The Microbial Community of a Passive Biochemical Reactor Treating Arsenic, Zinc, and Sulfate-Rich Seepage

Abstract

Sulfidogenic biochemical reactors (BCRs) for metal removal that use complex organic carbon have been shown to be effective in laboratory studies, but their performance in the field is highly variable. Successful operation depends on the types of microorganisms supported by the organic matrix, and factors affecting the community composition are unknown. A molecular survey of a field-based BCR that had been removing zinc and arsenic for over 6 years revealed that the microbial community was dominated by methanogens related to Methanocorpusculum sp. and Methanosarcina sp., which co-occurred with Bacteroidetes environmental groups, such as Vadin HA17, in places where the organic matter was more degraded. The metabolic potential for organic matter decomposition by Ruminococcaceae was prevalent in samples with more pyrolyzable carbon. Rhodobium- and Hyphomicrobium-related genera within the Rhizobiales order that have the metabolic potential for dark hydrogen fermentation and methylotrophy, and unclassified Comamonadaceae were the dominant Proteobacteria. The unclassified environmental group Sh765B-TzT-29 was an important Delta-Proteobacteria group in this BCR that co-occurred with the dominant Rhizobiales operational taxonomic units. Organic matter degradation is one driver for shifting the microbial community composition and therefore possibly the performance of these bioreactors over time.

Seasonal Microbial Population Shifts in a Bioremediation System Treating Metal and Sulfate-Rich Seepage

“…In the Rock-Eval-6 technique, samples are exposed to progressively increasing temperatures, during which hydrocarbon compounds of differing molecular weights are liberated and quantified. The method used for biosolids samples is given in detail elsewhere [20]. Briefly, the so-called S1 and S2 fractions represent hydrocarbons liberated at 300˝C and when the temperature is increased from 300-650˝C, respectively, and the S3 fraction is the amount of CO 2 evolved during pyrolysis.…”

“…The composition of the organic material was estimated using a pyrolysis technique that has been used previously for characterizing soil organic matter [61] and pulp mill biosolids within the BCR [20]. In the Rock-Eval-6 technique, samples are exposed to progressively increasing temperatures, during which hydrocarbon compounds of differing molecular weights are liberated and quantified.…”

“…Bioreactor influent and effluent water chemistry were measured bi-weekly [20] and the lysimeter pore water monthly at the same time that a biosolids mesh bag was removed. pH, oxidation-reduction potential (ORP), dissolved oxygen (DO) and temperature were measured in situ with multi-probe field meters according to the manufacturer's instructions (Hach Company, Loveland, CO, USA).…”

“…The methods used were identical to those described in [20]. Briefly, SSU rRNA amplicons were prepared using universal primers for the V6-V8 variable SSU rRNA region: 926f (5' AAACTYAAAKGAATTGRCGG 3') and 1392r (5' ACGGGCGGTGTGTRC 3') with adaptor and barcode, and sequenced at the Genome Quebec and McGill University Innovation Center (Montréal, QC, Canada) using a Roche GS-FLX Titanium Series sequencer.…”

“…Briefly, SSU rRNA amplicons were prepared using universal primers for the V6-V8 variable SSU rRNA region: 926f (5' AAACTYAAAKGAATTGRCGG 3') and 1392r (5' ACGGGCGGTGTGTRC 3') with adaptor and barcode, and sequenced at the Genome Quebec and McGill University Innovation Center (Montréal, QC, Canada) using a Roche GS-FLX Titanium Series sequencer. Pyrotag reads were filtered using quality control criteria (minimum length 200 bp, no ambiguous base reads, no missing quality scores, mean quality score greater than 25, no more than six nucleotide length homopolymer runs, and no mismatches in reverse primer) with the Qiime suite of Python scripts [24] as described in [20]. Operational taxonomic units (OTUs) were clustered according to 95% sequence similarity.…”