Linking microbial community structure, interactions and function in anaerobic digesters using new molecular techniques

Assessment of substrate biodegradability improvement in anaerobic Co-digestion using a chemometrics-based metabolomic approach

Anaerobic co-digestion (AcoD) can increase methane production of anaerobic digesters in plants treating wastewater sludge by improving the nutrient balance needed for the microorganisms to grow in the digesters, resulting in a faster process stabilization. Substrate mixture proportions are usually optimized in terms of biogas production, while the metabolic biodegradability of the whole mixture is neglected in this optimisation. In this aim, we developed a strategy to assess AcoD using metabolomics data. This strategy was explored in two different systems. Specifically, we investigated the co-digestion of wastewater sludge with different proportions of either grass or fish waste using untargeted High Performance Liquid Chromatography coupled to Mass Spectrometry (HPLC-MS) metabolomics and chemometrics methods. The analysis of these data revealed that adding grass waste did not improve the metabolic biodegradability of wastewater sludge. Conversely, a synergistic effect in the metabolic biodegradability was observed when fish waste was used, this effect being the highest for 25% of fish waste. In conclusion, metabolomics can be regarded as a promising tool both for characterizing the biochemical processes occurring during anaerobic digestion, and for providing a better understanding of the anaerobic digestion processes.

Genome-centric microbiome analysis reveals solid retention time (SRT)-shaped species interactions and niche differentiation in food waste and sludge co-digesters

Co-digestion of food waste with sewage sludge is widely applied for waste stabilization and energy recovery around the world. However, the effect of solid retention time (SRT) on the microbial population dynamics, metabolism and interspecies interaction have not been fully elucidated. Here, the influence of SRTs (5-25 days) on the performance of the co-digestion system was investigated and state-of-the-art genome-centric metagenomic analysis was employed to uncover the dynamics and metabolic network of the key players underlying the well-functioned and poorly-functioned co-digestion microbial communities. The results of the microbial analyses indicated that SRT largely shaped microbial community structure by enriching the syntrophic specialist Syntrophomonas and CO₂/H₂ ( formate)-using methanogen Methanocorpusculum in the well-functioned co-digester operated at SRT of 25 days, while selecting acid-tolerant populations Lactobacillus at SRT of 5 days. The metagenome assembled genomes (MAGs) of key players, such as Syntrophomonadaceae, Methanocorpusculum, and Mesotoga, were retrieved, additionally, the syntrophic acetate oxidation plus hydrogenotrophic methanogenesis (SAO-HM) were proposed as the dominant pathway for methane production. The metabolic interaction in the co-digestion microbial consortia was profiled by assigning MAGs into functional guilds. Functional redundancy was found in the bacterial groups in hydrolysis step, and the members in these groups reduced the direct competition by niche differentiation.

Syntrophic acetate oxidation replaces acetoclastic methanogenesis during thermophilic digestion of biowaste

BACKGROUND

Anaerobic digestion (AD) is a globally important technology for effective waste and wastewater management. In AD, microorganisms interact in a complex food web for the production of biogas. Here, acetoclastic methanogens and syntrophic acetate-oxidizing bacteria (SAOB) compete for acetate, a major intermediate in the mineralization of organic matter. Although evidence is emerging that syntrophic acetate oxidation is an important pathway for methane production, knowledge about the SAOB is still very limited.

RESULTS

A metabolic reconstruction of metagenome-assembled genomes (MAGs) from a thermophilic solid state biowaste digester covered the basic functions of the biogas microbial community. Firmicutes was the most abundant phylum in the metagenome (53%) harboring species that take place in various functions ranging from the hydrolysis of polymers to syntrophic acetate oxidation. The Wood-Ljungdahl pathway for syntrophic acetate oxidation and corresponding genes for energy conservation were identified in a Dethiobacteraceae MAG that is phylogenetically related to known SAOB. 16S rRNA gene amplicon sequencing and enrichment cultivation consistently identified the uncultured Dethiobacteraceae together with Syntrophaceticus, Tepidanaerobacter, and unclassified Clostridia as members of a potential acetate-oxidizing core community in nine full-scare digesters, whereas acetoclastic methanogens were barely detected.

CONCLUSIONS

Results presented here provide new insights into a remarkable anaerobic digestion ecosystem where acetate catabolism is mainly realized by Bacteria. Metagenomics and enrichment cultivation revealed a core community of diverse and novel uncultured acetate-oxidizing bacteria and point to a particular niche for them in dry fermentation of biowaste. Their genomic repertoire suggests metabolic plasticity besides the potential for syntrophic acetate oxidation. Video Abstract.

Effect of granular activated carbon pore-size distribution on biological activated carbon filter performance

Proper granular activated carbon (GAC) selection could improve the performance of biological activated carbon (BAC) filters through a combination of adsorption and biodegradation, while the GACs used in BAC filters are now mainly selected according to adsorption function, ignoring biodegradation. In this study, sand filter effluent obtained from a drinking water treatment plant was fed into continuous-flow bench-scale BAC columns operated in parallel over 245 days to examine the effects of GAC pore-size distribution on BAC filter performance, in terms of the dissolved organic carbon (DOC) and disinfection byproduct (DBP) precursors. A metagenomic analysis indicated that bacterial community structure played an important role in BAC filter performance. A significant correlation was found between metabolism-related proteins and the volume of micro-level macropores based on metaproteomic analysis. It is suggested that the adsorption saturation was dynamic and that adsorption played a role in the performance of the BAC filters throughout the 245-day operating period. Renewed adsorption capacity, or bioregeneration, was driven by bacterial metabolic activity. Such activity largely depended on the organic matter adsorbed by the GAC, in which micro-level macropores, especially those with diameters of 0.2-10 μm, played an important but previously unrecognized role. The results suggest that more attention should be paid to well-developed pores and pore-size distribution in the production and selection of GAC used for full-scale drinking water biofilters.

Effects of different conductive nanomaterials on anaerobic digestion process and microbial community of sludge

The effects of four conductive nanomaterials (nano-carbon powder, nano-Al₂O₃, nano-ZnO, nano-CuO) on sludge anaerobic digestion (AD) performance and microbial community were investigated through a 36-day fermentation experiment. Results showed that biogas production enhanced by 16.9% and 23.4% with nano-carbon powder and nano-Al₂O₃ added but decreased by 90.2% and 17.3% with nano-ZnO and nano-CuO. Total solids (TS) removal efficiency was increased by 38.73% and 27.11% with nano-carbon powder and nano-Al₂O₃ added but decreased by 70.67% and 43.70% with nano-ZnO and nano-CuO. Kinetic analysis indicated four conductive nanomaterials could shorten the lag phase of AD sludge with an average rate of 51.75%. 16S rRNA amplicon sequencing results demonstrated microbes such as Syntrophomonas and Methanosaeta were enriched in nano-carbon powder and nano-Al₂O₃ reactors. However, microbial community diversity and richness were both inhibited by adding nano-ZnO and nano-CuO. Redundancy analysis (RDA) revealed that genera belong to Firmicutes and Chloroflexi could conduce to methanogenesis process.

