Microbial community analysis of anaerobic reactors treating soft drink wastewater

Alternating polarity as a novel strategy for building synthetic microbial communities capable of robust Electro-Methanogenesis

Electro-methanogenic microbial communities can produce biogas with high efficiency and have attracted extensive research interest. In this study an alternating polarity strategy was developed to build electro-methanogenic communities. In two-chamber bioelectrochemical systems amended with activated carbon, the electrode potential was alternated between +0.8 V and -0.4 V vs. standard hydrogen electrode every three days. Cumulative biogas production under alternating polarity increased from 45 L/L/kg-activated carbon after start-up to 125 L/L/kg after the 4th enrichment, significantly higher than that under intermittent cathode (-0.4 V/open circuit), continuous cathode (-0.4 V), and open circuit. The communities assembled under alternating polarity were electroactive and structurally different from those assembled under other conditions. One Methanobacterium population and two Geobacter populations were consistently abundant and active in the communities. Their 16S rRNA was up-regulated by electrode potentials. Bayesian networks inferred close associations between these populations. Overall, electro-methanogenic communities have been successfully assembled with alternating polarity.

Uncovering the metabolic pathway of novel Burkholderia sp. for efficient triclosan degradation and implication: Insight from exogenous bioaugmentation and toxicity pressure

Triclosan (TCS), a synthetic and broad-spectrum antimicrobial agent, is frequently detected in various environmental matrices. A novel TCS degrading bacterial strain, Burkholderia sp. L303, was isolated from local activated sludge. The strain could metabolically degrade TCS up to 8 mg/L, and optimal conditions for TCS degradation were at temperature of 35 °C, pH 7, and an increased inoculum size. During TCS degradation, several intermediates were identified, with the initial degradation occurring mainly through hydroxylation of aromatic ring, followed by dechlorination. Further intermediates such as 2-chlorohydroquinone, 4-chlorocatechol, and 4-chlorophenol were produced via ether bond fission and C-C bond cleavage, which could be further transformed into unchlorinated compounds, ultimately resulting in the complete stoichiometric free chloride release. Bioaugmentation of strain L303 in non-sterile river water demonstrated better degradation than in sterile water. Further exploration of the microbial communities provided insights into the composition and succession of the microbial communities under the TCS stress as well as during the TCS biodegradation process in real water samples, the key microorganisms involved in TCS biodegradation or showing resistance to the TCS toxicity, and the changes in microbial diversity related to exogenous bioaugmentation, TCS input, and TCS elimination. These findings shed light on the metabolic degradation pathway of TCS and highlight the significance of microbial communities in the bioremediation of TCS-contaminated environments.

Validation of 16S rRNA gene sequencing and metagenomics for evaluating microbial immigration in a methanogenic bioreactor

To quantitatively evaluate the impact of microbial immigration from an upstream community on the microbial assembly of a downstream community, an ecological genomics (ecogenomics)-based mass balance (EGMB) model coupled with 16S rRNA gene sequencing was previously developed. In this study, a mock community was used to further validate the EGMB models and demonstrate the feasibility of using metagenome-based EGMB model to reveal both microbial activity and function. The mock community consisting of Aeromonas, Escherichia, and Pseudomonas was fed into a lab-scale methanogenic bioreactor together with dissolved organic substrate. Using qPCR, 16S rRNA gene, 16S rRNA gene copy number normalization (GCN), and metagenome, results showed highly comparable community profiles in the feed. In the bioreactor, Aeromonas and Pseudomonas exhibited negative growth rates throughout the experiment by all approaches. Escherichia's growth rate was negative by most biomarkers but was slightly positive by 16S rRNA gene. Still, all approaches showed a decreasing trend toward negative in the growth rate of Escherichia as reactor operation time increased. Uncultivated populations of phyla Desulfobacterota, Chloroflexi, Actinobacteriota, and Spirochaetota were observed to increase in abundance, suggesting their contribution in degrading the feed biomass. Based on metabolic reconstruction of metagenomes, these populations possessed functions of hydrolysis, fermentation, fatty acid degradation, or acetate oxidation. Overall results supported the application of both 16S rRNA gene- and metagenome-based EGMB models to measure the growth rate of microbes in the bioreactor, and the latter had advantage in providing insights into the microbial functions of uncultivated populations.

