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.

Impacts of draw solutes on the fate of tetracycline in an osmotic membrane bioreactor: Role of the combination between membrane fouling and microorganisms.

Osmotic membrane bioreactors (OMBRs) are considered a suitable technology for treating wastewater containing tetracycline due to their high rejection and biodegradation efficiency. However, the impact of membrane fouling layer (i.e., chemical composition, microbial composition, and formation) on the filtration and biodegradation of tetracycline is still unclear. Herein, the effects of draw solute concentration and type on the formation of a membrane fouling layer for tetracycline filtration and its relationship with microbial activity were investigated. The results showed that over 99% of tetracycline was retained on the feed side by membrane rejection, and the fouling layer played an important role in tetracycline filtration. Specifically, membrane foulants resulted in a more hydrophilic membrane facilitating tetracycline filtration, while the tetracycline-degrading genera from the fouled membrane promoted tetracycline degradation. The structure equation model showed that tetracycline filtration dominated by electrostatic repulsion between tetracycline and the fouled membrane was more important than tetracycline degradation for tetracycline removal (path coefficient of 0.655 vs. 0.395). This study provided insights into the combined effect of membrane foulants and microorganisms on tetracycline removal.

Shedding light on the transfer of tetracycline in forward osmosis through experimental investigation and machine learning modeling.

Tetracycline in wastewater can pose adverse impacts on the environment and human health. Forward osmosis (FO) is a promising method to reject antibiotics due to its low energy demand and high rejection rate. Tetracycline rejection during FO is a complicated process. Mechanistic models have been developed to describe antibiotic rejection by the FO membrane under ideal conditions but cannot be applied to real wastewater. Herein, the effects of draw concentration, pH, and solute type on the fate of tetracycline during FO were investigated by combining experimentation, factor analysis, and artificial neural network (ANN) modeling. High draw concentrations led to high convection that favored tetracycline diffusion. Low draw pH helped reject antibiotics potentially due to the decreased tortuosity and pore size of the FO membrane. When different draw solutes were tested, both convection and electrostatic interaction exerted effects on tetracycline retention on the FO membrane surface, and steric hindrance could further affect the amount of tetracycline in the draw solution. Exploratory factor analysis (EFA) showed that tetracycline rejection was a combined result of convection, steric hindrance, and electrostatic interactions. Path analysis revealed the significant roles of initial conductivity and draw pH in tetracycline rejection. Eight representative input variables were selected from 13 observed explanatory variables using redundancy analysis (RDA), based on which an ANN was trained and successfully predicted tetracycline diffusion and transfer through the FO membrane. These results have provided practical and predictive insights in the development of FO processes for efficient treatment of pharmaceutical wastewater.

Linking population dynamics to microbial kinetics for hybrid modeling of bioelectrochemical systems.

Mechanistic and data-driven models have been developed to provide predictive insights into the design and optimization of engineered bioprocesses. These two modeling strategies can be combined to form hybrid models to address the issues of parameter identifiability and prediction interpretability. Herein, we developed a novel and robust hybrid modeling strategy by incorporating microbial population dynamics into model construction. The hybrid model was constructed using bioelectrochemical systems (BES) as a platform system. We collected 77 samples from 13 publications, in which the BES were operated under diverse conditions, and performed holistic processing of the 16S rRNA amplicon sequencing data. Community analysis revealed core populations composed of putative electroactive taxa Geobacter, Desulfovibrio, Pseudomonas, and Acinetobacter. Primary Bayesian networks were trained with the core populations and environmental parameters, and directed Bayesian networks were trained by defining the operating parameters to improve the prediction interpretability. Both networks were validated with Bray-Curtis similarly, relative root-mean-square error (RMSE), and a null model. A hybrid model was developed by first building a three-population mechanistic component and subsequently feeding the estimated microbial kinetic parameters into network training. The hybrid model generated a simulated community that shared a Bray-Curtis similarity of 72% with the actual microbial community at the genus level and an average relative RMSE of 7% for individual taxa. When examined with additional samples that were not included in network training, the hybrid model achieved accurate prediction of current production with a relative error-based RMSE of 0.8 and outperformed the data-driven models. The genomics-enabled hybrid modeling strategy represents a significant step toward robust simulation of a variety of engineered bioprocesses.

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.

Ecogenomics-Based Mass Balance Model Reveals the Effects of Fermentation Conditions on Microbial Activity.

