abstract: Trichloroethene (TCE) is a ubiquitous soil and groundwater contaminant. The most common bioremediation approach for TCE relies on the process of reductive dechlorination by Dehalococcoides mccartyi. D. mccartyi use TCE, dichloroethene, and vinyl chloride as electron acceptors and hydrogen as an electron donor. At contaminated sites, reductive dechlorination is typically promoted by adding a fermentable substrate, which is broken down to short chain fatty acids, simple alcohols, and hydrogen. This study explored microbial chain elongation (MCE), instead of fermentation, to promote TCE reductive dechlorination. In MCE, microbes use simple substrates (e.g., acetate, ethanol) to build medium chain fatty acids and also produce hydrogen during this process. Soil microcosm using TCE and acetate and ethanol as MCE substrates were established under anaerobic conditions. In soil microcosms with synthetic groundwater and natural groundwater, ethene was the main product from TCE reductive dechlorination and butyrate and hydrogen were the main products from MCE. Transfer microcosms using TCE and either acetate and ethanol, ethanol, or acetate were also established. The transfers with TCE and ethanol showed the faster rates of reductive dechlorination and produced more elongated products (i.e., hexanoate). The microbial groups enriched in the soil microcosms likely responsible for chain elongation were most similar to Clostridium genus. These investigations showed the potential for synergistic microbial chain elongation and reductive dechlorination of chlorinated ethenes. / Dissertation/Thesis / Masters Thesis Civil, Environmental and Sustainable Engineering 2019

abstract: This research explores microbial chain elongation as a pathway for production of complex organic compounds in soils with implication for the carbon cycle. In chain elongation, simple substrates such as ethanol and short chain carboxylates such as acetate can be converted to longer carbon chain carboxylates under anaerobic conditions through cyclic, reverse β oxidation. This pathway elongates the carboxylate by two carbons. The chain elongation process is overall thermodynamically feasible, and microorganisms gain energy through this process. There have been limited insights into the versatility of chain elongating substrates, understanding the chain elongating microbial community, and its importance in sequestering carbon in the soils. We used ethanol, methanol, butanol, and hydrogen as electron donors and acetate and propionate as electron acceptors to test the occurrence of microbial chain elongation in four soils with different physicochemical properties and microbial communities. Common chain elongation products were the even numbered chains butyrate, caproate, and butanol, the odd numbered carboxylates valerate and heptanoate, along with molecular hydrogen. At a near neutral pH and mesophilic temperature, we observed a stable and sustained production of longer fatty acids along with hydrogen. Microbial community analysis show phylotypes from families such as Clostridiaceae, Bacillaceae, and Ruminococcaceae in all tested conditions. Through chain elongation, the products formed are less biodegradable. They may undergo transformations and end up as organic carbon, decreasing the greenhouse gas emissions, thus, making this process important to study. / Dissertation/Thesis / Masters Thesis Chemical Engineering 2018

Open cultures of anaerobic reactor systems convert organic wastes or biomass residues into mainly short-chain carboxylates with two to five carbon atoms. The short-chain carboxylates can be converted into the highly reduced end product methane by methanogenic consortia in anaerobic digestion. Microbial chain elongation such as via the reverse ꞵ-oxidation pathway was found as an alternative electron sink with the same anaerobic reactor microbiota. In natural ecosystems such as rumen microbial ecosystem, some anaerobic bacteria are known to produce medium-chain carboxylates (e.g., n-caproate and n-caprylate) through reverse ꞵ-oxidation. The carboxylate platform aims to recover carbon from waste streams or biomass residues by anaerobic fermentation in the form of medium-chain carboxylates. It has created great opportunities to replace chemicals derived from non-sustainable sources such as fossil feedstock. Mixed culture fermentation is commonly employed for the chain elongation processes. The diverse microbial chain elongation communities contain different functional groups involved in the processes of hydrolysis and fermentation of available organic compounds as well as the conversion of intermediates to medium-chain carboxylates. In general, the underlying metabolism and ecological interactions of the chain elongation communities are not well understood. This PhD thesis centres on the metabolism and ecological interactions in closed model ecosystems (i.e., anaerobic bioreactors) involved in microbial chain elongation with lactate. In the first chapter, a model ecosystem with reduced complexity was developed by using lactate and xylan as defined carbon sources to simulate the feedstock conditions of caproate-producing bioreactors operated with corn silage. Feeding defined carbon sources enabled balancing of electron and carbon flows. By preventing continuous inoculation, the