Biokinetics of protein degrading Clostridium cadaveris and Clostridium sporogenes in batch and continuous mode of operations

A quantitative real-time polymerase chain reaction (QPCR) was applied to estimate biokinetic coefficients of Clostridium cadaveris and Clostridium sporogenes, which utilize protein as carbon source. Experimental data of changes in peptone concentration and 16S rRNA gene copy numbers of C. cadaveris and C. sporogenes were fitted to model. The fourth-order Runge-Kutta approximation with non-linear least squared analysis was employed to solve the ordinary differential equations to estimate biokinetic coefficients. The maximum specific growth rate (μ_max), half saturation concentration (K_s), growth yield (Y), and decay coefficient (K_d) of C. cadaveris and C.sporogenes were 0.73 ± 0.05 and 1.35 ± 0.32 h^-1, 6.07 ± 1.52 and 5.67 ± 1.53 g/L, 2.25 ± 0.75 × 10¹⁰ and 7.92 ± 3.71 × 10⁹ copies/g, 0.002 ± 0.003 and 0.002 ± 0.001 h^-1, respectively. The theoretical specific growth rate of C. sporogenes always exceeded than that of C. cadaveris at peptone concentration higher than 3.62 g/L. When the influent peptone concentration was 5.0 g/L, the concentration of C.cadaveris gradually decreased to the steady value of 2.9 × 10¹⁰ copies/mL at 4 hours HRT, which indicates 67.1% of the initial population reduction, but the wash out occurred at 1.9 and 3.2 hours HRTs. The 16S rRNA gene copy numbers of C. sporogenes gradually decreased to steady values ranging from 1.1 × 10¹⁰ to 2.9 × 10¹⁰ copies/mL. C. sporogenes species was predicted to wash out at an HRT of 1.6 h.

Microbial Community Predicts Functional Stability of Microbial Fuel Cells

Stability as evaluated by functional resistance and resilience is critical to the effective operation of environmental biotechnologies. To date, limited tools have been developed that allow operators of these technologies to predict functional responses to environmental and operational disturbances. In the present study, 17 Microbial Fuel Cells (MFCs) were exposed to a low pH perturbation. MFC power dropped 52.7 ± 35.8% during the low pH disturbance. Following the disturbance, 3 MFCs did not recover while 14 took 60.7 ± 58.3 h to recover to previous current output levels. Machine learning models based on genomic data inputs were developed and evaluated on their ability to predict resistance and resilience. Resistance and resilience levels corresponding to risk of deactivation could be classified with 70.47 ± 15.88% and 65.33 ± 19.71% accuracy, respectively. Models predicting resistance and resilience coefficient values projected postperturbation current drops within 6.7-15.8% and recovery times within 5.8-8.7% of observed values. Results suggest that abundances of specific genera are better predictors of resistance while overall microbial community structure more accurately predicts resilience. This approach can be used to assess operational risk and is a first step toward the further understanding and improvement of overall stability of environmental biotechnologies.

The microbiome driving anaerobic digestion and microbial analysis

The microbiome residing in anaerobic digesters drives the anaerobic digestion (AD) process to convert various feedstocks to biogas as a renewable source of energy. This microbiome has been investigated in numerous studies in the last century. The early studies used cultivation-based methods and analysis to identify the four guilds (or functional groups) of microorganisms. Molecular biology techniques overcame the limitations of cultivation-based methods and allowed the identification of unculturable microorganisms, revealing the high diversity of microorganisms involved in AD. In the past decade, omics technologies, including metataxonomics, metagenomics, metatranscriptomics, metaproteomics, and metametabolomics, have been or start to be used in comprehensive analysis and studies of biogas-producing microbiomes. In this chapter, we reviewed the utilities and limitations of these analysis methods, techniques, and technologies when they were used in studies of biogas-producing microbiomes, as well as the new information on diversity, composition, metabolism, and syntrophic interactions of biogas-producing microbiomes. We also discussed the current knowledge gaps and the research needed to further improve AD efficiency and stability.

Genome-Centered Metagenomics Analysis Reveals the Microbial Interactions of a Syntrophic Consortium during Methane Generation in a Decentralized Wastewater Treatment System

The application of anaerobic digestors to decentralized wastewater treatment systems (DWTS) has gained momentum worldwide due to their ease of operation, high efficiency, and ability to recycle wastewater. However, the microbial mechanisms responsible for the high efficiency and ability of DWTS to recycle wastewater are still unclear. In this study, the microbial community structure and function of two different anaerobic bioreactors (a primary sludge digestor, PSD, and anaerobic membrane bioreactor, AnMBR) of a DWTS located in Germany was investigated using 16S rRNA gene amplicon and metagenomic sequencing, respectively. The results showed that the microbial community structure was remarkably different in PSD and AnMBR. Methanobacteriaceae and Syntrophaceae were identified as the families that significantly differed in abundance between these two bioreactors. We also used genome-centered metagenomics to predict the microbial interactions and methane-generating pathway, which yielded 21 near-complete assembled genomes (MAGs) (average completeness of 93.0% and contamination of 2.9%). These MAGs together represented the majority of the microbial community. MAGs affiliated with methanogenic archaea, including Methanobacterium sp., Methanomicrobiales archaea, Methanomassiliicoccales archaea, and Methanosaeta concilii, were recruited, along with other syntrophic bacterial MAGs associated with anaerobic digestion. Key genes encoding enzymes involved in specific carbohydrate-active and methanogenic pathways in MAGs were identified to illustrate the microbial functions and interactions that occur during anaerobic digestion in the wastewater treatment. From the MAG information, it was predicted that bacteria affiliated with Bacteroidetes, Prolixibacteraceae, and Synergistaceae were the key bacteria involved in anaerobic digestion. In the methane production step, Methanobacterium sp. performed hydrogenotrophic methanogenesis, which reduced carbon dioxide to methane with hydrogen as the primary electron donor. Taken together, our findings provide a clear understanding of the methane-generating pathways and highlight the syntrophic interactions that occur during anaerobic digestion in DWTS.

Solar Septic Tank: Next Generation Sequencing Reveals Effluent Microbial Community Composition as a Useful Index of System Performance

Septic tanks are widely deployed for off-grid sewage management but are typified by poor treatment performance, discharge of polluting effluents and the requirement for frequent de-sludging. The Solar Septic Tank (SST) is a novel septic tank design that uses passive heat from the sun to raise in-tank temperatures and improves solids degradation, resulting in a cleaner effluent. Treatment has been shown to exceed conventional systems, however, the underlying biology driving treatment in the system is poorly understood. We used next generation sequencing (Illumina Miseq (San Diego, CA, USA), V4 region 16S DNA) to monitor the microbiology in the sludge and effluent of two mature systems, a conventional septic tank and an SST, during four months of routine operation in Bangkok, Thailand, and evaluated the ecology against a suite of operating and performance data collected during the same time period. Significant differences were observed between the microbiome of the sludge and effluent in each system and the dominant taxa in each appeared persistent over time. Furthermore, variation in the microbial community composition in the system effluents correlated with effluent water quality and treatment performance parameters, including the removal of chemical and biochemical oxygen demand and the concentration of fecal and total coliforms in the effluent. Thus, we propose that a wide-scale survey of the biology underlying decentralised biotechnologies for sewage treatment such as the SST could be conducted by sampling system effluent rather than sampling sludge. This is advantageous as accessing sludge during sampling is both hazardous and potentially disruptive to the anaerobic methanogenic consortia underlying treatment in the systems.

