Long-term monitoring reveals stable and remarkably similar microbial communities in parallel full-scale biogas reactors digesting energy crops

Biogas is an important renewable energy carrier. It is a product of stepwise anaerobic degradation of organic materials by highly diverse microbial communities forming complex interlinking metabolic networks. Knowledge about the microbial background of long-term stable process performance in full-sc... Full description

Biogas is an important renewable energy carrier. It is a product of stepwise anaerobic degradation of organic materials by highly diverse microbial communities forming complex interlinking metabolic networks. Knowledge about the microbial background of long-term stable process performance in full-scale reactors is crucial for rationally improving the efficiency and reliability of biogas plants. To generate such knowledge, in the present study three parallel mesophilic full-scale reactors fed exclusively with energy crops were sampled weekly over one year. Physicochemical process parameters were determined and the microbial communities were analysed by terminal restriction fragment length polymorphism (T-RFLP) fingerprinting and 454-amplicon sequencing. For investigating the methanogenic community, a high-resolution T-RFLP approach based on the mcrA gene was developed by selecting restriction enzymes with improved taxonomic resolution compared to previous studies. Interestingly, no Methanosarcina-related generalists, but rather specialized hydrogenotrophic and acetoclastic methanogenic taxa were detected. In general, the microbial communities in the non-connected reactors were remarkably stable and highly similar indicating that identical environmental and process parameters resulted in identical microbial assemblages and dynamics. Practical implications such as flexible operation schemes comprising controlled variations of process parameters for an efficient microbial resource management under fluctuating process conditions are discussed. Microbial assemblages in full-scale anaerobic digesters were analysed by community fingerprinting techniques, high-throughput sequencing and multivariate statistics, and revealed to be shaped by deterministic rather than stochastic effects.