Comparing flow cytometry with culture-based methods for microbial monitoring and as a diagnostic tool for assessing drinking water treatment processes

Fuzzy C-means clustering algorithm applied in computed tomography images of patients with intracranial hemorrhage

In recent years, intracerebral hemorrhage (ICH) has garnered significant attention as a severe cerebrovascular disorder. To enhance the accuracy of ICH detection and segmentation, this study proposed an improved fuzzy C-means (FCM) algorithm and performed a comparative analysis with both traditional FCM and advanced convolutional neural network (CNN) algorithms. Experiments conducted on the publicly available CT-ICH dataset evaluated the performance of these three algorithms in predicting ICH volume. The results demonstrated that the improved FCM algorithm offered notable improvements in computational time and resource consumption compared to the traditional FCM algorithm, while also showing enhanced accuracy. However, it still lagged behind the CNN algorithm in areas such as feature extraction, model generalization, and the ability to handle complex image structures. The study concluded with a discussion of potential directions for further optimizing the FCM algorithm, aiming to bridge the performance gap with CNN algorithms and provide a reference for future research in medical image processing.

Ensuring microbial water quality for on-site water reuse: Importance of online sensors for reliable operation

A growing number of cities and regions are promoting or mandating on-site treatment and reuse of wastewater, which has resulted in the implementation of several thousand on-site water reuse systems on a global scale. However, there is only limited information on the (microbial) water quality from implemented systems. The focus of this study was on two best-in-class on-site water reuse systems in Bengaluru, India, which typically met the local water quality requirements during monthly compliance testing. This study aimed to (i) assess the microbial quality of the reclaimed water at a high temporal resolution (daily or every 15 min), and (ii) explore whether measurements from commercially available sensors can be used to improve the operation of such systems. The monitoring campaign revealed high variations in microbial water quality, even in these best-in-class systems, rendering the water inadequate for the intended reuse applications (toilet flushing and landscape irrigation). These variations were attributed to two key factors: (1) the low frequency of chlorination, and (2) fluctuations of the chlorine demand of the water, in particular of ammonium concentrations. Such fluctuations are likely inherent to on-site systems, which rely on a low level of process control. The monitoring campaign showed that the microbial water quality was most closely related to oxidation-reduction potential (ORP) and free chlorine sensors. Due to its relatively low cost and low need for maintenance, the ORP emerges as a compelling candidate for automating the chlorination to effectively manage variations in chlorine demand and ensure safe water reuse. Overall, this study underscores the necessity of integrating treatment trains, operation, and monitoring for safe on-site water reuse.

Predicting heterotrophic plate count exceedance in tap water: A binary classification model supervised by culture-independent data

Culture-independent data can be utilized to identify heterotrophic plate count (HPC) exceedances in drinking water. Although HPC represents less than 1% of the bacterial community and exhibits time lags of several days, HPC data are widely used to assess the microbiological quality of drinking water and are incorporated into drinking water standards. The present study confirmed the nonlinear relationships between HPC, intact cell count (ICC), and adenosine triphosphate (ATP) in tap water samples (stagnant and flushed). By using a combination of ICC, ATP, and free chlorine data as inputs, we show that HPC exceedance can be classified using a 2-layer feed-forward artificial neural network (ANN). Despite the nonlinearity of HPC, the best binary classification model showed accuracies of 95%, sensitivity of 91%, and specificity of 96%. ICC and chlorine concentrations were the most important features for classifiers. The main limitations, such as sample size and class imbalance, were also discussed. The present model provides the ability to convert data from emerging measurement techniques into established and well-understood measures, overcoming culture dependence and offering near real-time data to help ensure the biostability and safety of drinking water.