Fermentation of waste activated sludge (WAS) is an alternative approach to reduce solid wastes while providing valuable soluble products, such as volatile fatty acids and alcohols. This study systematically identified optimal fermentation conditions and key microbial populations by conducting two sets of experiments under different combinations of biochemical and physical parameters. Based on fermentation product concentrations, methane production, and solid removal, fermentation performance was enhanced under the combined treatments of inoculum heat shock (>60°C), pH 5, 55°C, and short solid retention time (<10 days). An ecogenomics-based mass balance (EGMB) approach was used to determine the net growth rates of individual microbial populations, and classified them into four microbial groups: known syntrophs, known methanogens, fermenters, and WAS-associated populations. Their growth rates were observed to be affected by the treatment conditions. The growth rates of syntrophs and fermenters, such as Syntrophomonas and Parabacteroides increased with a decrease in SRT. In contrast, treatment conditions, such as inoculum heat shock and high incubation temperature inhibited the growth of WAS-associated populations, such as Terrimonas and Bryobacter. There were also populations insensitive to the treatment conditions, such as those related to Microbacter and Rikenellaceae. Overall, the EGMB approach clearly revealed the ecological roles of important microbial guilds in the WAS fermentation system, and guided the selection of optimal conditions for WAS fermentation in future pilot-scale operation.

Nexus of Stochastic and Deterministic Processes on Microbial Community Assembly in Biological Systems.

Microbial community assembly in engineered biological systems is often simultaneously influenced by stochastic and deterministic processes, and the nexus of these two mechanisms remains to be further investigated. Here, three lab-scale activated sludge reactors were seeded with identical inoculum and operated in parallel under eight different sludge retention time (SRT) by sequentially reducing the SRT from 15 days to 1 day. Using 16S rRNA gene amplicon sequencing data, the microbial populations at the start-up (15-day SRT) and SRT-driven (≤10-day SRT) phases were observed to be noticeably different. Clustering results demonstrated ecological succession at the start-up phase with no consistent successional steps among the three reactors, suggesting that stochastic processes played an important role in the community assembly during primary succession. At the SRT-driven phase, the three reactors shared 31 core operational taxonomic units (OTUs). Putative primary acetate utilizers and secondary metabolizers were proposed based on K-means clustering, network and synchrony analysis. The shared core populations accounted for 65% of the total abundance, indicating that the microbial communities at the SRT-driven phase were shaped predominantly by deterministic processes. Sloan's Neutral model and a null model analysis were performed to disentangle and quantify the relative influence of stochastic and deterministic processes on community assembly. The increased estimated migration rate in the neutral community model and the higher percentage of stochasticity in the null model implied that stochastic community assembly was intensified by strong deterministic factors. This was confirmed by the significantly different α- and ß-diversity indices at SRTs shorter than 2 days and the observation that over half of the core OTUs were unshared or unsynchronized. Overall, this study provided quantitative insights into the nexus of stochastic and deterministic processes on microbial community assembly in a biological process.

Mainstream upflow nitritation-anammox system with hybrid anaerobic pretreatment: Long-term performance and microbial community dynamics.

Mainstream nitritation-anammox is of strong interest to energy- and resource-efficient domestic wastewater treatment. However, there lack in-depth studies of pretreatment, tests of actual wastewater, and examination of long-term performance. Herein, an upflow nitritation-anammox granular reactor has been investigated to treat primary effluent with a hybrid anaerobic reactor (HAR) as pretreatment for more than 300 days. This system achieved 92% of COD removal, 75% of which was accomplished by the HAR, and had an average final effluent COD concentration of 22 mg L-1. More than 90% of ammonium was removed in the nitritation-anammox reactor, achieving a nitrogen removal rate of 81.0 g N m-3 d-1 in the last stage. The accumulation of sulfate-reducing bacteria in the HAR evidenced the effect of sulfate on COD removal and subsequent nitrogen removal. Anammox bacteria (predominantly Ca. Jettenia asiatica) accounted for up to 40.2% of total granular communities, but their abundance decreased over time in the suspended communities. The dynamics of major metabolisms and functional genes involved in nitrogen conversion were predicted by PICRUSt based on the taxonomic data, providing more insights into the functions of the microbial communities. These results have demonstrated the effectiveness and importance of anaerobic pretreatment to successful mainstream nitritation-anammox.

Microbial reduction of vanadium (V) in groundwater: Interactions with coexisting common electron acceptors and analysis of microbial community.

