Perturbations to common gardens of anaerobic co-digesters reveal relationships between functional resilience and microbial community composition.

We report the relationship between enrichment of adapted populations and enhancement of community functional resilience in methanogenic bioreactors. Although previous studies have shown the positive effects of acclimation, this work directly investigated the relationships between microbiome dynamics and performance of anaerobic co-digesting reactors in response to different levels of an environmental perturbation (loading of grease interceptor waste [GIW]). Using the methanogenic microbiome from a full-scale digester, we developed eight sets of microbial communities in triplicate using different feed sources. These substrate-specific microbiomes were then exposed to three independent disturbance events of low-, mid- and high-GIW loading rates. This approach allowed us to directly attribute differences in community responses to differences in community composition. Despite identical inocula, environment (digester operation, substrate loading rate, and feeding patterns) and general whole-community function (methane production and effluent quality) during the cultivation period, different substrates led to different microbial community assemblies. Lipid pre-acclimation led to enrichment of a pool of specialized populations, along with thriving of sub-dominant communities. The enrichment of these populations improved functional resilience and process performance when exposed to a low level of lipid-rich perturbation compared with less-acclimated communities. At higher levels of perturbation, the communities were not able to recover methanogenesis, indicating a loading limit to the resilience response. This study extends our current understanding of environmental perturbations, feed-specific adaptation, and functional resilience in methanogenic bioreactors.IMPORTANCEThis study demonstrates, for the first time for GIW co-digestion, how applying similar perturbations to different microbial communities was used to directly identify the causal relationships between microbial community, function, and environment in triplicate anaerobic microbiomes. We evaluated the impact of feed-specific adaptation on methanogenic microbiomes and demonstrated how microbiomes can be influenced to improve their functional (methanogenic) resilience to GIW inhibition. These findings demonstrate how an ecological framework can help improve a biological engineering application, and more specifically, increase the potential of anaerobic co-digestion for converting wastes to energy.

Estimating rates of change to interpret quantitative wastewater surveillance of disease trends.

BACKGROUND: Wastewater monitoring data can be used to estimate disease trends to inform public health responses. One commonly estimated metric is the rate of change in pathogen quantity, which typically correlates with clinical surveillance in retrospective analyses. However, the accuracy of rate of change estimation approaches has not previously been evaluated. OBJECTIVES: We assessed the performance of approaches for estimating rates of change in wastewater pathogen loads by generating synthetic wastewater time series data for which rates of change were known. Each approach was also evaluated on real-world data. METHODS: Smooth trends and their first derivatives were jointly sampled from Gaussian processes (GP) and independent errors were added to generate synthetic viral load measurements; the range hyperparameter and error variance were varied to produce nine simulation scenarios representing different potential disease patterns. The directions and magnitudes of the rate of change estimates from four estimation approaches (two established and two developed in this work) were compared to the GP first derivative to evaluate classification and quantitative accuracy. Each approach was also implemented for public SARS-CoV-2 wastewater monitoring data collected January 2021-May 2023 at 25 sites in North Carolina, USA. RESULTS: All four approaches inconsistently identified the correct direction of the trend given by the sign of the GP first derivative. Across all nine simulated disease patterns, between a quarter and a half of all estimates indicated the wrong trend direction, regardless of estimation approach. The proportion of trends classified as plateaus (statistically indistinguishable from zero) for the North Carolina SARS-CoV-2 data varied considerably by estimation method but not by site. DISCUSSION: Our results suggest that wastewater measurements alone might not provide sufficient data to reliably track disease trends in real-time. Instead, wastewater viral loads could be combined with additional public health surveillance data to improve predictions of other outcomes.

Linking microbial population dynamics in anaerobic bioreactors to food waste type and decomposition stage.

A key question in anaerobic microbial ecology is how microbial communities develop over different stages of waste decomposition and whether these changes are specific to waste types. We destructively sampled over time 26 replicate bioreactors cultivated on fruit/vegetable waste (FVW) and meat waste (MW) based on pre-defined waste components and composition. To characterize community shifts, we examined 16S rRNA genes from both the leachate and solid fractions of the waste. Waste decomposition occurred faster in FVW than MW, as accumulation of ammonia in MW reactors led to inhibition of methanogenesis. We identified population succession during different stages of waste decomposition and linked specific populations to different waste types. Community analyses revealed underrepresentation of methanogens in the leachate fractions, emphasizing the importance of consistent and representative sampling when characterizing microbial communities in solid waste.

