Investigating the suitability of online flow cytometry for monitoring full-scale drinking water ozone system disinfection effectiveness.

While online monitoring of physicochemical parameters has widely been incorporated into drinking water treatment systems, online microbial monitoring has lagged behind, resulting in the use of surrogate parameters (disinfectant residual, applied dose, concentration × time, CT) to assess disinfection system performance. Online flow cytometry (online FCM) allows for automated quantification of total and intact microbial cells. This study sought to investigate the feasibility of online FCM for full-scale drinking water ozone disinfection system performance monitoring. A water treatment plant with high lime solids turbidity in the ozone contactor influent was selected to evaluate the online FCM in challenging conditions. Total and intact cell counts were monitored for 40 days and compared to surrogate parameters (ozone residual, ozone dose, and CT) and grab sample assay results for cellular adenosine triphosphate (cATP), heterotrophic plate counts (HPC), impedance flow cytometry, and 16S rRNA gene sequencing. Online FCM provided insight into the dynamics of the full-scale ozone system, including offering early warning of increased contactor effluent cell concentrations, which was not observed using surrogate measures. Positive correlations were observed between online FCM intact cell counts and cATP levels (Kendall's tau=0.40), HPC (Kendall's tau=0.20), and impedance flow cytometry results (Kendall's tau=0.30). Though a strong correlation between log intact cell removal and CT was not observed, 16S rRNA gene sequencing results showed that passage through the ozone contactor significantly changed the microbial community (p < 0.05). Potential causes of the low overall cell inactivation in the contactor and the significant changes in the microbial community after ozonation include regrowth in the later chambers of the contactor and varied ozone resistance of drinking water microorganisms. This study demonstrates the suitability of direct, online microbial analysis for monitoring full-scale disinfection systems.

Toward the autonomous flushing of building plumbing: Characterizing oxidation-reduction potential and temperature sensor dynamics.

Manual flushing of building plumbing is commonly used to address water quality issues that arise from water stagnation. Autonomous flushing informed by sensors has the potential to aid in the management of building plumbing, but a number of knowledge gaps hinder its application. This study evaluates autonomous flushing of building plumbing with online sensor and actuator nodes deployed under kitchen sinks in five residential houses. Online oxidation-reduction potential (ORP) and temperature data were collected for nine weeks during the winter and summer in houses with both free chlorine and chloramine. ORP levels in houses with free chlorine residuals decreased after overnight stagnation. The overnight decrease in ORP was not observed when tap water was automatically flushed for five minutes at 6:00 h every morning. ORP levels in houses with chloramine residuals did not decrease consistently after overnight stagnation, and daily automated flushes did not have an observable effect on the ORP signals. Additional laboratory experiments were carried out to evaluate ORP signals during chlorine decay and after incremental changes in chlorine, as would be expected in building plumbing conditions. Results from the lab and field deployments suggest on-line ORP sensors may be used to detect free chlorine decay due to stagnating water, but are not as effective in detecting chloramine decay. However, field results also suggest ORP may not respond as expected on a timely manner after free chlorine or chloramine have been restored, hindering their applicability in developing control algorithms. In this paper we tested twice-daily five-minute automatic flushing and found that it counteracts water quality degradation associated with overnight stagnation in free chlorine systems. An automatic sensor-based flushing is proposed using online temperature sensor data to determine when flushing has reached water from the main. The results suggest that flushing informed by temperature sensors can reduce the flushing time by 46 % compared to the preset five-minute static flush.

Simulating Rumen Conditions Using an Anaerobic Dynamic Membrane Bioreactor to Enhance Hydrolysis of Lignocellulosic Biomass.

