found that due to the structural differences, the removal rate of E. coli surface decreased at a high concentration, while S. cerevisiae still had a lower biosorption capacity. FTIR spectroscopy reflected the difference in functional groups involved in biosorption by three strains. SEM-EDS analysis showed the binding of Cd2+ to microorganisms mainly relied on ion exchange mechanism. Based on the above results, we suggested that B. subtilis is more suitable to get genetically modified for heavy metal biosorption.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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