Metagenomics for optimizing mine-influenced water treatment bioreactors
CIM Vancouver 2016
Mr Lauren Lundquist (Tetra Tech Engineering and Consulting Services), Mr Steven Hallam (Microbiology and Immunology, University of British Columbia), Mrs Alison Morrison (Trail Creek Consulting, Ltd), Mrs Susan A.Baldwin (Chemical and Biological Engineering, University of British Columbia)
Mine-influenced water (MIW) treatment is an immense challenge due to the complex mixtures of components present and the large volumes that have to be handled. Increasingly biological processes are being implemented for removing constituents of concern from MIW, due a combination of their effectiveness and lower costs compared with more traditional chemical technologies. Nevertheless, their reliability cannot always be ensured, which might lead to disastrous consequences when effluents that have not been treated adequately are discharged into the receiving environment. New innovative approaches are coming into play to help understand why treatment is successful when it works and the reasons for when it fails. Metagenomics is the science of reconstructing microbial population structure and function from massive high-throughput sequencing of nucleic acids extracted from an environmental sample. We have been using metagenomics to acquire information about microorganisms present in several different types of MIW treatment bioreactors, from so-called passive systems using complex carbonaceous material to active processes using defined nutrient mixtures to support microbial growth. Metagenomic information allowed us to diagnose possible causes of operational problems, which lead to suggested process changes that when implemented improved treatment performance. For instance, treatment success might require the presence of specific types of microorganisms, and conditions under which these thrive must be determined so as to implement effective process control strategies. On the other hand, certain types of microorganisms can be undesirable and their early detection will allow time for process correction before any deleterious impacts materialize. In this talk, we will describe some of the information that can be gleaned from metagenomics and show how this was applied to solve operational problems.