Vanadium (V) pollution in groundwater has posed serious risks to the environment and public health. Anaerobic microbial reduction can achieve efficient and cost-effective remediation of V(V) pollution, but its interactions with coexisting common electron acceptors such as NO3-, Fe3+, SO42- and CO2 in groundwater remain unknown. In this study, the interactions between V(V) reduction and reduction of common electron acceptors were examined with revealing relevant microbial community and identifying dominant species. The results showed that the presence of NO3- slowed down the removal of V(V) in the early stage of the reaction but eventually led to a similar reduction efficiency (90.0% ± 0.4% in 72-h operation) to that in the reactor without NO3-. The addition of Fe3+, SO42-, or CO2 decreased the efficiency of V(V) reduction. Furthermore, the microbial reduction of these coexisting electron acceptors was also adversely affected by the presence of V(V). The addition of V(V) as well as the extra dose of Fe3+, SO42- and CO2 decreased microbial diversity and evenness, whereas the reactor supplied with NO3- showed the increased diversity. High-throughput 16S rRNA gene pyrosequencing analysis indicated the accumulation of Geobacter, Longilinea, Syntrophobacter, Spirochaeta and Anaerolinea, which might be responsible for the reduction of multiple electron acceptors. The findings of this study have demonstrated the feasibility of anaerobic bioremediation of V(V) and the possible influence of coexisting electron acceptors commonly found in groundwater.

Unravelling and Reconstructing the Nexus of Salinity, Electricity, and Microbial Ecology for Bioelectrochemical Desalination.

Microbial desalination cells (MDCs) are an emerging concept for simultaneous water/wastewater treatment and energy recovery. The key to developing MDCs is to understand fundamental problems, such as the effects of salinity on system performance and the role of microbial community and functional dynamics. Herein, a tubular MDC was operated under a wide range of salt concentrations (0.05-4 M), and the salinity effects were comprehensively examined. The MDC generated higher current with higher salt concentrations in the desalination chamber. When fed with 4 M NaCl, the MDC achieve a current density of 300 A m-3 (anode volume), which was one of the highest among bioelectrochemical system studies. Community analysis and electrochemical measurements suggested that electrochemically active bacteria Pseudomonas and Acinetobacter transferred electrons extracellularly via electron shuttles, and the consequent ion migration led to high anode salinities and conductivity that favored their dominance. Predictive functional dynamics and Bayesian networks implied that the taxa putatively not capable of extracellular electron transfer (e.g., Bacteroidales and Clostridiales) might indirectly contribute to bioelectrochemical desalination. By integrating the Bayesian network with logistic regression, current production was successfully predicted from taxonomic data. This study has demonstrated uncompromised system performance under high salinity and thus has highlighted the potential of MDCs as an energy-efficient technology to address water-energy challenges. The statistical modeling approach developed in this study represents a significant step toward understating microbial communities and predicting system performance in engineered biological systems.

Platinum Group Metal-free Catalysts for Hydrogen Evolution Reaction in Microbial Electrolysis Cells.

Hydrogen gas is a green energy carrier with great environmental benefits. Microbial electrolysis cells (MECs) can convert low-grade organic matter to hydrogen gas with low energy consumption and have gained a growing interest in the past decade. Cathode catalysts for the hydrogen evolution reaction (HER) present a major challenge for the development and future applications of MECs. An ideal cathode catalyst should be catalytically active, simple to synthesize, durable in a complex environment, and cost-effective. A variety of noble-metal free catalysts have been developed and investigated for HER in MECs, including Nickel and its alloys, MoS2 , carbon-based catalysts and biocatalysts. MECs in turn can serve as a research platform to study the durability of the HER catalysts. This personal account has reviewed, analyzed, and discussed those catalysts with an emphasis on synthesis and modification, system performance and potential for practical applications. It is expected to provide insights into the development of HER catalysts towards MEC applications.

Effects of electron acceptors on removal of antibiotic resistant Escherichia coli, resistance genes and class 1 integrons under anaerobic conditions.