An anaerobic dynamic membrane bioreactor (AnDMBR) mimicking rumen conditions was developed to enhance the hydrolysis of lignocellulosic materials and the production of volatile fatty acids (VFAs) when treating food waste. The AnDMBR was inoculated with cow rumen content and operated at a 0.5 day hydraulic retention time, 2-4 day solids retention time, a temperature of 39 °C, and a pH of 6.3, characteristics similar to those of a rumen. Removal rates of neutral detergent fiber and acid detergent fiber of 58.9 ± 8.4 and 69.0 ± 8.6%, respectively, and a VFA yield of 0.55 ± 0.12 g VFA as chemical oxygen demand g volatile solids (VS)fed-1 were observed at an organic loading rate of 18 ± 2 kg VS m-3 day-1. The composition and activity of the microbial community remained consistent after biofilm disruption, bioreactor upset, and reinoculation. Up to 66.7 ± 5.7% of the active microbial populations and 51.0 ± 7.0% of the total microbial populations present in the rumen-mimicking AnDMBR originated from the inoculum. This study offers a strategy to leverage the features of a rumen; the AnDMBR achieved high hydrolysis and fermentation rates even when treating substrates different from those fed to ruminants.

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing.

IMPORTANCE: Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

Anaerobic Digestion as a Core Technology in Addressing the Global Sanitation Crisis: Challenges and Opportunities.

Successfully addressing the complex global sanitation problem is a massive undertaking. Anaerobic digestion (AD), coupled with post-treatment, has been identified as a promising technology to contribute to meeting this goal. It offers multiple benefits to the end users, such as the potential inactivation of pathogenic microorganisms in waste and the recovery of resources, including renewable energy and nutrients. This feature article provides an overview of the most frequently applied AD systems for decentralized communities and low- and lower-middle-income countries with an emphasis on sanitation, including technologies for which pathogen inactivation was considered during the design. Challenges to AD use are then identified, such as experience, economics, knowledge/training of personnel and users, and stakeholder analysis. Finally, accelerators for AD implementation are noted, such as the inclusion of field studies in academic journals, analysis of emerging contaminants, the use of sanitation toolboxes and life cycle assessment in design, incorporation of artificial intelligence in monitoring, and expansion of undergraduate and graduate curricula focused on Water, Sanitation, and Hygiene (WASH).

Evaluation of Nanaerobic Digestion as a Mechanism to Explain Surplus Methane Production in Animal Rumina and Engineered Digesters.

Nanaerobes are a newly described class of microorganisms that use a unique cytochrome bd oxidase to achieve nanaerobic respiration at <2 µM dissolved oxygen (∼1% of atmospheric oxygen) but are not viable above this value due to the lack of other terminal oxidases. Although sharing an overlapping ecological niche with methanogenic archaea, the role of nanaerobes in methanogenic systems has not been studied so far. To explore their occurrence and significance, we re-analyzed published meta-omic datasets from animal rumina and waste-to-energy digesters, including conventional anaerobic digesters and anaerobic digesters with ultra-low oxygenation. Results show that animal rumina share broad similarities in the microbial community and system performance with oxygenated digesters, rather than with conventional anaerobic digesters, implying that trace levels of oxygen drive the efficient digestion in ruminants. The rumen system serves as an ideal model for the newly named nanaerobic digestion, as it relies on the synergistic co-occurrence of nanaerobes and methanogens for methane yield enhancement. The most abundant ruminal bacterial family Prevotellaceae contains many nanaerobes, which perform not only anaerobic fermentation but also nanaerobic respiration using cytochrome bd oxidase. These nanaerobes generally accompany hydrogenotrophic methanogens to constitute a thermodynamically and physiologically consistent framework for efficient methane generation. Our findings provide new insights into ruminal methane emissions and strategies to enhance methane generation from biomass.

Environmental life cycle assessment of treatment and management strategies for food waste and sewage sludge.