Microbial community assembly in engineered bioreactors.

Microbial community assembly (MCA) processes that shape microbial communities in environments are being used to analyze engineered bioreactors such as activated sludge systems and anaerobic digesters. The goal of studying MCA is to be able to understand and predict the effect of design and operation procedures on bioreactor microbial composition and function. Ultimately, this can lead to bioreactors that are more efficient, resilient, or resistant to perturbations. This review summarizes the ecological theories underpinning MCA, evaluates MCA analysis methods, analyzes how these MCA-based methods are applied to engineered bioreactors, and extracts lessons from case studies. Furthermore, we suggest future directions in MCA research in engineered bioreactor systems. The review aims to provide insights and guidance to the growing number of environmental engineers who wish to design and understand bioreactors through the lens of MCA.

Microplate-Based Cell Viability Assay as a Cost-Effective Alternative to Flow Cytometry for Microalgae Analysis.

Cell viability is a critical indicator for assessing culture quality in microalgae cultivation for biorefinery and bioremediation. Fluorescent dyes that distinguish viable from nonviable cells can enable viability quantification based on the percentage of live cells. However, fluorescence analysis using the typical flow cytometry method is costly and impractical for industrial applications. To address this, we developed new microplate assays utilizing fluorescein diacetate as a live cell stain and erythrosine B as a dead cell stain. These assays provide a low-cost, simple, and reliable method of assessing cell viability. The proposed microplate assays were successfully applied to monitor the viability of the microalgae Dunaliella viridis under carbon and nitrogen limitation stresses and demonstrated good agreement with flow cytometry measurements. We conducted a systematic investigation of the effects of dye concentration, incubation time, and background fluorescence on the microplate assays' performance. Further, we provide a comprehensive review of commonly used fluorescent dyes for microalgae staining, discuss strategies to enhance assay performance, and offer recommendations for dye selection and protocol development. This study presents a comprehensive new method for microplate-based viability analysis, providing valuable insights for future microalgae viability assessments and applications.

Growth of Dunaliella viridis in multiple cycles of reclaimed media after repeated high pH-induced flocculation and harvesting.

Minimizing the use of water for growing microalgae is crucial for lowering the energy and costs of animal feed, food, and biofuel production from microalgae. Dunaliella spp., a haloterant species that can accumulate high intracellular levels of lipids, carotenoids, or glycerol can be harvested effectively using low-cost and scalable high pH-induced flocculation. However, the growth of Dunaliella spp. in reclaimed media after flocculation and the impact of recycling on the flocculation efficiency have not been explored. In this study, repeated cycles of growth of Dunaliella viridis in repeatedly reclaimed media from high pH-induced flocculation were studied by evaluating cell concentrations, cellular components, dissolved organic matter (DOM), and bacterial community shifts in the reclaimed media. In reclaimed media, D. viridis grew to the same concentrations of cells and intracellular components as fresh media-107 cells/mL with cellular composition of 3 % lipids, 40 % proteins, and 15 % carbohydrates-even though DOM accumulated and the dominant bacterial populations changed. There was a decrease in the maximum specific growth rate and flocculation efficiency from 0.72 d-1 to 0.45 d-1 and from 60 % to 48 %, respectively. This study shows the potential of repeated (at least five times) flocculation and reuse of media as a possible way of reducing the costs of water and nutrients with some tradeoffs in growth rate and flocculation efficiency.

Meeting the Water and Sanitation Challenges of Underbounded Communities in the U.S.

Water and sanitation (wastewater) infrastructure in the United States is aging and deteriorating, with massive underinvestment over the past several decades. For many years, lack of attention to water and sanitation infrastructure has combined with racial segregation and discrimination to produce uneven access to water and wastewater services resulting in growing threats to human and environmental health. In many metropolitan areas in the U.S., those that often suffer disproportionately are residents of low-income, minority communities located in urban disadvantaged unincorporated areas on the margins of major cities. Through the process of underbounding (the selective expansion of city boundaries to exclude certain neighborhoods often based on racial demographics or economics), residents of these communities are disallowed municipal citizenship and live without piped water, sewage lines, and adequate drainage or flood control. This Perspective identifies the range of water and sanitation challenges faced by residents in these communities. We argue that future investment in water and sanitation should prioritize these communities and that interventions need to be culturally context sensitive. As such, approaches to address these problems must not only be technical but also social and give attention to the unique geographic and political setting of local infrastructures.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study.

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical-anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.

