Abstract
Injection of up-flow packed-bed bioreactors with excess volatile fatty acids and limiting concentrations of nitrate and sulfate gave complete reduction of nitrate from 0 to 5.5 cm and complete or near-complete reduction of sulfate from 3.2 to 11.5 cm along the bioreactor flow path. Most of the biomass (85%) and most of the genes for nitrate reduction (narG, 96%; napA, 99%) and for sulfate reduction (dsrB, 91%) were present near the inlet (0–5.5 cm) of the 37-cm-long bioreactor. Microbial community analysis by a combination of denaturing gradient gel electrophoresis and pyrosequencing of 16S rRNA amplicons indicated that nitrate-reducing Arcobacter and Pseudomonas species were located from 0 to 3.2 cm and throughout, respectively. Desulfobulbus species were the main sulfate reducers present and acetotrophic methanogens of the genus Methanosaeta predominated at 20–37 cm. Overall, the results indicated a succession of microbial communities along the bioreactor flow path. In the absence of nitrate, the sulfate reduction zone moved nearer to the bioreactor inlet. The sulfide concentration in the bioreactor effluent was temporarily lowered after nitrate injection was re-started. Hence, the bioreactor sulfide output could be disrupted by pulsed, not by constant nitrate injection, as demonstrated also previously in a low-temperature oil field.
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Acknowledgments
This work was supported by an NSERC Industrial Research Chair Award to GV, which was also supported by Baker Hughes Incorporated, Commercial Microbiology Limited (Intertek), the Computer Modelling Group Limited, ConocoPhillips Company, YPF SA, Aramco Services, Shell Canada Limited, Suncor Energy Developments Inc., and Yara International ASA, as well as by the Alberta Innovates-Energy and Environment Solutions. This work was also supported by funding from Genome Canada, Genome Alberta, the Government of Alberta, and Genome BC. The authors are grateful for technical support provided by Dr. Sasha Grigoryan and for administrative support by Dr. Rhonda Clark. Gary Leveque from the Genome Quebec and McGill University Innovation Centre, Montreal, Quebec, are thanked for pyrosequencing.
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Fig. S1
Clustering analysis of pyrosequencing data obtained for samples from bioreactor-C using the Fast UniFrac service based on the weighted and normalized UniFrac unit matrix. The scale bar indicates the distance between clusters in UniFrac units (DOC 34 kb)
Table S1
Class level survey of 16S sequences in samples from bioreactor-C. The number of pyrosequencing reads (N) for each sample is indicated. The percentage fraction (%) of these is listed for each class. The list is ranked in order of most- to least-prevalent class for all samples. Classes with a percentage below 0.02% were eliminated. Samples were obtained for the glass wool (GW), polymeric mesh (PM), and above port 1a (a1a) sections as well as for ports 1a, 1, 2, 3, and 4 of bioreactor-C (see Fig. 1) (DOC 426 kb)
Table S2
Genus level survey of 16S sequences in samples from bioreactor-C. The number of reads (N) for each sample is indicated. The fractions (%) of these are listed for each genus. The list is ranked in order of most to least prevalent genus for all samples. Genera with an average fraction of 0.02% or less were eliminated. Samples were obtained for the glass wool (GW) and polymeric mesh (PM) and above port 1a (a1a) sections, as well as for ports 1a, 1, 2, 3, and 4 of bioreactor-C (see Fig. 1) (DOC 632 kb)
Table S3
Biomass and DNA concentrations in fractions obtained from bioreactor-C (DOC 46 kb)
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Callbeck, C.M., Dong, X., Chatterjee, I. et al. Microbial community succession in a bioreactor modeling a souring low-temperature oil reservoir subjected to nitrate injection. Appl Microbiol Biotechnol 91, 799–810 (2011). https://doi.org/10.1007/s00253-011-3287-2
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DOI: https://doi.org/10.1007/s00253-011-3287-2