A consequential life cycle assessment (LCA) was utilized to compare the environmental impacts of food waste and sewage sludge management strategies. The strategies included a novel two-phase anaerobic digestion (AD) system and alternatives including landfill, waste-to-energy, composting, anaerobic membrane bioreactor, and conventional AD (wet continuous stirred-tank reactor [CSTR]). The co-management of food waste with sewage sludge was also considered for the two-phase AD system and for a conventional AD reactor. A multidimensional LCA approach was taken, considering the five-midpoint impact categories of global warming, smog, human health particulate, acidification, and eutrophication estimated using the U.S. EPA Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts. Co-management of food waste and sewage sludge using the novel two-phase AD system was shown to maximize energy recovery and had a net global warming benefit while reducing other environmental impacts compared with the alternative management strategies. It had similar relative environmental advantages across all categories as conventional AD, with the advantage of a smaller physical footprint. However, both approaches featured net environmental burdens when the background electric grid intensity fell below 0.25 kg CO2-eq kWh-1, as could be expected in a decarbonized electric future. Upgrading the biogas produced from AD to renewable natural gas can displace the use of fossil natural gas for other non-electricity energy requirements that are difficult to decarbonize and may extend the time period of significant environmental benefits of utilizing AD for organic waste management. Treatment of the nutrient-rich supernatant generated by the novel two-phase AD system could be an obstacle for utilities with stringent nutrient discharge limits. Future research and full-scale implementation are needed to demonstrate the benefits of the two-phase AD system predicted through this analysis.

Low-cost informational intervention reduced drinking water arsenic exposure in Bangladesh.

Thirty million Bangladeshis continue to drink water with unacceptable levels of arsenic (>10 µg/L), resulting in a large public health burden. The vast majority of the Bangladeshi population relies on private wells, and less than 12% use piped water, increasing the complexity of mitigation efforts. While mass testing and informational campaigns were successful in the early 2,000 s, they have received little attention in recent years, even though the number of wells in the country has likely more than doubled. We investigated the effect of a low-cost (

Competitive Reactions during Ethanol Chain Elongation Were Temporarily Suppressed by Increasing Hydrogen Partial Pressure through Methanogenesis Inhibition.

Organic waste streams can be converted into high-value platform chemicals such as medium-chain carboxylic acids (MCCAs) using mixed microbial communities via chain elongation. However, the heterogeneity of waste streams and the use of complex microbial communities can lead to undesirable reactions, thus decreasing process efficiency. We explored suppressing excessive ethanol oxidation to acetate (EEO) by increasing the hydrogen partial pressure (PH2) through hydrogenotrophic methanogenesis inhibition by periodically adding 2-bromoethanesulfonate (2-BES) to an MCCA-producing bioreactor to reach 10 mM of 2-BES upon addition. The bioreactor was fed with pretreated food waste and brewery waste containing high concentrations of short-chain carboxylic acids and ethanol, respectively. While 2-BES addition initially reduced EEO, some methanogens (Methanobrevibacter spp.) persisted and resistant populations were selected over time. Besides changing the methanogenic community structure, adding 2-BES also changed the bacterial community structure due to its impact on PH2. While we demonstrated that PH2 could be manipulated using 2-BES to control EEO, methods that do not require the addition of a chemical inhibitor should be explored to maintain optimum PH2 for long-term suppression of EEO.

A snapshot of the global drinking water virome: Diversity and metabolic potential vary with residual disinfectant use.

Viruses are important drivers of microbial community ecology and evolution, influencing microbial mortality, metabolism, and horizontal gene transfer. However, the effects of viruses remain largely unknown in many environments, including in drinking water systems. Drinking water metagenomic studies have offered a whole community perspective of bacterial impacts on water quality, but have not yet considered the influences of viruses. In this study, we address this gap by mining viral DNA sequences from publicly available drinking water metagenomes from distribution systems in six countries around the world. These datasets provide a snapshot of the taxonomic diversity and metabolic potential of the global drinking water virome; and provide an opportunity to investigate the effects of geography, climate, and drinking water treatment practices on viral diversity. Both environmental conditions and differences in sample processing were found to influence the viral composition. Using free chlorine as the residual disinfectant was associated with clear differences in viral taxonomic diversity and metabolic potential, with significantly fewer viral populations and less even viral community structures than observed in distribution systems without residual disinfectant. Additionally, drinking water viruses carry antibiotic resistance genes (ARGs), as well as genes to survive oxidative stress and nitrogen limitation. Through this study, we have demonstrated that viral communities are diverse across drinking water systems and vary with the use of residual disinfectant. Our findings offer directions for future research to develop a more robust understanding of how virus-bacteria interactions in drinking water distribution systems affect water quality.