Characterization of microbial communities in anaerobic acidification reactors fed with casein and/or lactose

Abstract

Protein-rich agro-industrial waste streams are high in organic load and represent a major environmental problem. Anaerobic digestion is an established technology to treat these streams; however, retardation of protein degradation is frequently observed when carbohydrates are present. This study investigated the mechanism of the retardation by manipulating the carbon source fed to a complex anaerobic microbiota and linking the reactor performance to the variation of the microbial community. Two anaerobic acidification reactors were first acclimated either to casein (CAS reactor) or lactose (LAC reactor), and then fed with mixtures of casein and lactose. Results showed that when lactose was present, the microbial community acclimated to casein shifted from mainly Chloroflexi to Proteobacteria and Firmicutes, the degree of deamination in the CAS reactor decreased from 77 to 15%, and the VFA production decreased from 75 to 34% of the effluent COD. A decrease of 75% in protease activity and 90% in deamination activity of the microbiota was also observed. The microorganisms that can ferment both proteins and carbohydrates were predominant in the microbial community, and from a thermodynamical point of view, they consumed carbohydrates prior to proteins. The frequently observed negative effect of carbohydrates on protein degradation can be mainly attributed to the substrate preference of these populations.

Keypoints

• The presence of lactose shifted the microbial community and retarded anaerobic protein degradation.

• Facultative genera were dominant in the presence and absence of lactose.

• Substrate-preference caused retardation of anaerobic protein degradation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12132-5.

Mechanistic insight into co-metabolic dechlorination of hexachloro-1,3-butadiene in Dehalococcoides

Hexachloro-1,3-butadiene (HCBD) as one of emerging persistent organic pollutants (POPs) poses potential risk to human health and ecosystems. Organohalide-respiring bacteria (OHRB)-mediated reductive dehalogenation represents a promising strategy to remediate HCBD-contaminated sites. Nonetheless, information on the HCBD-dechlorinating OHRB and their dechlorination pathways remain unknown. In this study, both in vivo and in vitro experiments, as well as quantum chemical calculation, were employed to successfully identify and characterize the reductive dechlorination of HCBD by Dehalococcoides. Results showed that some Dehalococcoides extensively dechlorinated HCBD to (E)-1,2,3-tri-CBD via (E)-1,1,2,3,4-penta-CBD and (Z,E)-1,2,3,4-tetra-CBD in a co-metabolic way. Both qPCR and 16S rRNA gene amplicon sequencing analyses suggested that the HCBD-dechlorinating Dehalococcoides coupled their cell growth with dechlorination of perchloroethene (PCE), rather than HCBD. The in vivo and in vitro ATPase assays indicated ≥78.89% decrease in ATPase activity upon HCBD addition, which suggested HCBD inhibition on ATPase-mediated energy harvest and provided rationality on the Dehalococcoides-mediated co-metabolic dechlorination of HCBD. Interestingly, dehalogenation screening of organohalides with the HCBD-dechlorinating enrichment cultures showed that debromination of bromodichloromethane (BDCM) was active in the in vitro RDase assays but non-active in the in vivo experiments. Further in vitro assays of hydrogenase activity suggested that significant inhibition of BDCM on the hydrogenase activity could block electron derivation from H₂ for consequent reduction of organohalides in the in vivo experiments. Therefore, our results provided unprecedented insight into metabolic, co-metabolic and RDase-active-only dehalogenation of varied organohalides by specific OHRB, which could guide future screening of OHRB for remediation of sites contaminated by HCBD and other POPs.

Identification of key microorganisms in facultative stabilization ponds from dairy industries, using metagenomics

Wastewater stabilization ponds are a natural form of wastewater treatment. Their low operation and maintenance costs have made them popular, especially in developing countries. In these systems, effluents are retained for long periods of time, allowing the microbial communities present in the ponds to degrade the organic matter present, using both aerobic and anaerobic processes. Even though these systems are widespread in low income countries, there are no studies about the microorganisms present in them and how they operate. In this study, we analised the microbial communities of two serial full-scale stabilization ponds systems using whole genome shotgun sequencing. First, a taxonomic profiling of the reads was performed, to estimate the microbial diversity. Then, the reads of each system were assembled and binned, allowing the reconstruction of 110 microbial genomes. A functional analysis of the genomes allowed us to find how the main metabolic pathways are carried out, and we propose several organisms that would be key to this kind of environment, since they play an important role in these metabolic pathways. This study represents the first genome-centred approach to understand the metabolic processes in facultative ponds. A better understanding of these microbial communities and how they stabilize the effluents of dairy industries is necessary to improve them and to minimize the environmental impact of dairy industries wastewater.