Kinetics and mechanisms of bacteria disinfection by performic acid in wastewater: In comparison with peracetic acid and sodium hypochlorite

Performic acid (PFA) has been increasingly used in wastewater disinfection due to its strong oxidizing ability and few disinfection byproducts. However, its disinfection pathways and mechanisms towards pathogenic bacteria disinfection are poorly understood. In this study, E. coli, S. aureus, and B. subtilis were inactivated using sodium hypochlorite (NaClO), PFA, and peracetic acid (PAA) in simulated turbid water and municipal secondary effluent. Cell culture-based plate counting showed that E. coli and S. aureus were extremely susceptible to NaClO and PFA and achieved a 4-log inactivation at CTs ≤ 1 mg/L·min with an initial disinfectant concentration of 0.3 mg/L. B. subtilis was much more resistant. At the initial disinfectant dose of 7.5 mg/L, PFA required CTs of 3-13 mg/L·min to achieve a 4-log inactivation. Turbidity negatively affected the disinfection. In the secondary effluent, the CTs required for PFA to achieve a 4-log inactivation of E. coli and B. subtilis were 6-12 times higher than those required in simulated turbid water, and a 4-log inactivation of S. aureus could not be achieved. PAA showed a much weaker disinfection ability than the other two disinfectants. The reaction pathways of E. coli inactivation by PFA included both direct and indirect reactions, in which the PFA molecule accounted for 73 %, and ·OH and peroxide radicals accounted for 20 % and 6 %, respectively. During PFA disinfection, E. coli cells were severely disintegrated, while the S. aureus cell exteriors remained mostly intact. B. subtilis was the least affected. Compared with cell culture-based analysis, the inactivation detected by flow cytometry was significantly lower. Viable but non-culturable bacteria after disinfection were believed to be primarily responsible for this inconsistency. This study suggested that PFA was able to control regular bacteria in wastewater, but it should be used with caution when treating recalcitrant pathogens.

Sulfide inhibition on polyphosphate accumulating organisms and glycogen accumulating organisms: Cumulative inhibitory effect and recoverability

Sulfate in wastewater can be reduced to sulfide and its impact on the stability of enhanced biological phosphorus removal (EBPR) is still unclear. In this study, the metabolic changes and subsequent recovery of polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) were investigated at different sulfide concentrations. The results showed that the metabolic activity of PAOs and GAOs was mainly related to H2S concentration. Under anaerobic conditions, the catabolism of PAOs and GAOs was promoted at H2S concentrations below 79 mg/L S and 271 mg/L S, respectively, and inhibited above these concentrations; whereas anabolism was consistently inhibited in the presence of H2S. The phosphorus (P) release was also pH-dependent due to the intracellular free Mg2+ efflux from PAOs. H2S was more destructive to the esterase activity and membrane permeability of PAOs than those of GAOs and prompted intracellular free Mg2+ efflux of PAOs, resulting in worse aerobic metabolism and subsequent recovery of PAOs than GAOs. Additionally, sulfides facilitated the production of extracellular polymeric substances (EPS), especially tightly bound EPS. The amount of EPS in GAOs was significantly higher than that in PAOs. The above results indicated that sulfide had a stronger inhibition to PAOs than GAOs, and when sulfide was present, GAOs had a competitive advantage over PAOs in EBPR.

Predicting microbial water quality in on-site water reuse systems with online sensors

Widespread implementation of on-site water reuse is hindered by the limited availability of monitoring approaches that ensure microbial quality during operation. In this study, we developed a methodology for monitoring microbial water quality in on-site water reuse systems using inexpensive and commercially available online sensors. An extensive dataset containing sensor and microbial water quality data for six of the most critical types of disruptions in membrane bioreactors with chlorination was collected. We then tested the ability of three typological machine learning algorithms - logistic regression, support-vector machine, and random forest - to predict the microbial water quality as "safe" or "unsafe" for reuse. The main criteria for model optimization was to ensure a low false positive rate (FPR) - the percentage of safe predictions when the actual condition is unsafe - which is essential to protect users health. This resulted in enforcing a fixed FPR ≤ 2%. Maximizing the true positive rate (TPR) - the percentage of safe predictions when the actual condition is safe - was given second priority. Our results show that logistic-regression-based models using only two out of the six sensors (free chlorine and oxidation-reduction potential) achieved the highest TPR. Including sensor slopes as engineered features allowed to reach similar TPRs using only one sensor instead of two. Analysis of the occurrence of false predictions showed that these were mostly early alarms, a characteristic that could be regarded as an asset in alarm management. In conclusion, the simplest algorithm in combination with only one or two sensors performed best at predicting the microbial water quality. This result provides useful insights for water quality modeling or for applications where small datasets are a common challenge and a general advantage might be gained by using simpler models that reduce the risk of overfitting, allow better interpretability, and require less computational power.