Tenets of a holistic approach to drinking water-associated pathogen research, management, and communication.

In recent years, drinking water-associated pathogens that can cause infections in immunocompromised or otherwise susceptible individuals (henceforth referred to as DWPI), sometimes referred to as opportunistic pathogens or opportunistic premise plumbing pathogens, have received considerable attention. DWPI research has largely been conducted by experts focusing on specific microorganisms or within silos of expertise. The resulting mitigation approaches optimized for a single microorganism may have unintended consequences and trade-offs for other DWPI or other interests (e.g., energy costs and conservation). For example, the ecological and epidemiological issues characteristic of Legionella pneumophila diverge from those relevant for Mycobacterium avium and other nontuberculous mycobacteria. Recent advances in understanding DWPI as part of a complex microbial ecosystem inhabiting drinking water systems continues to reveal additional challenges: namely, how can all microorganisms of concern be managed simultaneously? In order to protect public health, we must take a more holistic approach in all aspects of the field, including basic research, monitoring methods, risk-based mitigation techniques, and policy. A holistic approach will (i) target multiple microorganisms simultaneously, (ii) involve experts across several disciplines, and (iii) communicate results across disciplines and more broadly, proactively addressing source water-to-customer system management.

Anaerobic co-digestion of various organic wastes: Kinetic modeling and synergistic impact evaluation.

Anaerobic mono- and co-digestion of coffee pulp (CP), cattle manure (CM), food waste (FW) and dewatered sewage sludge (DSS), were assessed using biochemical methane potential tests. The effects of two different inocula, anaerobically digested cattle manure (ADCM) and anaerobically digested waste activated sludge (ADWAS), and five different co-feedstock ratios for CP:CM and FW:DSS (1:0, 4:1, 2:1, 4:3, and 0:1) on specific methane yields were also evaluated. Mono-digestions of both CP and FW yielded the highest methane yield compared to the co-digestion ratios examined. Furthermore, no synergistic or antagonistic effect was observed for any of the co-digestion ratios tested. Nine different kinetic models (five conventional mono-digestion models and four co-digestion models) were compared and evaluated for both mono- and co-digestion studies. For CP:CM, cone and modified Gompertz with second order equation models were the best-fit for mono- and co-digestion systems, respectively, while for FW:DSS, superimposed model showed the best-fit for all systems.

Shower water contributes viable nontuberculous mycobacteria to indoor air.

Nontuberculous mycobacteria (NTM) are frequently present in municipal drinking water and building plumbing, and some are believed to cause respiratory tract infections through inhalation of NTM-containing aerosols generated during showering. However, the present understanding of NTM transfer from water to air is insufficient to develop NTM risk mitigation strategies. This study aimed to characterize the contribution of shower water to the abundance of viable NTM in indoor air. Shower water and indoor air samples were collected, and 16S rRNA and rpoB genes were sequenced. The sequencing results showed that running the shower impacted the bacterial community structure and NTM species composition in indoor air by transferring certain bacteria from water to air. A mass balance model combined with NTM quantification results revealed that on average 1/132 and 1/254 of NTM cells in water were transferred to air during 1 hour of showering using a rain and massage showerhead, respectively. A large fraction of the bacteria transferred from water to air were membrane-damaged, i.e. they had compromised membranes based on analysis by live/dead staining and flow cytometry. However, the damaged NTM in air were recoverable as shown by growth in a culture medium mimicking the respiratory secretions of people with cystic fibrosis, implying a potential infection risk by NTM introduced to indoor air during shower running. Among the recovered NTM, Mycobacterium mucogenicum was the dominant species as determined by rpoB gene sequencing. Overall, this study lays the groundwork for future pathogen risk management and public health protection in the built environment.

Tetracycline, sulfadimethoxine, and antibiotic resistance gene dynamics during anaerobic digestion of dairy manure.

