Anaerobic digestion (AD) is commonly used as a waste processing technology, however its potential to serve as a source of renewable energy has spurred interest into how the microbial communities in AD systems carryout the AD process and what influences their activity. Previous analyses of these communities were generally based on analysis techniques such as DGGE or small sequencing libraries. Additionally, conflicting results have been reported regarding the diversity and abundance of Bacteria and Archaea in AD systems. The overall objective of my research was to further describe the microbial consortia that participate in the AD process as well as to investigate the patterns of their diversity. In the first study an initial baseline of the microbial diversity participating in the AD process is established using a meta-analysis approach, allowing the global diversity of microbes in AD systems to be determined. Major bacterial groups identified were the phyla Chloroflexi, Proteobacteria, Firmicutes, and Bacteroidetes, while the largest archaeal groups were the genus Methanosaeta and the uncultured clade WSA2/ArcI. The second study focused on determining the effects of feedstock and biomass fraction on the microbial communities in a sequential digester operation. Using large 16S rRNA clone libraries, both the bacterial and archaeal populations were examined. The resulting communities were found to be very distinct, indicating feedstock composition had a large effect on selecting a microbial community suited to the particular feedstock supplied. Differences between the granular and liquid biomass fractions were observed, indicating potential differences in the metabolic role of these two microbial communities within a single AD system.
Using pyrosequencing, the third study examined changes in microbial community structure in relation to operational parameters in an AD system operated for a yearlong period. Analysis of six time points showed a highly variable microbial community, with large shifts in microbial abundance observed at the phylum level for Bacteria. A significant shift from Methanosaeta to Methanosarcina was observed due to additions of acetate to the system, with an increase of unclassified Euryarchaeota due to an increase in temperature. Exploratory use of the statistical analysis method canonical correspondence analysis (CCA) failed to fully associate patterns of bacterial diversity to reactor performance. The use of CCA itself was, however justified and future analyses will require a larger number of samples and more complete performance data for proper analysis. The fourth study sought to examine the shared microbial communities between AD systems with vastly different operational designs and parameters. The majority of OTUs were unique to the system from which they were recovered, with sequences corresponding to shared OTUs not being recovered in equal abundance for each sample, confirming that the diversity of AD systems is highly variable. As no members of the class Methanomicrobia were recovered in sequencing surveys, two multiplex qPCR assays for five genera of methanogens abundant in AD systems was developed. The results of the assays showed that Methanobacterium was abundant in nearly all samples, but not recovered using sequencing methods, suggesting that sequencing libraries miss important groups of Bacteria or Archaea.
The results of my research provide greater insight into the microbial communities that participate in the AD process than previously documented. Incorporation of these results into the design and optimization of AD systems will further improve the stability and performance of these systems in the future.