A composite taxonomical and functional framework of microbiomes under acid mine drainage bioremediation systems

Mining-industry is one of the most important activities in the economic development of many countries and produces highly significant alterations on the environment, mainly due to the release of a strong acidic metal-rich wastewater called acid mine drainage (AMD). Consequently, the establishment of multiple wastewater treatment strategies remains as a fundamental challenge in AMD research. Bioremediation, as a constantly-evolving multidisciplinary endeavor had been complemented during the last decades by novel tools of increasingly higher resolution such as those based on omics approaches, which are providing detailed insights into the ecology, evolution and mechanisms of microbial communities acting in bioremediation processes. This review specifically addresses, reanalyzes and reexamines in a composite comparative manner, the available sequence information and associated metadata available in public databases about AMD impacted microbial communities; summarizing our understanding of its composition and functions, and proposing potential genetic enhancements for improved bioremediation strategies. 16 S rRNA gene-targeted sequencing data from 9 studies previously published including AMD systems reported and studied around the world, were collected and reanalyzed to compare and identify the core and most abundant genera in four distinct AMD ecosystems: surface biofilm, water, impacted soils/sediments and bioreactor microbiomes. We determined that the microbial communities of bioreactors were the most diverse in bacterial types detected. The metabolic pathways predicted strongly suggest the key role of syntrophic communities with denitrification, methanogenesis, manganese, sulfate and iron reduction. The perspectives to explore the dynamics of engineering systems by high-throughput sequencing and biochemical techniques are discussed and foreseen application of synthetic biology and omics exploration on improved AMD biotransformation are proposed.

Quantifying the contribution of microbial immigration in engineered water systems

Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.

Effect of one step temperature increment from mesophilic to thermophilic anaerobic digestion on the linked pattern between bacterial and methanogenic communities

Process fluctuation caused by temperature modification of anaerobic digestion is routinely monitored via operational parameters, such as pH and gas production, but these parameters are lagging on microbial community performance. In this study, ¹³C isotope fractionation in CH₄ and CO₂ of biogas together with microbial community dynamics were applied to evaluate process stability in response to temperature increment. Results showed that the weakening correlated links between Firmicutes affiliated families and Methanomicrobiaceae were found regarding temperature increase. In contrast, Methanosarcinaceae and Methanobacteriaceae strengthened their links with multiple bacterial groups. This suggests that the ¹³C isotope fractionation in CH₄ can predict the collapse of certain microbial interconnections and process instability, the new reinforced microbial links directly reflect the microbial community redundancy for maintaining function of syntrophic populations.

Enhancement of COD removal in constructed wetlands treating saline wastewater: Intertidal wetland sediment as a novel inoculation

This study investigated intertidal wetland sediment (IWS) as a novel inoculation source for saline wastewater treatment in constructed wetlands (CWs). Samples of IWS (5-20 cm subsurface sediment), which are highly productive and rich in halophilic and anaerobic bacteria, were collected from a high-salinity natural wetland and added to CW matrix. IWS-supplemented CW microcosms that are planted and unplanted Phragmites australis were investigated under salty (150 mM NaCl: PA+(S) and CT+(S)) and non-salty (0 mM NaCl: PA+ and CT+) conditions. The chemical oxygen demand (COD) removal potential of IWS-supplemented CWs was compared with that of conventional CWs without IWS (PA(S) and CT(S), PA, and CT). Results showed that the COD removal rate was higher in PA+(S) (51.80% ± 3.03%) and CT+(S) (29.20% ± 1.26%) than in PA(S) (27.40% ± 3.09%) and CT(S) (27.20% ± 3.06%) at 150 mM NaCl. The plants' chlorophyll content and antioxidant enzyme activity indicated that the addition of IWS enhanced the resistance of plants to salt. Microbial community analysis showed that the dominant microorganisms in PA+(S) and CT+(S), namely, Anaerolineae, Desulfobacterales, and Desulfuromonadales, enhanced the organic removal rates via anaerobic degradation. IWS-induced Dehalococcoides, which is a key participant in ethylene formation, improved the plants' stress tolerance. Several halophilic/tolerant microorganisms were also detected in the CW system with IWS. Thus, IWS is a promising inoculation source for CWs that treat saline wastewater.

Synergetic alginate conversion by a microbial consortium of hydrolytic bacteria and methanogens

Sludge, of which alginate-like biomaterial is a major organic component, is an increasing environmental problem. Thus, efficient anaerobic degradation of alginate provides a new method for sludge utilization. In this study, anaerobic alginate hydrolytic bacteria (AHB) were proposed to enrich with methanogens synergetically to reduce the inhibition of intermediate metabolites. The COD of produced methane reached 80.7 ± 1.9% (n = 4) of initial alginate COD. After considering the microbial growth (8%-18% of COD), a good COD balance indicated that alginate was fully consumed and the main final metabolites were methane and CO₂. Methanogenesis could promote alginate conversion by AHB. The enriched bacteria for alginate degradation in this study were different from that of former known AHB. The metabolic pathway of alginate degradation was revealed by metagenomics, in which oligo-alginate lyase was detected in twelve bacteria, and typical carbon metabolic pathways to convert alginate to methane were identified. More studies of bacterial isolation and biofuel production are still needed in the future.

A snapshot of microbial community structures in 20 different field-scale anaerobic bioreactors treating food waste

This study aimed to identify significant factors shaping the microbial populations in biogas plants treating food waste (FW). Twenty full-scale anaerobic acidogenic/methanogenic bioreactors, located at 11 FW treatment facilities, were compared to find patterns in their microbial community structures and potential interactions with the process parameters. Temperature, hydraulic retention time, and organic loading rate were design parameters that systematically influenced the microbial communities. The latter two clearly separated the acidogenic and methanogenic bioreactors. Lactobacillus was the dominant (69.7 ± 19.8%) bacteria in the acidogenic reactors, while hydrogen-utilizing methanogens, such as Methanoculleus (65.1 ± 33.5%), were the dominant archaea in most methanogenic digesters. Defluiviitoga was the dominant (82.7 ± 1.4%) bacteria in the thermophilic digesters, but was also the most abundant (33.1-33.6%) bacteria in dry mesophilic digesters. The two bioreactor categories had lower bacterial diversities, and also higher propionate concentrations (>5 g/L in 4 out of 5 cases), which may impose potential risks for the management of such digesters. The current 'snapshot' of the microbial communities suggests several bacterial and archaeal taxa as potential indicators of bioreactor categories and/or process variables.

Interspecies microbial nexus facilitated methanation of polysaccharidic wastes

Compositional variations in organic wastes influence microbial abundancy and syntrophy during anaerobic digestion (AD), impacting the normal performance of digesters for methanation. Investigation of the microbial dynamics during AD following augmentation with polysaccharidic wastes (PW) revealed the association of effective digester performance and methane yields with the microbial nexus. Dominance of the acidogenic saccharolytic genera, Prevotella, Eubacterium, and Lachnoclostridium, enhanced the utilization of carbohydrates (54%) in PW-augmented digesters. Spearman's rs correlation showed dynamic interspecies interactions among acetogenic syntrophs, and that of iron oxidizers/reducers with acetoclastic and hydrogenotrophic methanogens. Propionate oxidizers in Chloroflexi (i.e., Bellilinea, Levilinea, and Longilinea) exhibited positive associations with acetoclastic methanogens. Increase in the population of acetoclastic methanogens (Methanosaeta, 77% and Methanosarcina, 9%) accelerated the methanogenic activity of PW-augmented digesters by 7 times during the exponential phase, increasing the methane yield (75%) compared to the control. Thus, microbial syntrophy facilitated the effective methanation of PW during AD process.