SARS-CoV-2 Wastewater Surveillance for Public Health Action.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has garnered extensive public attention during the coronavirus disease pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, bridging the communication and knowledge gaps between researchers and public health responders is needed. We describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethics consideration for monitoring. Although wastewater surveillance to assess community infections is not a new idea, the coronavirus disease pandemic might be the initiating event to make this emerging public health tool a sustainable nationwide surveillance system, provided that these barriers are addressed.

Global Water, Sanitation, and Hygiene Approaches: Anthropological Contributions and Future Directions for Engineering.

Anthropologists contribute key insights toward a comprehensive understanding of water, sanitation, and hygiene (WASH) as a multidimensional, multiscalar, and culturally embedded phenomenon. Yet, these insights have yet to be sufficiently operationalized and implemented in WASH development and wider WASH access-related paradigms. Ensuring WASH security requires a comprehensive approach to identifying both human health risk and environmental impact of WASH-related programs and strategies. It requires an understanding of how sanitation is integrated into households and communities and how individuals within particular cultural contexts practice sanitation and hygiene. This work facilitates that goal by outlining the major contributions of anthropology and allied social sciences to WASH, as well as outlining key considerations for future work and collaboration. We identify six major themes that, if applied in future engineering approaches, will more equitably integrate stakeholders and multiple vantage points in the successful implementation of WASH projects for marginalized and diverse groups. These include a critical understanding of previous approaches, culturally aware interventions, capacity building that considers (un)intended impact, co-created technology, collaboration between fields such as anthropology and engineering, and challenge-ready initiatives that respond to historic and emergent social and environmental inequity.

Impact of sampling depth on pathogen detection in pit latrines.

Wastewater based epidemiology (WBE) is increasingly used to provide decision makers with actionable data about community health. WBE efforts to date have primarily focused on sewer-transported wastewater in high-income countries, but at least 1.8 billion people in low- and middle-income countries (LMIC) use onsite sanitation systems such as pit latrines and septic tanks. Like wastewater, fecal sludges from such systems offer similar advantages in community pathogen monitoring and other epidemiological applications. To evaluate the distribution of enteric pathogens inside pit latrines-which could inform sampling methods for WBE in LMIC settings unserved by sewers-we collected fecal sludges from the surface, mid-point, and maximum-depth of 33 pit latrines in urban and peri-urban Malawi and analyzed the 99 samples for 20 common enteric pathogens via multiplex quantitative reverse transcription PCR. Using logistic regression adjusted for household population, latrine sharing, the presence of a concrete floor or slab, water source, and anal cleansing materials, we found no significant difference in the odds of detecting the 20 pathogens from the mid-point (adjusted odds ratio, aOR = 1.1; 95% confidence interval = 0.73, 1.6) and surface samples (aOR = 0.80, 95% CI = 0.54, 1.2) compared with those samples taken from the maximum depth. Our results suggest that, for the purposes of routine pathogen monitoring, pit latrine sampling depth does not strongly influence the odds of detecting enteric pathogens by molecular methods. A single sample from the pit latrines' surface, or a composite of surface samples, may be preferred as the most recent material contributed to the pit and may be easiest to collect.

Increased loading stress leads to convergence of microbial communities and high methane yields in adapted anaerobic co-digesters.

Enhancing biogas production, while avoiding inhibition of methanogenesis during co-digestion of grease interceptor waste (GIW), can help water resource recovery facilities reduce their carbon footprint. Here we used pre-adapted and non-adapted digesters to link microbial community structure to digester function. Before disturbance, the pre-adapted and non-adapted digesters showed similar methane production and microbial community diversity but dissimilar community composition. When exposed to an identical disturbance, the pre-adapted digester achieved better performance, while the non-adapted digester was inhibited. When re-exposed to disturbance after recovery, communities and performance of both digesters converged, regardless of the temporal variations. Co-digestion of up to 75% GIW added on a volatile solids (VS) basis was achieved, increasing methane yield by 336% from 0.180 to 0.785 l-methane/g-VS-added, the highest methane yield reported to date for lipid-rich waste. Progressive perturbation substantially enriched fatty acid-degrading Syntrophomonas from less than 1% to 24.6% of total 16S rRNA gene sequences, acetoclastic Methanosaeta from 2.3% to 11.9%, and hydrogenotrophic Methanospirillum from less than 1% to 6.6% in the pre-adapted digester. Specific hydrolytic and fermentative populations also increased. These ecological insights demonstrated how progressive perturbation can be strategically used to influence methanogenic microbiomes and improve co-digestion of GIW.