Sensor setpoints that ensure compliance with microbial water quality targets for membrane bioreactor and chlorination treatment in on-site water reuse systems

Widespread implementation of on-site water reuse systems is hindered by the limited ability to ensure the level of treatment and protection of human health during operation. In this study, we tested the ability of five commercially available online sensors (free chlorine (FC), oxidation-reduction potential (ORP), pH, turbidity, UV absorbance at 254 nm) to predict the microbial water quality in membrane bioreactors followed by chlorination using logistic regression-based and mechanism-based models. The microbial water quality was assessed in terms of removal of enteric bacteria from the wastewater, removal of enteric viruses, and regrowth of bacteria in the treated water. We found that FC and ORP alone could predict the microbial water quality well, with ORP-based models generally performing better. We further observed that prediction accuracy did not increase when data from multiple sensors were integrated. We propose a methodology to link online sensor measurements to risk-based water quality targets, providing operation setpoints protective of human health for specific combinations of wastewaters and reuse applications. For instance, we recommend a minimum ORP of 705 mV to ensure a virus log-removal of 5, and an ORP of 765 mV for a log-removal of 6. These setpoints were selected to ensure that the percentage of events where the water is predicted to meet the quality target but it does not remains below 5%. Such a systematic approach to set sensor setpoints could be used in the development of water reuse guidelines and regulations that aim to cover a range of reuse applications with differential risks to human health.

Microbial Water Quality through a Full-Scale Advanced Wastewater Treatment Demonstration Facility

The fates of viruses, bacteria, and antibiotic resistance genes during advanced wastewater treatment are important to assess for implementation of potable reuse systems. Here, a full-scale advanced wastewater treatment demonstration facility (ozone, biological activated carbon filtration, micro/ultrafiltration, reverse osmosis, and advanced oxidation) was sampled over three months. Atypically, no disinfectant residual was applied before the microfiltration step. Microbial cell concentrations and viability were assessed via flow cytometry and adenosine triphosphate (ATP). Concentrations of bacteria (16S rRNA gene), viruses (human adenovirus and JC polyomavirus), and antibiotic resistance genes (sul1 and bla _TEM ) were assessed via quantitative PCR following the concentration of large sample volumes by dead-end ultrafiltration. In all membrane filtration permeates, microbial concentrations were higher than previously reported for chloraminated membranes, and log₁₀ reduction values were lower than expected. Concentrations of 16S rRNA and sul1 genes were reduced by treatment but remained quantifiable in reverse osmosis permeate. It is unclear whether sul1 in the RO permeate was from the passage of resistance genes or new growth of microorganisms, but the concentrations were on the low end of those reported for conventional drinking water distribution systems. Adenovirus, JC polyomavirus, and bla _TEM genes were reduced below the limit of detection (∼10^-2 gene copies per mL) by microfiltration. The results provide insights into how treatment train design and operation choices affect microbial water quality as well as the use of flow cytometry and ATP for online monitoring and process control.

Removal of antibiotic microbial resistance by micro- and ultrafiltration of secondary wastewater effluents at pilot scale

Low-pressure membrane filtration was investigated at pilot scale with regard to its removal of antimicrobial resistance genes (ARGs) in conventional secondary treated wastewater plant effluents. While operating microfiltration (MF) and ultrafiltration (UF) membranes, key operational parameters for antimicrobial resistance (AMR) studies and key factors influencing AMR removal efficiencies of low-pressure membrane filtration processes were examined. The main factor for AMR removal was the pore size of the membrane. The formation of the fouling layer on capillary membranes had only a small additive effect on intra- and extrachromosomal ARG removal and a significant additive effect on mobile ARG removal. Using feeds with different ARGs abundances revealed that higher ARG abundance in the feed resulted in higher ARG abundance in the filtrate. Live-Dead cell counting in UF filtrate showed intact bacteria breaking through the UF membrane. Strong correlations between 16S rRNA genes (as surrogate for bacteria quantification) and the sul1 gene in UF filtrate indicated ARBs likely breaking through UF membranes.