How the bacterial community of a tannery effluent responds to bioaugmentation with the consortium SFC 500-1. Impact of environmental variables

Bioaugmentation with the consortium SFC 500-1 is a promising alternative to remediate wastewaters, such as tannery effluents. With the aim of assessing the changes produced in response to bioaugmentation, bacterial 16S rDNA genes were sequenced with Illumina MiSeq Platform. Additionally, bacterial and fungal groups were analyzed through standard culture dependent methods. The impact of diverse physico-chemical and microbiological parameters on the prokaryotic diversity was also evaluated throughout. Bacteroidetes, Firmicutes and Proteobacteria, represented together up to 91% of the total number of sequences obtained from the tannery effluent. Diversity decreased immediately after inoculation, due to an increase in the representation of the taxa to which the added consortium belongs. However, bioaugmentation produced no greater variations since only a 10% of unique operational taxonomic units were found in the inoculated treatment. An increase in the abundance of Myroides and a reduction in the representation of Proteiniclasticum and Halomonas were major observed variations. On the other hand, pH and dissolved oxygen constituted main environmental factors affecting the structure of the prokaryotic communities. In all treatments yeasts increased over time, to the detriment of filamentous fungi. Together, data from this report may contribute to the development of improved bioremediation strategies of industrial wastewaters.

Microbial community composition and methanogens' biodiversity during a temperature shift in a methane fermentation chamber

More information on the connection between anaerobic digestion (AD) parameters and composition of the microbial community involved in the AD process is required to gain a better understanding of how a bioreactor functions. The aim of this study was to analyse the composition of microbial communities and the dynamics of methanogens' biodiversity changes during the shift from mesophilic (38°C) to thermophilic (55°C) conditions during biogas production. The total microbial composition was examined via the metagenomic approach based on 16S rRNA gene sequencing, whereas the methanogen communities were analysed using PCR-DGGE (Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis) of mcrA. Even though the temperature is one of the crucial parameters affecting microorganisms involved in the AD process, the results presented here revealed that there were no statistically significant differences in bacterial community composition between the mesophilic and thermophilic phases of the process. The most abundant phyla were found to be Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes. However, the methanogens' community genotypic structure as examined by the PCR-DGGE method changed under thermophilic conditions. The temperature had the strongest impact on the archaeal methanogens in the fermentation chamber directly after implementing the temperature shift. A relatively higher biogas yield and average content of CH₄ in the produced biogas were observed under thermophilic conditions.

Biological pretreatment enhances the activity of functional microorganisms and the ability of methanogenesis during anaerobic digestion

Biological pretreatment can increase the methane production of anaerobic digestion. In this study, stover was pretreated via microbial consortium prior to anaerobic digestion; through 16S rRNA gene and 16S rRNA amplicon sequencing and metatranscriptomic analysis, and the effects of the pretreatment on the microbial community and critical factors of the increased methane production were studied. Microbial community structure was less affected by the pretreatment, which ensures the stable performance of anaerobic digestion. The methane production increased by 62.85% at the peak phase compared to the untreated stover. The activity of Methanosaeta increased from 2.0% to 10.1%, significantly enhancing the ability of the community to capture acetic acid and reduce CO₂ to methane. The main contribution to the increase in methane production was a unique acetyl-CoA synthetase, which showed significant up-regulation (121.8%). This research demonstrated the importance of Methanosaeta and its unique metabolic pathways in anaerobic digestion utilizing a biological pretreatment.

Organic matter rather than salinity as a predominant feature changes performance and microbiome in methanogenic sludge digesters

Due to low digestibility and long retention time of anaerobic sludge digestion, pre-treatment with alkaline/acid has been widely employed to enhance the rate and extent of sludge digestion. Nonetheless, effects of gradient concentrations of alkaline/acid pre-treatments and resulting salinity on digestion performance and sludge microbiome remain poorly understood. To elucidate these effects, both batch- and reactor-experiments were setup with varied feeding sludge. Significant digestion improvement and sludge microbiome changes were observed with alkaline/acid sludge pre-treatment, compared to non-pretreatment controls, e.g., ˜88% increase of carbon removal in sludge digesters. Surprisingly, with the same concentration of influent sludge, no notable change in digestion performance and sludge microbiome was observed in digesters when increasing alkaline/acid concentrations from 0.25 to 0.8 mol/L, and in batch serum bottles with or without NaCl amendment. Consequently, organic compounds dissolved in sludge pre-treatment could be a predominant selective pressure driving the performance and microbiome changes. By contrast, salinity as a consequence of the alkaline/acid pre-treatment could only enrich specific lineages, without altering the overall community profile and function. Together, this study provided insights into specific impacts of major factors on digester performance and sludge microbiome, and shed lights on optimization of sludge digestion.

Evaluation of bacterial association in methane generation pathways of an anaerobic digesting sludge via metagenomic sequencing

Anaerobic digestion, a recently hot technology to produce biogases especially methane generation for biofuel from wastewater, is considered an effective explanation for energy crisis and global pollution threat. A complex microbiome population is present in sludge, which plays an important role in the digestion of complex polymer into simple monomers. 16S rRNA approaches simply are not enough for amplification due to the involvement of extreme complex population. However, Illumina sequencing is a recent powerful technology to reveal the entire microbiome structure and methane generation pathways in anaerobic digestion. Metagenomic sequencing was tested to reveal the microbial structure of a digested sludge from a local wastewater treatment plant in Beijing. The Illumina HiSeq program was used to extract about 5 GB of data for metagenomic analysis. The classification investigation revealed about 97.64% dominancy of bacteria while 1.78% were detected to be archaea using MG-RAST server. The most abundant bacterial communities were reported to be Actinobacteria, Bacteroidetes, Firmicutes and Proteobacteria. Furthermore, the important microbiome involved in methane generation was revealed. The dominant methanogens were detected (Methanosaeta and Methanosarcina), with affiliation of dominant genes involved in acetoclastic methanogenesis in a digesting sludge. The metagenomic analysis showed that microbial structure and methane generation pathways were successfully dissected in an anaerobic digester.

Syntroph diversity and abundance in anaerobic digestion revealed through a comparative core microbiome approach

Anaerobic digestion is an important biotechnology treatment process for conversion of waste to energy. In this study, a comparative core microbiome approach, i.e., determining taxa that are shared in functioning digesters but not shared in non-functioning digesters, was used to determine microbial taxa that could play key roles for effective anaerobic digestion. Anaerobic digester functions were impaired by adding the broad-spectrum antimicrobial triclosan (TCS) or triclocarban (TCC) at different concentrations, and the core microbiomes in both functioning and non-functioning anaerobic digesters were compared. Digesters treated with high (2500 mg/kg) or medium (450 mg/kg) TCS and high (850 mg/kg) TCC concentrations lost their function, i.e., methane production decreased, effluent volatile fatty acid concentrations increased, and pH decreased. Changes in microbial community diversity and compositions were assessed using 16S rRNA gene amplicon sequencing. Microbial richness decreased significantly in non-functioning digesters (p < 0.001). Microbial community compositions in non-functioning digesters significantly differed from those in functioning digesters (p = 0.001, ANOSIM). Microbes identified as potentially key taxa included previously known fatty acid-degrading syntrophs and amino acid-degrading syntrophs. A diverse group of syntrophs detected in this study had low relative abundance in functioning digesters, suggesting the importance of rare microbes in anaerobic digester operation. The comparative microbiome approach used in this study can be applied to other microbial systems where a community-driven biological phenomena can be observed directly.

Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process

BACKGROUND

Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters.

RESULTS

This study quantified microbial immigration from an upstream full-scale anaerobic reactor to downstream activated sludge reactors. A mass balance was applied to 16S rRNA gene amplicon sequencing data to calculate the net growth rates of individual populations in the activated sludge reactors. Among the 1178 observed operational taxonomic units (OTUs), 582 had a positive growth rate, including all the populations with abundance > 0.1%. These active populations collectively accounted for 99% of the total sequences in activated sludge. The remaining 596 OTUs with a growth rate ≤ 0 were classified as inactive populations. All the abundant populations in the upstream anaerobic reactor were inactive in the activated sludge process, indicating a negligible immigration impact. We used a supervised learning regressor to predict environmental parameters based on community composition and compared the prediction accuracy based on either the entire community or the active populations. Temperature was the most predictable parameter, and the prediction accuracy was improved when only active populations were used to train the regressor.