Anaerobic biotechnologies can effectively remove antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs), but there is a need to better understand the mechanisms. Here we employ bioelectrochemical systems (BES) as a platform to investigate the fate of a native tetracycline and sulfonamide-resistant Escherichia coli strain and its ARGs. The E. coli strain carrying intI1, sulI and tet(E) was isolated from domestic wastewater and dosed into a tubular BES. The BES was first operated as a microbial fuel cell (MFC), with aeration in the cathode, which resulted in enhanced removal of E. coli and ARGs by ~2 log (i.e., order of magnitude) when switched from high current to open circuit operation mode. The BES was then operated as a microbial electrolysis cell (MEC) to exclude the effects of oxygen diffusion, and the removal of E. coli and ARGs during the open circuit configuration was again 1-2 log higher than that at high current mode. Significant correlations of E. coli vs. current (R(2)=0.73) and ARGs vs. E. coli (R(2) ranged from 0.54 to 0.87), and the fact that the BES substrate contained no electron acceptors, implied that the persistence of the E. coli and its ARGs was determined by the availability of indigenous electron acceptors in the BES, i.e., the anode electrode or the electron shuttles generated by the exoelectrogens. Subsequent experiments with pure-culture tetracycline and sulfonamide-resistant E. coli being incubated in a two-chamber MEC and serum bottles demonstrated that the E. coli could survive by respiring anode electrode and/or electron shuttles released by exoelectrogens, and ARGs persisted with their host E. coli.

Bioelectrochemical production of hydrogen in an innovative pressure-retarded osmosis/microbial electrolysis cell system: experiments and modeling.

BACKGROUND: While microbial electrolysis cells (MECs) can simultaneously produce bioelectrochemical hydrogen and treat wastewater, they consume considerable energy to overcome the unfavorable thermodynamics, which is not sustainable and economically feasible in practical applications. This study presents a proof-of-concept system in which hydrogen can be produced in an MEC powered by theoretically predicated energy from pressure-retarded osmosis (PRO). The system consists of a PRO unit that extracts high-quality water and generates electricity from water osmosis, and an MEC for organic removal and hydrogen production. The feasibility of the system was demonstrated using simulated PRO performance (in terms of energy production and effluent quality) and experimental MEC results (e.g., hydrogen production and organic removal). RESULTS: The PRO and MEC models were proven to be valid. The model predicted that the PRO unit could produce 485 mL of clean water and 579 J of energy with 600 mL of draw solution (0.8 M of NaCl). The amount of the predicated energy was applied to the MEC by a power supply, which drove the MEC to remove 93.7 % of the organic compounds and produce 32.8 mL of H2 experimentally. Increasing the PRO influent volume and draw concentration could produce more energy for the MEC operation, and correspondingly increase the MEC hydraulic retention time (HRT) and total hydrogen production. The models predicted that at an external voltage of 0.9 V, the MEC energy consumption reached the maximum PRO energy production. With a higher external voltage, the MEC energy consumption would exceed the PRO energy production, leading to negative effects on both organic removal and hydrogen production. CONCLUSIONS: The PRO-MEC system holds great promise in addressing water-energy nexus through organic removal, hydrogen production, and water recovery: (1) the PRO unit can reduce the volume of wastewater and extract clean water; (2) the PRO effluents can be further treated by the MEC; and (3) the osmotic energy harvested from the PRO unit can be applied to the MEC for sustainable bioelectrochemical hydrogen production.

Porous Carbon Nanosheets Codoped with Nitrogen and Sulfur for Oxygen Reduction Reaction in Microbial Fuel Cells.

In this work, a simple synthesis strategy has been developed for the preparation of nitrogen- and sulfur-codoped porous carbon nanosheets (N/S-CNS) as a cathode catalyst for microbial fuel cells (MFCs). The as-prepared N/S-CNS showed favorable features for electrochemical energy conversion such as high surface area (1004 m(2) g(-1)), defect structure, and abundant exposure of active sites that arose primarily from porous nanosheet morphology. Benefiting from the unique nanostructure, the resulting nanosheets exhibited effective electrocatalytic activity toward oxygen reduction reaction (ORR). The onset potential of the N/S-CNS in linear-sweep voltammetry was approximately -0.05 V vs Ag/AgCl in neutral phosphate buffer saline. Electrochemical impedance spectroscopy showed that the ohmic and charge-transfer resistance of the codoped catalyst were 1.5 and 14.8 Ω, respectively, both of which were lower than that of platinum/carbon (Pt/C). Furthermore, the electron-transfer number of the N/S-CNS was calculated to be ∼3.5, suggesting that ORR on the catalyst proceeds predominantly through the favorable four-electron pathway. The MFC with N/S-CNS as a cathode catalyst generated current density (6.6 A m(-2)) comparable to that with Pt/C (7.3 A m(-2)). The high durability and low price indicate that N/S-CNS can be a competitive catalyst for applications of MFCs.

