< Back to previous page

Project

Linking microbial community assembly with functionality in lab-scale anaerobic digestion bioreactors: a replicate experimental approach

Anaerobic digestion (AD) is the microbiological conversion of organic material under anaerobic conditions, leading to the formation of biomass, biogas and a nutrient rich digestate. The process is gaining an increasing interest because of its potential for simultaneous waste stabilisation and valorisation. Using AD, methane-rich biogas as well as valuable chemicals and a nutrient-rich residue can be produced from organic material in solid wastes and wastewater. Last decades, the demand for more sustainable waste management techniques, together with the urgent need for renewable energy sources, has led to an increasing interest and application of AD technologies, both in solid waste and wastewater treatments. Aside from the potential bioenergy and nutrient recovery, AD for wastewater treatment comprises several other advantages over conventional aerobic technology, including lower energy demand, small footprint and fewer excess sludge production. However, disadvantages include wash-out of the anaerobic biomass, long start-up periods and higher sensitivity to fluctuating process conditions. The first problem is largely countered by the development of methods that allow to concentrate the anaerobic biomass in the reactor. The second issue is mostly covered as well, since a more widespread implementation of AD has resulted in an increasing availability of active anaerobic sludge for inoculation of new AD systems, which allows to start-up within several weeks. The last, however, is a major reason why in many cases aerobic treatment is still chosen over anaerobic technology. An increasing knowledge on AD process operation has helped to increase reactor stability, but still, industries fear the complexity of the anaerobic process and its sensitivity to changing conditions, which limits the application of AD technology.

AD process performance is directly linked with the structure and dynamics of the microbial reactor community. Therefore, a better understanding of the AD microbiome and the identification of microbial indicators of process performance and stability is considered a key research subject towards the optimisation, control and management of anaerobic reactors. Despite intensive efforts to identify microbial parameters that significantly correlate with process performance and stability, microbial-based control and management of AD reactors is still far from reality. The high community diversity in the AD microbiome, complex microbial interactions and a high degree of functional redundancy, which is the ability of different microbial communities to perform the same ecological functions, are considered major causes for the slow progression in this field. A thorough understanding of the relationship between community composition and functionality is currently hampered by the lack of biological replicates in well-controlled experimental conditions. Taking into account the high functional redundancy existing in AD communities, the variation in community assembly and its effect on reactor performance is difficult to grasp.

The overall objective of this study was (i) to get more insight into the factors that shape community assembly in the AD process, both at the taxonomic and functional level, (ii) to evaluate the impact on process performance and (iii) to indicate common determining species and functions. The focus was on the role of the inoculum community and the role of stress factors. In contrast to many other AD studies, a replicate approach was used in order to get insight into the variability of the community assembly process and the role of deterministic and stochastic factors in shaping AD communities. Community structures were studied using amplicon metagenomic sequencing of the 16S rRNA gene and transcript, to target the total and the active AD community, respectively. Functional profiles were retrieved by applying metaproteomics using high-resolution tandem mass spectrometry.

In a first chapter, taking into account the crucial role that the inoculum plays in industrial AD reactors, we examined the relationship between the inoculum community composition, process performance, and reactor community assembly. We questioned whether identical operational conditions would lead to similar assemblies at the taxonomic level despite using different starting communities, and examined the deterministic character of the assembly process. Moreover, we determined the contribution of the inoculum to reactor community assembly. To this end, we studied three sets of biologically replicated AD reactors inoculated with different communities, but operated identically, targeting both total and active communities. All reactors performed highly similar regarding volatile fatty acid and methane production. Community analyses showed reproducible total and active community compositions in replicate reactors indicating that particularly deterministic factors shape the AD community. However, between differently inoculated reactors we observed strong variation in community composition, indicating the role of inoculum composition in community shaping. In all three reactor sets, especially species that were low in abundance or even not detected in the inoculum contributed to the reactor communities, supporting the importance of functional redundancy and high diversity in inocula used for AD seeding. The careful start-up of the AD process using initially low organic loading rates likely contributed to the successful assembly of rare species into a novel cooperative AD community in the reactors.