Disentangling the syntrophic electron transfer mechanisms of Candidatus geobacter eutrophica through electrochemical stimulation and machine learning

Interspecies hydrogen transfer (IHT) and direct interspecies electron transfer (DIET) are two syntrophy models for methanogenesis. Their relative importance in methanogenic environments is still unclear. Our recent discovery of a novel species Candidatus Geobacter eutrophica with the genetic potential of IHT and DIET may serve as a model species to address this knowledge gap. To experimentally demonstrate its DIET ability, we performed electrochemical enrichment of Ca. G. eutrophica-dominating communities under 0 and 0.4 V vs. Ag/AgCl based on the presumption that DIET and extracellular electron transfer (EET) share similar metabolic pathways. After three batches of enrichment, Geobacter OTU650, which was phylogenetically close to Ca. G. eutrophica, was outcompeted in the control but remained abundant and active under electrochemical stimulation, indicating Ca. G. eutrophica's EET ability. The high-quality draft genome further showed high phylogenomic similarity with Ca. G. eutrophica, and the genes encoding outer membrane cytochromes and enzymes for hydrogen metabolism were actively expressed. A Bayesian network was trained with the genes encoding enzymes for alcohol metabolism, hydrogen metabolism, EET, and methanogenesis from dominant fermentative bacteria, Geobacter, and Methanobacterium. Methane production could not be accurately predicted when the genes for IHT were in silico knocked out, inferring its more important role in methanogenesis. The genomics-enabled machine learning modeling approach can provide predictive insights into the importance of IHT and DIET.

Water content as a primary parameter determines microbial reductive dechlorination activities in soil

Organohalide-respiring bacteria (OHRB) remove halogens from a variety of organohalides, which have been utilized for in situ remediation of different contaminated sites, e.g., groundwater, sediment and soil. Nonetheless, dehalogenation activities of OHRB and consequent remediation efficiencies can be synergistically affected by water content, soil type and inoculated/indigenous OHRB, which need to be disentangled to identify the key driving parameter and to elucidate the underlying mechanism. In this study, we investigated the impacts of water content (0-100%), soil type (laterite, brown soil and black soil) and inoculated OHRB (Dehalococcoides mccartyi CG1 and a river sediment culture) on reductive dechlorination of perchloroethene (PCE) and polychlorinated biphenyls (PCBs), as well as on associated microbial communities. Results suggested that the water content as a primary rate-limiting parameter governed dechlorination activities in environmental matrices, particularly in the soil, possibly through mediation of cell-to-organohalide mobility of OHRB. By contrast, interestingly, organohalide-dechlorinating microbial communities were predominantly clustered based on soil types, rather than water contents or inoculated OHRB. This study provided knowledge on the impacts of major parameters on OHRB-mediated reductive dechlorination in groundwater, sediment and soil for future optimization of in situ bioremediation of organohalides.

Microbial Communities in Methane Cycle: Modern Molecular Methods Gain Insights into Their Global Ecology

The role of methane as a greenhouse gas in the concept of global climate changes is well known. Methanogens and methanotrophs are two microbial groups which contribute to the biogeochemical methane cycle in soil, so that the total emission of CH4 is the balance between its production and oxidation by microbial communities. Traditional identification techniques, such as selective enrichment and pure-culture isolation, have been used for a long time to study diversity of methanogens and methanotrophs. However, these techniques are characterized by significant limitations, since only a relatively small fraction of the microbial community could be cultured. Modern molecular methods for quantitative analysis of the microbial community such as real-time PCR (Polymerase chain reaction), DNA fingerprints and methods based on high-throughput sequencing together with different “omics” techniques overcome the limitations imposed by culture-dependent approaches and provide new insights into the diversity and ecology of microbial communities in the methane cycle. Here, we review available knowledge concerning the abundances, composition, and activity of methanogenic and methanotrophic communities in a wide range of natural and anthropogenic environments. We suggest that incorporation of microbial data could fill the existing microbiological gaps in methane flux modeling, and significantly increase the predictive power of models for different environments.

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.