Modeling cell aggregate morphology during aerobic granulation in activated sludge processes reveals the combined effect of substrate and shear.

Past research on AGS (aerobic granular sludge technology) has mainly focused on macro-environment factors, such as settling time, feeding pattern, OLR (organic loading rate), SRT (sludge retention time), among others, and their effects on the granulation process. The biomass granulation process, however, is significantly affected by the micro-environment surrounding these biomass aggregates. In this research, an in silico computational approach was adopted to study the impact of the micro-environment on the biomass granulation process. A 2-D biofilm model based on the cellular automata algorithm and computational fluid dynamics was used to simulate the development of an individual biomass aggregate under specific hydrodynamic and substrate availability conditions. The simulation results indicated that shear and bulk substrate concentration combined to create the optimal conditions for aerobic granule formation. This process can be characterized by the RT (reversed Thiele) modulus value, which is the ratio of the maximum substrate transport over the maximum substrate reaction rate and an indicator of substrate availability. For AGS formation, the RT value should be greater than 0.1. Many common strategies, such as the application of batch reactors, selection for slow-growing microorganism, F/M (food/mass) ratio adjustment, feast and famine condition, and short settling time, for biomass granulation production can be explained by the RT value. The results suggest that rethinking unit process configurations in wastewater treatment facilities will be required to achieve reliable AGS formation.

Dynamic Modeling of Microalgae Growth and Lipid Production under Transient Light and Nitrogen Conditions.

We developed a new dynamic model to characterize how light and nitrogen regulate the cellular processes of photosynthetic microalgae leading to transient changes in the production of neutral lipids, carbohydrates, and biomass. Our model recapitulated the versatile neutral lipid synthesis pathways via (i) carbon reuse from carbohydrate metabolism under nitrogen sufficiency and (ii) fixed carbon redirection under nitrogen depletion. We also characterized the effects of light adaptation, light inhibition hysteresis, and nitrogen limitation on photosynthetic carbon fixation. The formulated model was calibrated and validated with experimental data of Dunaliella viridis cultivated in a lab-scale photobioreactor (PBR) under various light (low/moderate/high) and nitrogen (sufficient/limited) conditions. We conducted the identifiability, uncertainty, and sensitivity analyses to verify the model reliability using the profile likelihood method, the Markov chain Monte Carlo (MCMC) technique, and the extended Fourier Amplitude Sensitivity Test (eFAST). Our model predictions agreed well with experimental observations and suggested potential model improvement by incorporating a lipid degradation mechanism. The insights from our model-driven analysis helped improve the mechanistic understanding of transient algae growth and bioproducts formation under environmental variations and could be applied to optimize biofuel and biomass production.

Measuring the Shape and Size of Activated Sludge Particles Immobilized in Agar with an Open Source Software Pipeline.

Experimental bioreactors, such as those treating wastewater, contain particles whose size and shape are important parameters. For example, the size and shape of activated sludge flocs can indicate the conditions at the microscale, and also directly affect how well the sludge settles in a clarifier. Particle size and shape are both misleadingly 'simple' measurements. Many subtle issues, often unaddressed in informal protocols, can arise when sampling, imaging, and analyzing particles. Sampling methods may be biased or not provide enough statistical power. The samples themselves may be poorly preserved or undergo alteration during immobilization. Images may not be of sufficient quality; overlapping particles, depth of field, magnification level, and various noise can all produce poor results. Poorly specified analysis can introduce bias, such as that produced by manual image thresholding and segmentation. Affordability and throughput are desirable alongside reproducibility. An affordable, high throughput method can enable more frequent particle measurement, producing many images containing thousands of particles. A method that uses inexpensive reagents, a common dissecting microscope, and freely-available open source analysis software allows repeatable, accessible, reproducible, and partially-automated experimental results. Further, the product of such a method can be well-formatted, well-defined, and easily understood by data analysis software, easing both within-lab analyses and data sharing between labs. We present a protocol that details the steps needed to produce such a product, including: sampling, sample preparation and immobilization in agar, digital image acquisition, digital image analysis, and examples of experiment-specific figure generation from the analysis results. We have also included an open-source data analysis pipeline to support this protocol.

Controlling aerobic biological floc size using Couette-Taylor Bioreactors.