CONCLUSIONS

Calculating growth rate of individual microbial populations in the downstream system provides an effective approach to determine microbial activity and quantify immigration impact. For the studied biological process, a marginal immigration impact was observed, likely due to the significant differences in the growth environments between the upstream and downstream processes. Excluding inactive populations as a result of immigration further enhanced the prediction of key environmental parameters affecting process performance.

Innovative operation of microbial fuel cell-based biosensor for selective monitoring of acetate during anaerobic digestion

Volatile fatty acids (VFAs) especially acetate concentration have been proved to be a sensitive and reliable indicator for many anaerobic processes such as anaerobic digestion (AD). Microbial fuel cells (MFC) have been demonstrated as a promising VFAs sensor due to simple reactor design and operating conditions among microbial electrochemical biosensors. However, the conventional MFC biosensors may fail to distinguish between VFAs and other organics as real digestates containing complex organics and microbes are fed into anode directly. In the present study, an MFC based biosensor was developed and operated in a smart way for selective acetate detection. In the biosensor, acetate ions contained in the AD sample was first fed into the cathode, and then acetic ion transferred through the membrane from the cathode to anode chamber where it was further used as the sole substrate by pre-enriched electroactive biofilm for the current generation. A linear correlation between the current density and acetate concentrations (0.5-20 mM) at varied reaction time (1-5 h) was established. Then, the interference from propionate, butyrate, isobutyrate, and glucose on the performance of the biosensor was evaluated. Furthermore, the influence of sample temperatures (37 and 55 °C) was also studied. Finally, the VFAs content in real AD effluent with this biosensor was measured. The results corresponded well with gas chromatographic measurements. This simple, and reliable biosensor could serve as a promising alternative method for acetate detection in the AD process or any other acetate-rich fluids.

Influence of Pre-Hydrolysis on Sewage Treatment in an Up-Flow Anaerobic Sludge BLANKET (UASB) Reactor: A Review

The up-flow anaerobic sludge blanket (UASB) process has emerged as a promising high-rate anaerobic digestion technology for the treatment of low- to high-strength soluble and complex wastewaters. Sewage, a complex wastewater, contains 30–70% particulate chemical oxygen demand (CODP). These particulate organics degrade at a slower rate than the soluble organics found in sewage. Accumulation of non-degraded suspended solids can lead to a reduction of active biomass in the reactor and hence a deterioration in its performance in terms of acid accumulation and poor biogas production. Hydrolysis of the CODP in sewage prior to UASB reactor will ensure an increased organic loading rate and better UASB performance. While single-stage UASB reactors have been studied extensively, the two-phase full-scale treatment approach (i.e., a hydrolysis unit followed by an UASB reactor) has still not yet been commercialized worldwide. The concept of treating sewage containing particulate organics via a two-phase approach involves first hydrolyzing and acidifying the volatile suspended solids without losing carbon (as methane) in the first reactor and then treating the soluble sewage in the UASB reactor. This work reviews the available literature to outline critical findings related to the treatment of sewage with and without hydrolysis before the UASB reactor.

Oxygen Half-Saturation Constants for Pharmaceuticals in Activated Sludge and Microbial Community Activity under Varied Oxygen Levels

Aeration accounts for the largest energy demand in conventional activated sludge wastewater treatment. Emerging aeration control strategies for energy conservation have significantly reduced operational bulk liquid dissolved oxygen (DO) from above 2 mg/L to at or below 0.5 mg/L. As we move toward low DO treatment processes, there is a need to understand how low DO impacts the kinetics of micropollutant biotransformation. The objective of this study was to characterize the impact of DO concentration on pharmaceutical biotransformation rates via two approaches: (1) Determine oxygen half saturation constants that describe the community-wide impact of DO on biotransformation rates. (2) Evaluate shifts in the microbial community 16S rRNA pool due to DO concentration. Batch experiments were performed at several DO concentrations using biomass from a full-scale wastewater treatment plant. Results reveal that substantial reductions in bulk liquid DO concentrations to 0.5 mg-O₂/L are possible without compromising pharmaceutical biotransformation rates. Sequencing of cDNA generated from community rRNA revealed that diverse, low abundance community members may play important roles in pharmaceutical transformation. The results of this work advance our ability to predict and model the impact of DO on pharmaceutical biotransformations during wastewater treatment and identify taxonomic groups associated with those biotransformations.

Biogeographic Patterns and Assembly Mechanisms of Bacterial Communities Differ Between Habitat Generalists and Specialists Across Elevational Gradients

A core issue in microbial ecology is the need to elucidate the ecological processes and underlying mechanisms involved in microbial community assembly. However, the extent to which these mechanisms differ in importance based on traits of taxa with different niche breadth is poorly understood. Here, we used high-throughput sequencing to examine the relative importance of environmental selection and stochastic processes in shaping soil bacterial sub-communities with different niche breadth (including habitat generalists, specialists and other taxa) across elevational gradients on the subalpine slope of Mount Wutai, Northern China. Our findings suggested that the composition of soil bacterial communities differed significantly different among elevational gradients. According to the niche breadth index, 10.9% of OTUs were defined as habitat generalists (B-value >8.7) and 10.0% of OTUs were defined as habitat specialists (B-value <1.5). Generalists and specialists differed distinctly in diversity and biogeographic patterns across elevational gradients. Environmental selection (deterministic processes) and spatial factors (stochastic processes) seemed to determine the assembly and biogeography of habitat generalists. However, for specialists, deterministic processes strongly influenced the distribution, while stochastic processes were not at play. Environmental drivers for generalists and specialists differed, as did their importance. Elevation, total nitrogen and pH were the main factors determining habitat generalists, and soil water content, nitrate nitrogen and pH had the strongest impacts on specialists. Moreover, variation partitioning analysis revealed that environmental selection had a much greater impact on both generalists (17.7% of pure variance was explained) and specialists (3.6%) than spatial factors. However, generalists had a much stronger response to spatial factors (2.3%) than specialists (0.3%). More importantly, null models of β-diversity suggested that specialists deviated significantly from non-neutral assembly mechanisms (relative null deviation= 0.64–0.74) relative to generalists (0.16–0.65) (P < 0.05). These results indicate that generalists and specialists are governed by different assembly mechanisms and present distinct biogeographical patterns. The large proportion of unexplained variation in specialists (93.3%) implies that very complex assembly mechanisms exist in the assembly of specialists across elevational gradients on the subalpine slope of Mount Wutai. It is essential to understand the microbial community assembly at a more refined level, and to expand the current understanding of microbial ecological mechanisms.

Effects of various feedstocks on isotope fractionation of biogas and microbial community structure during anaerobic digestion

Feedstock type influences bacterial and methanogenic communities in anaerobic digestion. These two communities work tightly to maintain the stability of anaerobic digestion. How to quick report the changes of microbial community structure especially methanogenesis is the key issue for optimizing anaerobic digestion process. In this study, ¹³C isotope fractionations of CH₄ and CO₂ in biogas and microbial community composition were analyzed in 5 different feedstocks. Our results showed that grass silage, maize silage and swine manure fed reactors had similar δ ¹³C values and methanogenic community composition, dominated by Methanosarcinaceae. The lowest δ ¹³CH₄ values were detected in straw and chicken manure fed reactors, reflecting reduced microbial degradation of material or the presence of toxic components in these feedstocks. The straw fed bioreactor lead to low δ ¹³CH₄ values, probably reflecting relatively high levels of the syntrophic acetate oxidizing bacteria, Synergistaceae and Syntrophaceae, which might work collectively with hydrogenotrophic methanogens, resulting in the low δ ¹³CH₄ values in this bioreactor. Significantly, all core microbes in the 5 different feedstock fed bioreactors were either Clostridia species or related to the Synergistaceae (syntrophic acetate oxidizing bacteria).