Antibiotic use in animal husbandry is a potential entryway for antibiotics and antibiotic resistance genes (ARGs) to enter the environment through manure fertilizer application. The potential of anaerobic digestion (AD) to remove antibiotics and ARGs was investigated through tetracycline (TC) and sulfadimethoxine (SDM) additions into dairy manure digested for 44 d. This was the first study to evaluate antibiotics at concentrations quantified on-farm and relevant to field applications of manure. Triplicate treatments included a 1 mg L-1 TC spike, a 10 mg L-1 TC spike, a 1 mg L-1 SDM spike (SDM 1), a 10 mg L-1 SDM spike, a mixture of TC and SDM at 1 mg L-1 each (TC+SDM 1), and a manure-only treatment. The SDM spikes were reduced by >99% reduction during the AD processing, but TC additions had variable reductions (0-96%). Molecular analyses showed that decreases in tetM gene copies correlated with declines in TC; however, reductions in SDM concentration did not correlate with decreases in sul1 gene copy concentrations. The AD reactors containing 10 mg L-1 of TC and 10 mg L-1 of SDM both had CH4 production reductions of 7.8%, whereas no CH4 reduction was observed in other treatments (1 mg L-1 treatments). The study results were the first to confirm that AD can remove SDM when adding at concentrations observed in on-farm manure (<1 mg L-1 ) without compromising energy production. Because TC adsorbs to the solid particles and transforms into isomers, the decreases in TC concentrations were more variable and should be closely monitored.

Anaerobic co-digestion: Current status and perspectives.

Anaerobic digestion is a long-established technology for the valorization of diverse organic wastes with concomitant generation of valuable resources. However, mono-digestion (i.e., anaerobic digestion using one feedstock) suffers from challenges associated with feedstock characteristics. Co-digestion using multiple feedstocks provides the potential to overcome these limitations. Significant research and development efforts have highlighted several inherent merits of co-digestion, including enhanced digestibility due to synergistic effects of co-substrates, better process stability, and higher nutrient value of the produced co-digestate. However, studies focused on the underlying effects of diverse co-feedstocks on digester performance and stability have not been synthesized so far. This review fills this gap by highlighting the limitations of mono-digestion and critically examining the benefits of co-digestion. Furthermore, this review discusses synergistic effect of co-substrates, characterization of microbial communities, the prediction of biogas production via different kinetic models, and highlights future research directions for the development of a sustainable biorefinery.

Metagenomic Quantification of Genes with Internal Standards.

We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families.IMPORTANCE qPCR and metagenomics are central molecular techniques that have offered insights into biological processes for decades, from monitoring spatial and temporal gene dynamics to tracking ARGs or pathogens. Still needed is a tool that can quantify thousands of relevant genes in a sample as gene copies per sample mass or volume. We compare a quantitative metagenomic approach with traditional qPCR approaches in the quantification of ARG targets in dairy manure samples. By leveraging the benefits of nontargeted community genomics, we demonstrate high-throughput absolute gene quantification of all known ARG sequences in environmental samples.

Predictive Modeling of Virus Inactivation by UV.

UV254 disinfection strategies are commonly applied to inactivate pathogenic viruses in water, food, air, and on surfaces. There is a need for methods that rapidly predict the kinetics of virus inactivation by UV254, particularly for emerging and difficult-to-culture viruses. We conducted a systematic literature review of inactivation rate constants for a wide range of viruses. Using these data and virus characteristics, we developed and evaluated linear and nonlinear models for predicting inactivation rate constants. Multiple linear regressions performed best for predicting the inactivation kinetics of (+) ssRNA and dsDNA viruses, with cross-validated root mean squared relative prediction errors similar to those associated with experimental rate constants. We tested the models by predicting and measuring inactivation rate constants of a (+) ssRNA mouse coronavirus and a dsDNA marine bacteriophage; the predicted rate constants were within 7% and 71% of the experimental rate constants, respectively, indicating that the prediction was more accurate for the (+) ssRNA virus than the dsDNA virus. Finally, we applied our models to predict the UV254 rate constants of several viruses for which high-quality UV254 inactivation data are not available. Our models will be valuable for predicting inactivation kinetics of emerging or difficult-to-culture viruses.