Biological floc size is an important reactor microenvironment parameter that is often not experimentally controlled due to a lack of suitable methods. Here, we introduce the Couette-Taylor bioreactor (CTB) as an improved tool for controlling biological floc size, specifically as compared with bubble-column sequencing batch reactors (SBRs). A CTB consists of two concentric walls, either of which may be rotated to induce fluid motion. The induced flow produces hydrodynamic shear which is more uniform than that produced through aeration in SBRs. Because hydrodynamic shear is a major parameter controlling floc size, we hypothesized the ability to better control shear rates within a CTB would enable better-controlled floc sizes. To test this hypothesis, we measured the particle size distributions of activated sludge flocs from CTBs with either inner (iCTB) or outer (oCTB) rotating walls as well as SBRs with varying height to diameter ratios (0.5, 1.1, and 9.4). The rotation speed of the CTBs and aeration rate of the SBRs were varied to produce predicted mean shear rates from 25 to 250 s-1. Further, the shear rate distributions for each experiment were estimated using computational fluid dynamics (CFD). In all SBR experiments, the floc distributions did not significantly vary with shear rate or geometry, likely because shear rates (estimated by CFD) differed much less than originally predicted by theory. In the CTB experiments, the mean particle size decreased proportionally with increased hydrodynamic shear, and iCTBs produced particle size distributions with smaller coefficients of variation than oCTBs (0.3 vs. 0.5-0.7, respectively).

Development of Photochemical Microsensors for Evaluating Photosynthetic Light Dose Distributions in Microalgal Photobioreactors.

We describe the development and testing of a Lagrangian method for quantifying light dose distributions within photobioreactors (PBRs) using novel photochemical microsensors. These microsensors were developed using 3-µm microspheres coated with a fluorescent dye that responds to wavelengths of visible light that are critical for photosynthesis. The dose-response kinetics of the microsensors was established by varying known doses of collimated light and quantifying the fluorescence responses of individual particles using flow cytometry. A deconvolution scheme was used to determine the light dose distribution from the fluorescence distribution of the microsensors. As proof-of-concept, the microsensors were used to quantify the photosynthetic light dose distributions within a gently mixed, 3 L flat-plate, batch PBR with and without algae and no gas bubbling and without algae but with gas bubbling. The microsensor approach not only provided information about the photosynthetic light distributions within the PBRs but also predicted the average light attenuation due to algal cells within 1% of estimates made with an in situ light sensor. The results showed that bubbles, under the conditions tested, increased the overall light irradiance by 18%; a result not captured by static measurements. The Lagrangian microsensors provide a novel approach for quantifying light within a photobioreactor.

Microbial ecological succession during municipal solid waste decomposition.

The decomposition of landfilled refuse proceeds through distinct phases, each defined by varying environmental factors such as volatile fatty acid concentration, pH, and substrate quality. The succession of microbial communities in response to these changing conditions was monitored in a laboratory-scale simulated landfill to minimize measurement difficulties experienced at field scale. 16S rRNA gene sequences retrieved at separate stages of decomposition showed significant succession in both Bacteria and methanogenic Archaea. A majority of Bacteria sequences in landfilled refuse belong to members of the phylum Firmicutes, while Proteobacteria levels fluctuated and Bacteroidetes levels increased as decomposition proceeded. Roughly 44% of archaeal sequences retrieved under conditions of low pH and high acetate were strictly hydrogenotrophic (Methanomicrobiales, Methanobacteriales). Methanosarcina was present at all stages of decomposition. Correspondence analysis showed bacterial population shifts were attributed to carboxylic acid concentration and solids hydrolysis, while archaeal populations were affected to a higher degree by pH. T-RFLP analysis showed specific taxonomic groups responded differently and exhibited unique responses during decomposition, suggesting that species composition and abundance within Bacteria and Archaea are highly dynamic. This study shows landfill microbial demographics are highly variable across both spatial and temporal transects.

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests.

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic performance of microalgae-based biofuel production. Models that estimate microalgal growth under different conditions can help to optimize PBR design and operation. To be effective, the growth parameters used in these models must be accurately determined. Algal growth experiments are often constrained by the dynamic nature of the culture environment, and control systems are needed to accurately determine the kinetic parameters. The first step in setting up a controlled batch experiment is live data acquisition and monitoring. This protocol outlines a process for the assembly and operation of a bench-scale photosynthetic bioreactor that can be used to conduct microalgal growth experiments. This protocol describes how to size and assemble a flat-plate, bench-scale PBR from acrylic. It also details how to configure a PBR with continuous pH, light, and temperature monitoring using a data acquisition and control unit, analog sensors, and open-source data acquisition software.