Comparative metatranscriptomic analysis of anaerobic digesters treating anionic surfactant contaminated wastewater

Three distinct biological reactors fed with synthetic medium (UASB_Control), synthetic medium and linear alkylbenzene sulfonate (LAS; UASB_SL), and real laundry wastewater (UASB_LW) were compared using a metatranscriptomic approach to determine putative bioindicator genes and taxonomies associated to all steps of anaerobic LAS biodegradation pathway. A homemade bioinformatics pipeline combined with an R workflow was developed to perform the RNAseq data analysis. UASB_SL and UASB_LW showed similar values of LAS biological degradation (~47%) and removal (53-55%). Rarefaction analysis revealed that 1-2 million reads were sufficient to access the whole functional capacity. In the first step of LAS biodegradation pathway, fumarate reductase subunit C was detected and taxonomically assigned to the genus Syntrophobacter (0.002% - UASB_SL; 0.0015% - UASB_LW; not detected - UASB_Control). In the second step, many enzymes related to beta-oxidation were observed and most of them with low relative abundance in UASB Control and taxonomically related with Smithella, Acinetobacter and Syntrophorhabdus. For the ring cleavage step, the abundance of 6 OCH CoA hydrolase putative gene was ten times higher in UASB_SL and UASB_LW when compared to UASB_Control, and assigned to Desulfomonile and Syntrophorhabdus. Finally, the adenylylsulfate reductase, taxonomically related with Desulfovibrio and Desulfomonile, was observed in the desulfonation step with the highest relative abundance in UASB_LW.

Process Disturbances in Agricultural Biogas Production—Causes, Mechanisms and Effects on the Biogas Microbiome: A Review

Disturbances of the anaerobic digestion process reduce the economic and environmental performance of biogas systems. A better understanding of the highly complex process is of crucial importance in order to avoid disturbances. This review defines process disturbances as significant changes in the functionality within the microbial community leading to unacceptable and severe decreases in biogas production and requiring an active counteraction to be overcome. The main types of process disturbances in agricultural biogas production are classified as unfavorable process temperatures, fluctuations in the availability of macro- and micronutrients (feedstock variability), overload of the microbial degradation potential, process-related accumulation of inhibiting metabolites such as hydrogen (H2), ammonium/ammonia (NH4+/NH3) or hydrogen sulphide (H2S) and inhibition by other organic and inorganic toxicants. Causes, mechanisms and effects on the biogas microbiome are discussed. The need for a knowledge-based microbiome management to ensure a stable and efficient production of biogas with low susceptibility to disturbances is derived and an outlook on potential future process monitoring and control by means of microbial indicators is provided.

Rare Taxa Exhibit Disproportionate Cell-Level Metabolic Activity in Enriched Anaerobic Digestion Microbial Communities

Microbial communities are composed of populations with vastly different abundances and levels of metabolic and replicative activity, ranging from actively metabolizing and dividing to dormant or nonviable. The 16S rRNA/rDNA ratio is an emerging tool for evaluating cell-level metabolic activity independent of abundance. In this study, we used five long-term enriched model anaerobic digestion (AD) communities to investigate community composition, diversity, structure, and in particular activity based on the rRNA/rDNA ratio. We cross-validated the 16S amplicon-based results using two alternative operational taxonomic unit (OTU) formation methods (conventional 97% sequence similarity and 100% sequence similar zero-radius OTUs by UNOISE3) and compared these to metagenome-derived population genomes and metatranscriptomes. Significant positive correlations were observed between microbial total activity and abundance with both the amplicon- and omic-based methods. All three methods revealed disproportionately high transcription/abundance ratios for some rare taxa but lower ratios for most abundant taxa for all the communities, which was further corroborated by the high replication rate (iRep) of most low-abundance population genomes. IMPORTANCE Variation in microbial activity levels is increasingly being recognized as both an important dimension in community function and a complicating factor in sequencing-based survey methods. This study extends previous reports that rare taxa may contribute disproportionately to community activity in some natural environments, showing that this may also hold in artificially maintained model communities with well-described inputs, outputs, and biochemical functions. These results demonstrate that assessment of activity levels using the rRNA/rDNA ratio is robust across taxonomic unit formation methods and is independently corroborated by omics methods. The results also provide insight into the comparative advantages and disadvantages of different taxonomic unit formation methods in amplicon sequencing studies, showing that UNOISE3 provides comparable microbial diversity, structure, and activity information as the 97% sequence similarity method but potentially loses some phylogenetic diversity and creates more "phantom taxa" (which are present in the RNA pool but not the corresponding DNA pool).

The Potential of Bioelectrochemical Sensor for Monitoring of Acetate During Anaerobic Digestion: Focusing on Novel Reactor Design

Acetate as the dominant fraction of volatile fatty acids (VFAs) is an important intermediate in metabolic pathways of methanogenesis, which could reflect the stability status of anaerobic digestion (AD) process. Bioelectrochemical sensors for environmental or bioprocess monitoring have become increasingly attractive in recent years. Although it was more favorable, several challenges still need to be addressed for acetate detection, including large electrode spacing, low stability, biofouling at the cathode and low detection range. In this study, an innovative biosensor on the basis of a three-chamber microbial electrochemical system was proposed to monitor the acetate during the AD process. In such a system, acetate was first transferred from sample chamber through the anion exchange membrane (AEM) to anode due to the driven force of concentration difference and then oxidized by anodic biofilm as a substrate for the current generation. With such design, the influence of waste properties fluctuation in the cathodic reaction could be avoided. The response of current density to different acetate concentrations was investigated. The selectivity, the influence of the sample temperature and the external resistance were also evaluated. The correlation (R 2 > 0.99) between the current densities and acetate concentrations (up to 160 mM) was established at specific reaction time (from 2 to 5 h). Current densities after 5 h reaction were improving about 20% when the sample temperature was high (e.g., 37 and 55°C). The detection range increased along with the decrease of external resistance. The acetate concentrations of AD effluents as determined by the biosensor where within 24.2% of the ones determined by gas chromatography. Nevertheless, the application of the biosensor for monitoring acetate in environmental samples could still be promising.

Anaerobic Process for Bioenergy Recovery From Dairy Waste: Meta-Analysis and Enumeration of Microbial Community Related to Intermediates Production

Dairy wastes are widely studied for the hydrogen and methane production, otherwise the changes in microbial communities related to intermediate valuable products was not deeply investigated. Culture independent techniques are useful tools for exploring microbial communities in engineered system having new insights into their structure and function as well as potential industrial application. The deep knowledge of the microbiota involved in the anaerobic process of specific waste and by-products represents an essential step to better understand the entire process and the relation of each microbial population with biochemical intermediates and final products. Therefore, this study investigated the microbial communities involved in the laboratory-scale anaerobic digestion of a mixture of mozzarella cheese whey and buttermilk amended with 5% w/v of industrial animal manure pellets. Culture-independent methods by employing high-throughput sequencing and microbial enumerations highlighted that lactic acid bacteria, such as Lactobacillaceae and Streptococcaceae dominated the beginning of the process until about day 14 when a relevant increase in hydrogen production (more than 10 ml H₂ gVS^-1 from days 13 to 14) was observed. Furthermore, during incubation a gradual decrease of lactic acid bacteria was detected with a simultaneous increase of Clostridia, such as Clostridiaceae and Tissierellaceae families. Moreover, archaeal populations in the biosystem were strongly related to inoculum since the non-inoculated samples of the dairy waste mixture had a relative abundance of archaea less than 0.1%; whereas, in the inoculated samples of the same mixture several archaeal genera were identified. Among methanogenic archaea, Methanoculleus was the dominant genus during all the process especially when the methane production occurred, and its relative abundance increased up to 99% at the end of the incubation time highlighting that methane was formed from dairy wastes primarily by the hydrogenotrophic pathway in the reactors.