Integrating membrane filtration into bioelectrochemical systems as next generation energy-efficient wastewater treatment technologies for water reclamation: A review.

Bioelectrochemical systems (BES) represent an energy-efficient approach for wastewater treatment, but the effluent still requires further treatment for direct discharge or reuse. Integrating membrane filtration in BES can achieve high-quality effluents with additional benefits. Three types of filtration membranes, dynamic membrane, ultrafiltration membrane and forward osmosis membrane that are grouped based on pore size, have been studied for integration in BES. The integration can be accomplished either in an internal or an external configuration. In an internal configuration, membranes can act as a separator between the electrodes, or be immersed in the anode/cathode chamber as a filtration component. The external configuration allows BES and membrane module to be operated independently. Given much progress and interest in the integration of membrane filtration into BES, this paper has reviewed the past studies, described various integration methods, discussed the advantages and limitations of each integration, and presented challenges for future development.

Graphene-modified electrodes for enhancing the performance of microbial fuel cells.

Graphene is an emerging material with superior physical and chemical properties, which can benefit the development of microbial fuel cells (MFC) in several aspects. Graphene-based anodes can enhance MFC performance with increased electron transfer efficiency, higher specific surface area and more active microbe-electrode-electrolyte interaction. For cathodic processes, oxygen reduction reaction is effectively catalyzed by graphene-based materials because of a favorable pathway and an increase in active sites and conductivity. Despite challenges, such as complexity in synthesis and property degeneration, graphene-based electrodes will be promising for developing MFCs and other bioelectrochemical systems to achieve sustainable water/wastewater treatment and bioenergy production.

Effect of acclimation and nutrient supply on 5-tolyltriazole biodegradation with activated sludge communities.

The corrosion inhibitor 5-tolyltriazole (5-TTri) can have a detrimental impact on aquatic systems thus implying an acute need to reduce the effluent concentrations of 5-TTri. In this study, 5-TTri biodegradation was enhanced through acclimation and nutrient supply. Activated sludge communities (ASC) were setup in nine subsequent ASC generations. While generation two showed a lag phase of five days without biodegradation, generations four to nine utilized 5-TTri right after inoculation, with biodegradation rates from 3.3 to 5.2 mg L(-1)d(-1). Additionally, centrifuged AS supernatant was used to simulate the nutrient conditions in wastewater. This sludge supernatant (SS) significantly enhanced biodegradation, resulting in removal rates ranging from 3.2 to 5.0 mg L(-1)d(-1) without acclimation while the control groups without SS observed lower rates of ⩽ 2.2 mg L(-1)d(-1).

Determination of optimal conditions for 5-methyl-benzotriazole biodegradation with activated sludge communities by dilution of the inoculum.

The aerobic biodegradation of 5-methyl-benzotriazole (5-TTri) was optimized using lab-scale setups and activated sludge communities (ASC) collected from three wastewater treatment plants (WWTP) MBR-MH, CAS-E and CAS-M being different in their treatment technologies. ASC inocula were diluted to rule out non-biodegrading species and incubated under two nutrient conditions: A) mineral salt media (MSM) and B) carbon and nitrogen supplied MSM giving MSM-CN. 5-TTri removal with the ASC ranged from 60% to 100% in only 10 days. 100 µL suspended biomass from the biodegrading setups was subsequently plated on solid media to eliminate possible activated sludge remnants. After growth occurred, mixed colonies were harvested and inoculated in fresh liquid MSM containing 20 mg L(-1) 5-TTri. These bacterial consortia showed good 5-TTri removal in MSM-CN rather than in MSM, indicating nutrient supply being required for efficient biodegradation. In addition, experiments with high 5-TTri concentrations ranging from 20 to 1,000 mg L(-1) were conducted in both, MSM and MSM-CN and the maximal 5-TTri removal capacity of the ASC evaluated. 50 mg L(-1) 5-TTri was still removed in both media whereas 100 mg L(-1) was solely removed in MSM-CN. 5-TTri biodegradation patterns also indicated that 5-TTri might be co-metabolized by microbial consortia. Furthermore, experiments with gradient-solid-media-plates showed 5-TTri to be inhibitory for the ASC in concentrations above 50 mg L(-1) and revealed the optimal conditions regarding carbon and nitrogen concentration and pH value for effective 5-TTri biodegradation by ASC. Nitrogen proved a crucial factor for enhancing organisms' biodegradation capacity with an optimal pH around 7 while carbon showed no such effect.