collection date | 2014-01-29 |
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broad-scale environmental context | Engineered |
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local-scale environmental context | Engineered |
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environmental medium | Engineered |
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geographic location | South Africa |
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investigation type | metagenome-assembled genome |
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isolation source | metagenome |
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project name | Gold mining and other industrial activities make extensive use of cyanide (CN-) and produce large volumes of thiocyanate- (SCN-) contaminated wastewater that must be treated before reuse in mining processes. Furthermore, contaminated wastewater stored in tailings dams may pose an environmental threat through the potential for leakage into local groundwater. Microbial communities are often used for biodegradation and environmental remediation, however, little is known about the membership and metabolic potential of SCN-degrading consortia. Application and improvement of the remediation strategy will benefit from an understanding of organisms that can contribute to the breakdown of SCN- into sulfur, carbon and nitrogen compounds. To this end, we performed metagenomic analysis of samples from two laboratory-scale bioreactors used to study SCN- and CN- degradation by established microbial consortia. Community analysis revealed the dominance of Thiobacillus spp. whose genomes harbor a previously unreported operon for SCN- degradation. Metabolic predictions suggest that a large portion of each bioreactor community is autotrophic, relying not on molasses in reactor feed, but using energy gained from oxidation of the sulfur compounds produced during SCN- degradation. Heterotrophs compose a smaller portion of the reactor bacterial community, and predation by phage and eukaryotes is predicted to affect community dynamics. Furthermore, genes for ammonium oxidation and denitrification were detected, possibly allowing removal of nitrogen as required for complete remediation of wastewater. These findings suggest possible optimization strategies for reactor design such as improved aerobic/anaerobic partitioning and elimination of organic carbon from reactor feed. |
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sample name | SRR3901701_bin.43_CONCOCT_v1.1_MAG |
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ENA-CHECKLIST | ERC000047 |
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ENA-FIRST-PUBLIC | 2023-01-03 |
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ENA-LAST-UPDATE | 2023-01-03 |
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External Id | SAMEA14081930 |
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INSDC center alias | EBI |
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INSDC center name | European Bioinformatics Institute |
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INSDC first public | 2023-01-03T00:32:23Z |
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INSDC last update | 2023-01-03T00:32:23Z |
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INSDC status | public |
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Submitter Id | SRR3901701_bin.43_CONCOCT_v1.1_MAG |
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assembly quality | Many fragments with little to no review of assembly other than reporting of standard assembly statistics |
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assembly software | metaspadesv3.12.0 |
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binning parameters | Default |
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binning software | CONCOCT v1.1 |
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broker name | EMG broker account, EMBL-EBI |
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completeness score | 65.79 |
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completeness software | CheckM |
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contamination score | 1.75 |
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geographic location (latitude) | -33.9575 |
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geographic location (longitude) | 18.4606 |
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metagenomic source | metagenome |
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sample derived from | SAMN05389816 |
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scientific_name | uncultured Rhizobium sp. |
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sequencing method | Illumina HiSeq 2500 |
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taxonomic identity marker | multi-marker approach |
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