Mass Spectrometry-Based Microbial Metabolomics: Techniques, Analysis, and Applications

The demand for understanding the roles genes play in biological systems has steered the biosciences into the direction the metabolome, as it closely reflects the metabolic activities within a cell. The importance of the metabolome is further highlighted by its ability to influence the genome, transcriptome, and proteome. Consequently, metabolomic information is being used to understand microbial metabolic networks. At the forefront of this work is mass spectrometry, the most popular metabolomics measurement technique. Mass spectrometry-based metabolomic analyses have made significant contributions to microbiological research in the environment and human disease. In this chapter, we break down the technical aspects of mass spectrometry-based metabolomics and discuss its application to microbiological research.

Understanding microbial ecology can help improve biogas production in AD

454-Pyrosequencing and lipid fingerprinting were used to link anaerobic digestion (AD) process parameters (pH, alkalinity, volatile fatty acids (VFAs), biogas production and methane content) with the reactor microbial community structure and composition. AD microbial communities underwent stress conditions after changes in organic loading rate and digestion substrates. 454-Pyrosequencing analysis showed that, irrespectively of the substrate digested, methane content and pH were always significantly, and positively, correlated with community evenness. In AD, microbial communities with more even distributions of diversity are able to use parallel metabolic pathways and have greater functional stability; hence, they are capable of adapting and responding to disturbances. In all reactors, a decrease in methane content to <30% was always correlated with a 50% increase of Firmicutes sequences (particularly in operational taxonomic units (OTUs) related to Ruminococcaceae and Veillonellaceae). Whereas digesters producing higher methane content (above 60%), contained a high number of sequences related to Synergistetes and unidentified bacterial OTUs. Finally, lipid fingerprinting demonstrated that, under stress, the decrease in archaeal biomass was higher than the bacterial one, and that archaeal Phospholipid etherlipids (PLEL) levels were correlated to reactor performances. These results demonstrate that, across a number of parameters such as lipids, alpha and beta diversity, and OTUs, knowledge of the microbial community structure can be used to predict, monitor, or optimise AD performance.

Terminal restriction fragment length polymorphism is an "old school" reliable technique for swift microbial community screening in anaerobic digestion

The microbial community in anaerobic digestion has been analysed through microbial fingerprinting techniques, such as terminal restriction fragment length polymorphism (TRFLP), for decades. In the last decade, high-throughput 16S rRNA gene amplicon sequencing has replaced these techniques, but the time-consuming and complex nature of high-throughput techniques is a potential bottleneck for full-scale anaerobic digestion application, when monitoring community dynamics. Here, the bacterial and archaeal TRFLP profiles were compared with 16S rRNA gene amplicon profiles (Illumina platform) of 25 full-scale anaerobic digestion plants. The α-diversity analysis revealed a higher richness based on Illumina data, compared with the TRFLP data. This coincided with a clear difference in community organisation, Pareto distribution, and co-occurrence network statistics, i.e., betweenness centrality and normalised degree. The β-diversity analysis showed a similar clustering profile for the Illumina, bacterial TRFLP and archaeal TRFLP data, based on different distance measures and independent of phylogenetic identification, with pH and temperature as the two key operational parameters determining microbial community composition. The combined knowledge of temporal dynamics and projected clustering in the β-diversity profile, based on the TRFLP data, distinctly showed that TRFLP is a reliable technique for swift microbial community dynamics screening in full-scale anaerobic digestion plants.

Interspecies cross-feeding orchestrates carbon degradation in the rumen ecosystem

Because of their agricultural value, there is a great body of research dedicated to understanding the microorganisms responsible for rumen carbon degradation. However, we lack a holistic view of the microbial food web responsible for carbon processing in this ecosystem. Here, we sampled rumen-fistulated moose, allowing access to rumen microbial communities actively degrading woody plant biomass in real time. We resolved 1,193 viral contigs and 77 unique, near-complete microbial metagenome-assembled genomes, many of which lacked previous metabolic insights. Plant-derived metabolites were measured with NMR and carbohydrate microarrays to quantify the carbon nutrient landscape. Network analyses directly linked measured metabolites to expressed proteins from these unique metagenome-assembled genomes, revealing a genome-resolved three-tiered carbohydrate-fuelled trophic system. This provided a glimpse into microbial specialization into functional guilds defined by specific metabolites. To validate our proteomic inferences, the catalytic activity of a polysaccharide utilization locus from a highly connected metabolic hub genome was confirmed using heterologous gene expression. Viral detected proteins and linkages to microbial hosts demonstrated that phage are active controllers of rumen ecosystem function. Our findings elucidate the microbial and viral members, as well as their metabolic interdependencies, that support in situ carbon degradation in the rumen ecosystem.

A combination of proteomics, metagenome-assembled genomes and heterologous gene expression experiments reveals a trophic system for carbon utilization in the moose rumen microbiome and provides insights into phage dynamics in this ecosystem.

Toward Integrative Bacterial Monitoring of Metolachlor Toxicity in Groundwater

Common herbicides such as metolachlor (MET), and their transformation products, are frequently detected in groundwater worldwide. Little is known about the response of groundwater bacterial communities to herbicide exposure, and its potential use for ecotoxicological assessment. The response of bacterial communities exposed to different levels of MET from the Ariège alluvial aquifer (Southwest of France) was investigated in situ and in laboratory experiments. Variations in both chemistry and bacterial communities were observed in groundwater, but T-RFLP analysis did not allow to uncover a pesticide-specific effect on endogenous bacterial communities. To circumvent issues of hydrogeochemical and seasonal variations in situ, groundwater samples from two monitoring wells of the Ariège aquifer with contrasting records of pesticide contamination were exposed to different levels of MET in laboratory experiments. The standard Microtox® acute toxicity assay did not indicate toxic effects of MET, even at 5 mg L-1 (i.e., 1000-fold higher than in contaminated groundwater). Analysis of MET transformation products and compound-specific isotope analysis (CSIA) in laboratory experiments demonstrated MET biodegradation but did not correlate with MET exposure. High-throughput sequencing analysis (Illumina MiSeq) of bacterial communities based on amplicons of the 16S rRNA gene revealed that bacterial community differed mainly by groundwater origin rather than by its response to MET exposure. OTUs correlating with MET addition ranged between 0.4 to 3.6% of the total. Predictive analysis of bacterial functions impacted by pesticides using PICRUSt suggested only minor changes in bacterial functions with increasing MET exposure. Taken together, results highlight MET biodegradation in groundwater, and the potential use of bacterial communities as sensitive indicators of herbicide contamination in aquifers. Although detected effects of MET on groundwater bacterial communities were modest, this study illustrates the potential of integrating DNA- and isotopic analysis-based approaches to improve ecotoxicological assessment of pesticide-contaminated aquifers. GRAPHICAL ABSTRACTAn integrative approach was develop to investigate in situ and in laboratory experiments the response of bacterial communities exposed to different levels of MET from the Ariége alluvial aquifer (Southwest of France).