In a second chapter, we used the same approach to explore how community assembly was affected by the presence of a stress factor under the form of phenol. Four inocula were used to start three replicate fed-batch reactors each, which received an increasing loading rate of phenol in addition to a dairy synthetic feed. Three of the inocula were sampled from AD systems that were previously exposed to phenolic compounds, to examine whether this pre-exposure affected success rate and community assembly. Phylotypes which explained reactor performance and community assembly were identified. The non-pre-exposed sludge developed successful and stable AD in all three replicates. In contrast, only one of the pre-exposed sludges developed stable AD, and this in only two of the three replicates. Well-performing reactors always showed phenol degradation, indicating that phenol removal was an essential asset for establishing phenol tolerance in the reactors. In well-performing stable reactors, replicate reactors inoculated with the same community, showed highly similar community compositions, indicating that phenol did not affect the deterministic character of the community assembly process. In contrast, in unstable reactors, community compositions showed more variation, even among reactors started from the same inoculum. The AD performance in stable reactors was explained by the proliferation of species belonging to Syntrophus, Cryptanaerobacter, Lactivibrio and Mesotoga, of which Syntrophus and Cryptanaerobacter are known for their phenol degrading capacity.  these determining species were observed as rare species in the starting communities of all reactors, including those of unstable reactors. Our study showed that the use of pre-exposed sludge does not necessarily improve the tolerance of AD reactors to phenol, nor AD process performance on a phenol-rich influent. Moreover, it showed that start-up with phenol-impacted wastewaters is not always a reliable process. Comparison of total and active community compositions showed a stronger response to changing conditions and process disturbance in the active than in the total community, suggesting that RNA-based community analysis has the higher potential to provide an early indication of community structure responses.

Triggered by the large functional redundancy observed in the AD reactor communities, in a third chapter, we examined whether the functional profiles of the AD reactor communities showed less variability than the taxonomic profiles, and hence would be more suited to search for universal biomarkers determining the AD process. To this end, the metaproteomes from the dairy-fed replicate reactor communities were examined, and the observed similarities were compared to those at the taxonomic level. We found significantly higher similarity in the community’s metaproteomic profiles compared to their taxonomic profiles, both at the DNA and the RNA level. This functional similarity supports the idea that robust microbial indicators would rather be function-related than taxonomic biomarkers. Highly abundant enzymes shared among all stable-performing dairy-fed reactors included several enzymes linked with the AD process.

In the last chapter, we performed a quantitative metaproteomic analysis of the phenol-amended reactors in order to determine specific functional markers related with stable anaerobic phenol degradation. In addition, we compared the metaproteomes of the phenol-fed communities with those obtained from communities in dairy-fed reactors without phenol in order to determine effects of phenol at the metaproteome level. From the set of shared abundant enzymes in dairy-fed reactors, only lactate dehydrogenase was not detected in any of the phenol-fed reactors. Furthermore, in several reactors which had experienced high phenol concentrations acetyl-CoA synthetase, a key enzyme related to acetoclastic methanogenesis, was not detected, suggesting a shift from acetoclastic to hydrogenotrophic methanogenesis after phenol toxicity. The metaproteomic analysis of phenol-fed reactors provided evidence for the anaerobic degradation of phenol via the benzoyl-CoA pathway and further degradation to acetyl-CoA.

In conclusion, this study showed variability in AD community’s functional, but mostly taxonomic profiles, using lab-scale replicate reactors under well- controlled conditions and applying a multi-omics approach including amplicon metagenomics and metaproteomics. These results will further elucidate the microbial ‘black box’ of anaerobic reactors and evaluate the possibilities for microbial-based control and management in the future.

Date:19 Feb 2014 →  13 Feb 2020
Keywords:Anaerobic digestion, Community ecology, 16S rRNA amplicon sequencing, Metaproteomics
Disciplines:Soil sciences, challenges and pollution, Agriculture, land and farm management
Project type:PhD project