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Environ Sci Technol. 2017 Mar 7;51(5):2944-2953. doi: 10.1021/acs.est.6b04477. Epub 2017 Feb 13.

Genome-Resolved Meta-Omics Ties Microbial Dynamics to Process Performance in Biotechnology for Thiocyanate Degradation.

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Department of Plant and Microbial Biology, University of California , Berkeley, California 94720, United States.
Centre for Bioprocess Engineering Research, Department of Chemical Engineering, University of Cape Town , Rondebosch, 7701, South Africa.
Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States.
Graduate School of Genome Science and Technology, University of Tennessee , Knoxville, Tennessee 37996, United States.
Department of Earth and Planetary Sciences, University of California , Berkeley, California 94720, United States.
Joint Genome Institute , Walnut Creek, California 94598, United States.
Department of Environmental Science, Policy, and Management, University of California , Berkeley, California 94720, United States.


Remediation of industrial wastewater is important for preventing environmental contamination and enabling water reuse. Biological treatment for one industrial contaminant, thiocyanate (SCN-), relies upon microbial hydrolysis, but this process is sensitive to high loadings. To examine the activity and stability of a microbial community over increasing SCN- loadings, we established and operated a continuous-flow bioreactor fed increasing loadings of SCN-. A second reactor was fed ammonium sulfate to mimic breakdown products of SCN-. Biomass was sampled from both reactors for metagenomics and metaproteomics, yielding a set of genomes for 144 bacteria and one rotifer that constituted the abundant community in both reactors. We analyzed the metabolic potential and temporal dynamics of these organisms across the increasing loadings. In the SCN- reactor, Thiobacillus strains capable of SCN- degradation were highly abundant, whereas the ammonium sulfate reactor contained nitrifiers and heterotrophs capable of nitrate reduction. Key organisms in the SCN- reactor expressed proteins involved in SCN- degradation, sulfur oxidation, carbon fixation, and nitrogen removal. Lower performance at higher loadings was linked to changes in microbial community composition. This work provides an example of how meta-omics can increase our understanding of industrial wastewater treatment and inform iterative process design and development.

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