Insights into the variability of microbial community composition and micropollutant degradation in diverse biological wastewater treatment systems

The biological potential of conventional wastewater treatment plants to remove micropollutants mainly depends on process conditions and the predominant microbial community. To explore this dependence and to connect the occurrence of genera with operating conditions, five pilot-scale reactors with different process conditions were combined into two reactor cascades and fed with the effluent of the primary clarifier of a municipal WWTP. All reactors and the WWTP were analyzed for the removal of 33 micropollutants by LC-MS/MS and the presence of the microbial community using 16S rRNA gene sequencing. The overall removal of the micropollutants was slightly improved (ca. 20%) by the reactor cascades in comparison to the WWTP while certain compounds such as diatrizoate, venlafaxine or diclofenac showed an enhanced removal (ca. 70% in one or both cascades). To explore the diverse bacteria in more detail, the general community was divided into a core and a specialized community. Despite their profoundly different operating parameters (especially redox conditions), the different treatments share a core community consisted of 143 genera (9% of the overall community). Furthermore, the alpha- and beta-biodiversity as well as the occurrence of several genera belonging to the specialized microbial community could be linked to the prevalent process conditions of the individual treatments. Members of the specialized community also correlated with the removal of certain groups of micropollutants. Hence, the comparison of the specialized community with micropollutant removal and operating conditions via correlation analysis is a valuable tool for an extended evaluation of prevalent process conditions. Based on an extended data set this approach could also be used to identify organisms as indicators for operating conditions which are beneficial for an improved removal of specific micropollutants.

Intermittent fasting for microbes: how discontinuous feeding increases functional stability in anaerobic digestion

BACKGROUND

Demand-driven biogas production could play an important role for future sustainable energy supply. However, feeding a biogas reactor according to energy demand may lead to organic overloading and, thus, to process failures. To minimize this risk, digesters need to be actively steered towards containing more robust microbial communities. This study focuses on acetogenesis and methanogenesis as crucial process steps for avoiding acidification. We fed lab-scale anaerobic digesters with volatile fatty acids under various feeding regimes and disturbances. The resulting microbial communities were analyzed on DNA and RNA level by terminal restriction fragment length polymorphism of the mcrA gene, 16S rRNA gene amplicon sequencing, and a [2-13C]-acetate assay. A modified Anaerobic Digestion Model 1 (ADM1) that distinguishes between the acetoclastic methanogens Methanosaeta and Methanosarcina was developed and fitted using experimental abiotic and biotic process parameters.

RESULTS

Discontinuous feeding led to more functional resilience than continuous feeding, without loss in process efficiency. This was attributed to a different microbial community composition. Methanosaeta dominated the continuously fed reactors, while its competitor Methanosarcina was washed out. With discontinuous feeding, however, the fluctuating acetic acid concentrations provided niches to grow and co-exist for both organisms as shown by transcription analysis of the mcrA gene. Our model confirmed the higher functional resilience due to the higher abundance of Methanosarcina based on its higher substrate uptake rate and higher resistance to low pH values. Finally, we applied our model to maize silage as a more complex and practically relevant substrate and showed that our model is likely transferable to the complete AD process.

CONCLUSIONS

The composition of the microbial community determined the AD functional resilience against organic overloading in our experiments. In particular, communities with higher share of Methanosarcina showed higher process stability. The share of these microorganisms can be purposefully increased by discontinuous feeding. A model was developed that enables derivation of the necessary feeding regime for a more robust community with higher share of Methanosarcina.

Study on the bacterial and archaeal community structure and diversity of activated sludge from three wastewater treatment plants

In this study, the bacterial and archaeal communities along with their functions of activated sludge from three wastewater treatment plants were investigated by Illumina MiSeq Platform. The treatment processes were modified A/A/O, DE oxidation ditch and pre-anaerobic carrousel oxidation ditch, respectively. The taxonomic analyses showed that Proteobacteria was the predominant bacterial phylum, and Nitrosospira was the dominant nitrification genus. Candidatus Accumulibacter was abundant in DE oxidation ditch process, and the main archaea communities were methanosaeta-like species which had the capability to anaerobic ammonia oxidation. The results illustrated that anaerobic ammonium oxidation played an important role in the nitrogen metabolism and there might be other unknown phosphate-accumulating organisms (PAOs) performing phosphorus removal in activated sludge. The predicted function analyses indicated that both bacteria and archaea were involved in nitrification, denitrification, ammonification and phosphorus removal processes, and their relative abundance varied metabolic modules differed from each other.

Genetic repertoires of anaerobic microbiomes driving generation of biogas

BACKGROUND

Biogas production is an attractive technology for a sustainable generation of renewable energy. Although the microbial community is fundamental for such production, the process control is still limited to technological and chemical parameters. Currently, most of the efforts on microbial management system (MiMaS) are focused on process-specific marker species and community dynamics, but a practical implementation is in its infancy. The high number of unknown and uncharacterized microorganisms in general is one of the reasons hindering further advancements.

RESULTS

A Biogas Metagenomics Hybrid Assembly (BioMETHA) database, derived from microbiomes of biogas plants, was generated using a dedicated assembly strategy for different metagenomic datasets. Long reads from nanopore sequencing (MinION) were combined with short, more accurate second-generation sequencing reads (Illumina). The hybrid assembly resulted in 231 genomic bins each representing a taxonomic unit with an average completeness of 47%. Functional annotation identified 13,190 non-redundant genes covering roughly 207 k coding sequences. Mapping rates of metagenomics DNA derived from diverse biogas plants and laboratory reactors increased up to 73%. In addition, an EC (enzyme commission) reference sequence collection (ERSC) was generated whose genes are crucial for biogas-related processes, consisting of 235 unique EC numbers organized in 52 metabolic modules. Mapping rates of metatranscriptomic data to this ERSC revealed coverages of up to 93%. Process parameters and imbalances of laboratory reactors could be reconstructed by evaluating abundance of biogas-specific metabolic modules using metatranscriptomic data derived from various fermenter systems.

CONCLUSION

This newly established metagenomic hybrid assembly in combination with an EC reference sequence collection might help to shed light on the microbial dark matter of biogas plants by contributing to the development of a reference for biogas plant microbiome-specific gene sequences. Considering a biogas microbiome as a complex meta-organism expressing a meta-transcriptome, the approach established here could lay the foundation for a function-based microbial management system.

Novel prosthecate bacteria from the candidate phylum Acetothermia

Members of the candidate phylum Acetothermia are globally distributed and detected in various habitats. However, little is known about their physiology and ecological importance. In this study, an operational taxonomic unit belonging to Acetothermia was detected at high abundance in four full-scale anaerobic digesters by 16S rRNA gene amplicon sequencing. The first closed genome from this phylum was obtained by differential coverage binning of metagenomes and scaffolding with long nanopore reads. Genome annotation and metabolic reconstruction suggested an anaerobic chemoheterotrophic lifestyle in which the bacterium obtains energy and carbon via fermentation of peptides, amino acids, and simple sugars to acetate, formate, and hydrogen. The morphology was unusual and composed of a central rod-shaped cell with bipolar prosthecae as revealed by fluorescence in situ hybridization combined with confocal laser scanning microscopy, Raman microspectroscopy, and atomic force microscopy. We hypothesize that these prosthecae allow for increased nutrient uptake by greatly expanding the cell surface area, providing a competitive advantage under nutrient-limited conditions.