摘要

Anaerobic treatment is a sustainable and economical technology for waste stabilization and production of methane as a renewable energy. However, the process is under-utilized due to operational challenges. Organic overload or toxicants can stress the microbial community that performs waste degradation, resulting in system failure. In addition, not all methanogenic microbial communities are equally capable of consistent, maximum biogas production. Opinion varies as to which parameters should be used to monitor the fitness of digester biomass. No standard molecular tools are currently in use to monitor and compare full-scale operations. It was hypothesized that determining the number of gene copies of mcrA, a methanogen-specific gene, would positively correlate with specific methanogenic activity (SMA) rates from biomass samples from six full-scale anaerobic digester systems. Positive correlations were observed between mcrA gene copy numbers and methane production rates against H-2:CO2 and propionate (R-2=067-070, P<005) but not acetate (R-2=049, P>005). Results from this study indicate that mcrA gene targeted qPCR can be used as an alternate tool to monitor and compare certain methanogen communities in anaerobic digesters. Significance and Impact of the StudyUsing quantitative PCR (qPCR), we demonstrate that the abundance of mcrA, a gene specific to methane producing archaea, correlated with specific methanogenic activity (SMA) measurements when H-2 and CO2, or propionate were provided as substrates. However, mcrA abundance did not correlate with SMA with acetate. SMA values are often used as a fitness indicator of anaerobic biomass. Results from qPCR can be obtained within a day while SMA analysis requires days to weeks to complete. Therefore, qPCR for mcrA abundance is a sensitive and fast method to compare and monitor the fitness of certain anaerobic biomass. As a monitoring tool, qPCR of mcrA will help anaerobic digester operators optimize treatment and encourage more widespread use of this valuable technology.

  • 出版日期2016-2