Skip to main content
eScholarship
Open Access Publications from the University of California

Bioreactor microbial ecosystems for thiocyanate and cyanide degradation unravelled with genome-resolved metagenomics.

  • Author(s): Kantor, Rose S
  • van Zyl, A Wynand
  • van Hille, Robert P
  • Thomas, Brian C
  • Harrison, Susan TL
  • Banfield, Jillian F
  • et al.
Abstract

Gold ore processing uses cyanide (CN(-) ), which often results in large volumes of thiocyanate- (SCN(-) ) contaminated wastewater requiring treatment. Microbial communities can degrade SCN(-) and CN(-) , but little is known about their membership and metabolic potential. Microbial-based remediation strategies will benefit from an ecological understanding of organisms involved in the breakdown of SCN(-) and CN(-) into sulfur, carbon and nitrogen compounds. We performed metagenomic analysis of samples from two laboratory-scale bioreactors used to study SCN(-) and CN(-) degradation. Community analysis revealed the dominance of Thiobacillus spp., whose genomes harbour a previously unreported operon for SCN(-) degradation. Genome-based 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 sulfur compounds produced during SCN(-) degradation. Heterotrophs, including a bacterium from a previously uncharacterized phylum, compose a smaller portion of the reactor community. Predation by phage and eukaryotes is predicted to affect community dynamics. Genes for ammonium oxidation and denitrification were detected, indicating the potential for nitrogen removal, as required for complete remediation of wastewater. These findings suggest optimization strategies for reactor design, such as improved aerobic/anaerobic partitioning and elimination of organic carbon from reactor feed.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
Current View