Enhanced Microbial Interactions and Deterministic Successions During Anoxic Decomposition of Microcystis Biomass in Lake Sediment

Microcystis biomass remineralization after blooming represents a hotspot of nutrient recycling in eutrophic lakes. Because Microcystis blooms are massively deposited on lake sediments, resulting in anoxic conditions, it is important to understand the response and role of benthic microbial communities during the anoxic decomposition of Microcystis in freshwater lakes. In the present study, we employed a microcosm method, combined with high-throughput sequencing, functional prediction, and network analysis, to investigate microbial succession during the short-term (30 days) anaerobic decomposition of Microcystis in a eutrophic sediment. Continuous accumulation of CH4 and CO2 and increasing relative abundance of methanogens were observed during the incubation. The microbial community composition (MCC) significantly changed after addition of Microcystis biomass, with a shift in the community from a stochastic to a functional, deterministic succession. Families, including Clostridiaceae, Rhodocyclaceae, Rikenellaceae, Peptostreptococcaceae, Syntrophomonadaceae, Lachnospiraceae, and Methanosarcinaceae, were predominantly enriched and formed diverse substitution patterns, suggesting a synergistic action of these family members in the decomposition of Microcystis biomass. Importantly, intense species-to-species interactions and weak resistance to disturbance were observed in the microbial community after Microcystis biomass addition. Collectively, these results suggest that the addition of Microcystis induce phylogenetic clustering and structure instability in the sediment microbial community and the synergistic interactions among saprotrophic bacteria play a key role in Microcystis biomass remineralization.

Molecular microbial ecology of stable versus failing rice straw anaerobic digesters

Waste rice straw (RS) is generated in massive quantities around the world and is often burned, creating greenhouse gas and air quality problems. Anaerobic digestion (AD) may be a better option for RS management, but RS is presumed to be comparatively refractory under anaerobic conditions without pre-treatment or co-substrates. However, this presumption assumes frequent reactor feeding regimes but less frequent feeding may be better for RS due to slow hydrolysis rates. Here, we assess how feeding frequency (FF) and organic loading rate (OLR) impacts microbial communities and biogas production in RS AD reactors. Using 16S rDNA amplicon sequencing and bioinformatics, microbial communities from five bench-scale bioreactors were characterized. At low OLR (1.0 g VS l-1  day-1 ), infrequently fed units (once every 21 days) had higher specific biogas yields than more frequent feeding (five in 7 days), although microbial community diversities were statistically similar (P > 0.05; ANOVA with Tukey comparison). In contrast, an increase in OLR to 2.0 g VS l-1  day-1 significantly changed Archaeal and fermenting Eubacterial sub-communities and the least frequency fed reactors failed. 'Stable' reactors were dominated by Methanobacterium, Methanosarcina and diverse Bacteroidetes, whereas 'failed' reactors saw shifts towards Clostridia and Christensenellaceae among fermenters and reduced methanogen abundances. Overall, OLR impacted RS AD microbial communities more than FF. However, combining infrequent feeding and lower OLRs may be better for RS AD because of higher specific yields.

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.

Effects of the Wastewater Flow Rate on Interactions between the Genus Nitrosomonas and Diverse Populations in an Activated Sludge Microbiome

The present study characterized the interactions of microbial populations in activated sludge systems during the operational period after an increase in the wastewater flow rate and consequential ammonia accumulation using a 16S rRNA gene sequencing-based network analysis. Two hundred microbial populations accounting for 81.8% of the total microbiome were identified. Based on a co-occurrence analysis, Nitrosomonas-type ammonia oxidizers had one of the largest number of interactions with diverse bacteria, including a bulking-associated Thiothrix organism. These results suggest that an increased flow rate has an impact on constituents by changing ammonia concentrations and also that Nitrosomonas- and Thiothrix-centric responses are critical for ammonia removal and microbial community recovery.

Novel Geobacter species and diverse methanogens contribute to enhanced methane production in media-added methanogenic reactors

To determine whether the addition of conductive materials could enhance methane production by direct interspecies electron transfer (DIET), we operated three anaerobic reactors amended with non-conductive (ceramic) or conductive materials (anthracite and granular activated carbon (GAC)). Throughout eight months of operation, ethanol was consistently detected as the major fermentation product. The specific yield in the anthracite and GAC-added reactors increased by 31.5% and 43.3%, respectively, compared to the ceramic-added reactor. 16S rRNA gene sequencing results indicated Geobacter was dominant (up to 55% of total sequences), whereas acids-degrading syntrophic bacteria were low in abundance (<2%). Using metagenomic analysis, the draft genome of the dominant Geobacter population (bin GAC1) was reconstructed and observed to possess genetic abilities of ethanol oxidation, hydrogen production, and extracellular electron transfer, and represented a phylogenetically novel Geobacter species. While Methanosaeta was the dominant methanogen, reactors containing conductive materials harbored more diverse and abundant archaeal populations, as revealed by FISH, qPCR, and metagenomics. Our findings suggested that a novel Geobacter population could oxidize ethanol and employed both hydrogen transfer and DIET depending on the accessibility of conductive materials. Thermodynamic advantages of DIET over hydrogen production could lead to enhanced methane production in reactors with conductive materials.

Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake

Massive partial sequencing of 16S rRNA genes has become the predominant tool used for studying microbial ecology. However, determining which hypervariable regions and primer sets should be used for screening microbial communities requires extensive investigation if controversial results are to be avoided. Here, the performances of different variable regions of the 16S rRNA gene on bacterial diversity studies were evaluated in silico with respect to the SILVA non-redundant reference database (SILVA SSU Ref 123NR), and subsequently verified using samples from Lake Taihu in China, a eutrophic lake. We found that the bacterial community composition results were strongly impacted by the different V regions. The results show that V1-V2 and V1-V3 regions were the most reliable regions in the full-length 16S rRNA sequences, while most V3 to V6 regions (including V3, V4, V3-V4, V5, V4-V5, V6, V3-V6, V4-V6, and V5-V6) were more closely aligned with the SILVA SSU Ref 123NR database. Overall, V4 was the most prominent V region for achieving good domain specificity, higher coverage and a broader spectrum in the Bacteria domain, as confirmed by the validation experiments. S-D-Bact-0564-a-S-15/S-D-Bact-0785-b-A-18 is, therefore, a promising primer set for surveying bacterial diversity in eutrophic lakes.

A Single-Granule-Level Approach Reveals Ecological Heterogeneity in an Upflow Anaerobic Sludge Blanket Reactor

Upflow anaerobic sludge blanket (UASB) reactor has served as an effective process to treat industrial wastewater such as purified terephthalic acid (PTA) wastewater. For optimal UASB performance, balanced ecological interactions between syntrophs, methanogens, and fermenters are critical. However, much of the interactions remain unclear because UASB have been studied at a “macro”-level perspective of the reactor ecosystem. In reality, such reactors are composed of a suite of granules, each forming individual micro-ecosystems treating wastewater. Thus, typical approaches may be oversimplifying the complexity of the microbial ecology and granular development. To identify critical microbial interactions at both macro- and micro- level ecosystem ecology, we perform community and network analyses on 300 PTA–degrading granules from a lab-scale UASB reactor and two full-scale reactors. Based on MiSeq-based 16S rRNA gene sequencing of individual granules, different granule-types co-exist in both full-scale reactors regardless of granule size and reactor sampling depth, suggesting that distinct microbial interactions occur in different granules throughout the reactor. In addition, we identify novel networks of syntrophic metabolic interactions in different granules, perhaps caused by distinct thermodynamic conditions. Moreover, unseen methanogenic relationships (e.g. “Candidatus Aminicenantes” and Methanosaeta) are observed in UASB reactors. In total, we discover unexpected microbial interactions in granular micro-ecosystems supporting UASB ecology and treatment through a unique single-granule level approach.

Enrichment and characterization of microbial consortia degrading soluble microbial products discharged from anaerobic methanogenic bioreactors

Soluble microbial products (SMP) produced in bioprocesses have been known as a main cause to decrease treatment efficiency, lower effluent quality, and promote membrane fouling in water reclamation plants. In this study, biological degradation of SMP using selectively enriched microbial consortia in a down-flow hanging sponge (DHS) reactor was introduced to remove SMP discharged from anaerobic methanogenic reactors. On average, 68.9-87.5% SMP removal was achieved by the enriched microbial consortia in the DHS reactor for >800 days. The influent SMP fed to the DHS reactor exhibited a bimodal molecular weight (MW) distribution with 14-20 kDa and <4 kDa. Between these two types of SMP, the small MW SMP were biodegraded in the upper part of the reactor, together with most of the large MW SMP. Using 16S rRNA gene pyrosequencing technology, the microbial community composition and structure were characterized and correlated with operational factors, such as hydraulic retention time, organic loading rate, and removal of soluble chemical oxygen demand at different depths of the reactor, by performing network and redundancy analyses. The results revealed that Saprospiraceae was strongly correlated to the increasing SMP loading condition, indicating positive co-occurrences with neighboring bacterial populations. Different microbial diversity along with the depth of the reactor implies that stratified microbial communities could participate in the process of SMP degradation. Taken together, these observations indicate that the spatial and temporal variability of the enriched microbial community in the DHS reactor could effectively treat SMP with respect to changes in the operational factors.