DRIVERS OF POPULATION SUCCESSION IN ANAEROBIC COMMUNITIES OF METHANOGENIC TREATMENT PROCESSES

Anaerobic digestion (AD) is a process in which complex organic matter is converted into methane and CO2 with the activities of an anaerobic food web. Despite recent efforts to understanding the mechanisms of microbial community assembly, processes shaping the community structure in AD remain unresolved. With this study, firstly, we investigated the anaerobic microbial community in the anaerobic treatment of dairy wastewater in triplicate anaerobic bioreactors over a 118-day period. The results showed successional trajectories of the microbial community during this period, with stochastic processes accounting for 66.5% -77.7% of community assembly. Subsequent network analysis indicated strong positive correlations between intra-taxa populations and negative correlations between inter-taxa populations, implying the importance of deterministic factors derived from internal dynamics. Secondly, in order to characterize the impact of deterministic processes on microbial community assembly, the anaerobic bioreactors were subjected to a change in substrate. As expected, microbial succession before and after the substrate shift was controlled mainly by deterministic processes (92.4%). For the archaeal community, Methanosaeta remained as the most abundant archaeal genus before and after substrate shift, while Methanoregula thrived after substrate shift. As for the bacteria, the top five abundant bacterial phyla before substrate shift were Firmicutes, Bacteroidetes, Proteobacteria, Synergistetes and Actinobacteria. Following the substrate shift, Chloroflexi and Spirochaetes outcompeted Synergistetes and Actinobacteria to join the top five abundant phyla, suggesting these populations might be metabolically responsive to the change in substrate. To evaluate community responses to other deterministic drivers, ammonia stress was tested in the AD bioreactors. Microbial community analysis revealed the increased contribution of deterministic processes with elevated levels of ammonia stress. As for the microbial responses, Methanobacterium and Methanosarcina were abundant methanogens in all bioreactors, suggesting the resistance of these populations to ammonia stress. Results of the bacterial compositions indicated that sequences of Treponema from the phylum Spirochaetes was inhibited when ammonia was added. After ammonia stress was relieved, the abundance of Treponema rebounded, indicating the lack of intolerance of this population toward ammonia stress and its competitiveness at low ammonia concentration. Additionally, to characterize the microbial response to osmotic stress, which is a common deterministic driver in AD, the impact of sodium stress was investigated in AD. Microbial composition analysis suggests that Methanosarcina and Methanofollis are methanogen populations tolerant to elevated sodium. As for the bacteria, the genus Kosmotoga in Thermotogae and genus Aminobacterium in phylum Synergistetes exhibited tolerance to sodium stress, while genus Treponema from phylum Spirochaetes were found to be sensitive to sodium. These observations again imply the importance of deterministic factors derived from internal dynamics. To identify the functional basis for the responses of anaerobic populations to deterministic drivers, metagenomics analysis was performed for the microbial communities in the anaerobic bioreactors with a focus on acetoclastic methanogensis, which was a dominant pathway in anaerobic treatment. Metabolic pathways associated with acetate conversion was profiled in the obligate acetoclastic methanogen—Methanosaeta. The results supported the broad occurrence and importance of Methanosaeta populations in the methanogenic process. Findings of this study will enhance the understanding of metabolic and ecological processes that shape methanogenic microbial communities, which could be used to develop models for the effective control and management of anaerobic conversion processes