simplified community of enrichment cultures allowed to study the metabolic and community dynamics in a clearer manner than open reactor systems. During a long-term reactor experiment, four succession stages including adaptation, stage I (high medium-chain carboxylate-producing period), transition and stage II (high butyrate-producing period) were observed. Co-occurrence networks of species based on 16S rRNA amplicon sequences and associations with process parameters were analysed to infer potential metabolic functions and microbial interactions. The results suggested that the process included diverse functions of xylan hydrolysis, xylose fermentation and chain elongation with lactate as electron donor. The inferred interactions such as cooperation between lactic acid bacteria and chain-elongating bacteria, as well as competition between medium-chain carboxylate-producing bacteria and butyrate-producing bacteria, resulted in the community development over four succession stages. In this closed model ecosystem, the chain-elongating bacteria were outcompeted by butyrate-producing bacteria under constant conditions, leading to the increase of butyrate yield at the cost of n-caproate and n-caprylate yields. The second chapter tested the effects of shortening the hydraulic retention time on the community assembly and functioning in the model ecosystems, aiming to quantitatively predict ecophysiological functions of the microbial communities. For the process performance, higher productivities and yields of n-caproate and n-caprylate were achieved by reducing the hydraulic retention time from 8 days to 2 days in two continuous reactors. A predictive model was generated by applying the random forest approach using 16S rRNA amplicon sequencing data. More than 90% accuracy in the quantitative prediction of n-caproate and n-caprylate productivities was achieved. Four inferred bioindicators belonging to the genera Olsenella, Lactobacillus, Syntrophococcus and Clostridium IV suggested their relevance to the higher carboxylate productivity at shorter hydraulic retention time. Combined with metagenomics, the recovery of metagenome-assembled genomes of these bioindicators confirmed their genetic potential to perform key steps of carboxylate production. Besides, functional redundancy in the conversion of xylan and lactate to n-butyrate, n-caproate and n-caprylate was revealed, with the relevant bioindicators increasing in relative abundance. Thus, the involved metabolic pathways were strongly coupled to the decrease in hydraulic retention time. In general, the developed machine learning framework to identify bioindicators and to quantitatively predict process performance is transferable to other ecosystem processes and microbial systems where community dynamics is linked to key functions. In the third chapter, the effects of pH increase on the chain elongation community assembly and functioning were tested based on the developed model ecosystems. The increase in pH from 5.5 to 6.0 caused fluctuations in the yields of n-butyrate, n-caproate and n-caprylate. After the pH disturbance, the carboxylate yields returned to the previous values while the communities developed to a different state, observed as decrease in diversity and evenness and increase in richness. Some taxa shifted from rare to abundant, reflecting strong selective effects of lower pH values. By applying Aitchison PCA clustering, linear mixed effect models and random forest classification, the different pH preferences of the potential chain elongators Clostridium IV and Clostridium sensu stricto were identified. By constructing networks for different pH levels, the cooperation of the chain elongator Clostridium IV with lactic acid bacteria switches from Olsenella to Lactobacillus along the pH increase, revealing the plasticity of the food web of chain elongation communities. Compared with the previously observed results of decreasing the hydraulic retention time, pH increase induced dramatic shifts in the community assembly but exhibited no strong effects on community functioning in terms of medium-chain carboxylate production. High functional redundancy was indicated despite the reactors being long-term closed systems. In parallel to the reactor experiments, pure cultures of chain-elongating clostridial strains were isolated, representing three novel species. Their genomes were assembled using a hybrid short and long read sequencing approach. The three novel strains produced n-caproate, n-butyrate, iso-butyrate and acetate from lactate in batch cultivation at pH 5.5, with the confirmation of their genetic background of lactate-based chain elongation and using CoA transferase as the terminal enzyme. Their genomes show substantial genetic heterogeneity but contain highly conserved genes involved in lactate oxidation, reverse ꞵ-oxidation, hydrogen formation and either of two types of energy conservation systems (Rnf and Ech). The genetic background of lactate-based chain elongation in these isolates and other experimentally validated chain-elongating strains was analysed by comparative genomics. The chain elongation-specific core-genome was indicated to encode the pathways for reverse ꞵ-oxidation, hydrogen formation and energy conservation while chain-elongating species displayed substantial genome