Next-Generation Sequencing of Microbial Communities in the Athabasca River and Its Tributaries in Relation to Oil Sands Mining Activities

• Published in: Applied and Environmental Microbiology
• Main Authors: Yergeau, Etienne, Lawrence, John R., Sanschagrin, Sylvie, Waiser, Marley J., Korber, Darren R., Greer, Charles W.
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Society for Microbiology 2012
• Subjects: Athabasca River
• Online Access: http://dx.doi.org/10.1128/aem.02036-12; https://journals.asm.org/doi/pdf/10.1128/AEM.02036-12

ABSTRACT The Athabasca oil sands deposit is the largest reservoir of crude bitumen in the world. Recently, the soaring demand for oil and the availability of modern bitumen extraction technology have heightened exploitation of this reservoir and the potential unintended consequences of pollution in the Athabasca River. The main objective of the present study was to evaluate the potential impacts of oil sands mining on neighboring aquatic microbial community structure. Microbial communities were sampled from sediments in the Athabasca River and its tributaries as well as in oil sands tailings ponds. Bacterial and archaeal 16S rRNA genes were amplified and sequenced using next-generation sequencing technology (454 and Ion Torrent). Sediments were also analyzed for a variety of chemical and physical characteristics. Microbial communities in the fine tailings of the tailings ponds were strikingly distinct from those in the Athabasca River and tributary sediments. Microbial communities in sediments taken close to tailings ponds were more similar to those in the fine tailings of the tailings ponds than to the ones from sediments further away. Additionally, bacterial diversity was significantly lower in tailings pond sediments. Several taxonomic groups of Bacteria and Archaea showed significant correlations with the concentrations of different contaminants, highlighting their potential as bioindicators. We also extensively validated Ion Torrent sequencing in the context of environmental studies by comparing Ion Torrent and 454 data sets and by analyzing control samples.