heterogeneity. Further research is needed to elucidate the pathways for iso-butyrate formation in these strains. In summary, model communities of chain elongation processes were enriched and further shaped by alternations of pH and hydraulic retention time in long-term bioreactor experiments. The metabolism and ecological interactions of reactor microbiota involved in microbial chain elongation with lactate were elucidated by using 16S rRNA amplicon sequencing and metagenomics coupled to network analysis, statistical modelling and machine learning, which also sparkled new insights into the relationship between microbial chain elongation community diversity and functioning. The isolation of novel chain-elongating species further expands our knowledge on the metabolism of chain elongation bacteria. Finally, a better understanding of the rules governing community assembly is key to accelerate the development of microbiota-based biotechnologies.:Abbreviations ...................................................................................................1 List of figures ...................................................................................................4 List of tables.....................................................................................................9 Zusammenfassung ........................................................................................12 Summary .......................................................................................................17 1 Introduction .................................................................................................21 1.1 Reactor microbiota................................................................................21 1.2 Carboxylate platform.............................................................................21 1.3 Microbial chain elongation ....................................................................22 1.4 Methods for investigating reactor microbiota ........................................24 1.4.1 PCR-based methods ......................................................................24 1.4.2 Metagenomics ................................................................................25 1.4.3 Culture-dependent methods...........................................................27 1.5 Aims of this study..................................................................................28 2 Research chapters......................................................................................29 2.1 Competition between butyrate fermenters and chain-elongating bacteria limits the efficiency of medium-chain carboxylate production .....................29 2.1.1 Main text.........................................................................................30 2.1.2 Supplementary information.............................................................43 2.2 Machine learning-assisted identification of bioindicators predicts medium-chain carboxylate production performance of an anaerobic mixed culture .47 2.2.1 Main text.........................................................................................48 2.2.2 Supplementary information.............................................................83 2.3 Effects of pH increase on microbial chain elongation and community dynamics in closed bioreactor ecosystems...............................................104 2.3.1 Main text.......................................................................................105 2.3.2 Supplementary information...........................................................134 2.4 Draft genome sequences of three Clostridia isolates involved in lactate-based chain elongation.............................................................................148 2.5 Three novel Clostridia isolates produce n-caproate and iso-butyrate from lactate: comparative genomics of chain-elongating bacteria ....................151 2.5.1 Main text.......................................................................................152 2.5.2 Supplementary information...........................................................192 3 General discussion ...................................................................................196 3.1 Understanding microbial community assembly in model ecosystems 196 3.2 Linking microbial community structure to functioning..........................199 3.3 Moving from intriguing science to real-world practice – Microbiota-based biotechnology ...........................................................................................200 4 References ...............................................................................................202 5 Appendix...................................................................................................208 5.1 Declaration of authorship....................................................................208 5.2 Coauthor contributions........................................................................209 5.3 Curriculum Vitae .................................................................................213 5.4 List of publications and conference contributions ...............................215 5.5 Acknowledgements.............................................................................218