Exploring the use of flow cytometry for understanding the efficacy of disinfection in chlorine contact tanks

A pilot scale chlorine contact tank (CCT) with flexible baffling was installed at an operational water treatment plant (WTP), taking a direct feed from the outlet of the rapid gravity filters (RGF). For the first time, disinfection efficacy was established by direct microbial monitoring in a continuous reactor using flow cytometry (FCM). Disinfection variables of dose, time, and hydraulic efficiency (short circuiting and dispersion) were explored following characterisation of the reactor's residence time distributions (RTD) by tracer testing. FCM enabled distinction to be made between changes in disinfection reactor design where standard culture-based methods could not. The product of chlorine concentration (C) and residence time (t) correlated well with inactivation of microbes, organisms, with the highest cell reductions (N/N₀) reaching <0.025 at Ct_x¯ of 20 mg.min/L and above. The influence of reactor geometry on disinfection was best shown from the Ct₁₀. This identified that the initial level of microbial inactivation was higher in unbaffled reactors for low Ct₁₀ values, although the highest levels of inactivation of 0.015 could only be achieved in the baffled reactors, because these conditions enabled the highest Ct₁₀ values to be achieved. Increased levels of disinfection were closely associated with increased formation of the trihalomethane disinfection by-products. The results highlight the importance of well-designed and operated CCT. The improved resolution afforded by FCM provides a tool that can dynamically quantify disinfection processes, enabling options for much better process control.

Bioaugmentation of pilot-scale slow sand filters can achieve compliant levels for the micropollutant metaldehyde in a real water matrix

Metaldehyde is a polar, mobile, low molecular weight pesticide that is challenging to remove from drinking water with current adsorption-based micropollutant treatment technologies. Alternative strategies to remove this and compounds with similar properties are necessary to ensure an adequate supply of safe and regulation-compliant drinking water. Biological removal of metaldehyde below the 0.1 µg•L^-1 regulatory concentration was attained in pilot-scale slow sand filters (SSFs) subject to bioaugmentation with metaldehyde-degrading bacteria. To achieve this, a library of degraders was first screened in bench-scale assays for removal at micropollutant concentrations in progressively more challenging conditions, including a mixed microbial community with multiple carbon sources. The best performing strains, A. calcoaceticus E1 and Sphingobium CMET-H, showed removal rates of 0.0012 µg•h^-1•10⁷ cells^-1 and 0.019 µg•h^-1•10⁷ cells^-1 at this scale. These candidates were then used as inocula for bioaugmentation of pilot-scale SSFs. Here, removal of metaldehyde by A. calcoaceticus E1, was insufficient to achieve compliant water regardless testing increasing cell concentrations. Quantification of metaldehyde-degrading genes indicated that aggregation and inadequate distribution of the inoculum in the filters were the likely causes of this outcome. Conversely, bioaugmentation with Sphingobium CMET-H enabled sufficient metaldehyde removal to achieve compliance, with undetectable levels in treated water for at least 14 d (volumetric removal: 0.57 µg•L^-1•h^-1). Bioaugmentation did not affect the background SSF microbial community, and filter function was maintained throughout the trial. Here it has been shown for the first time that bioaugmentation is an efficient strategy to remove the adsorption-resistant pesticide metaldehyde from a real water matrix in upscaled systems. Swift contaminant removal after inoculum addition and persistent activity are two remarkable attributes of this approach that would allow it to effectively manage peaks in metaldehyde concentrations (due to precipitation or increased application) in incoming raw water by matching them with high enough degrading populations. This study provides an example of how stepwise screening of a diverse collection of degraders can lead to successful bioaugmentation and can be used as a template for other problematic adsorption-resistant compounds in drinking water purification.

Seawater desalination based drinking water: Microbial characterization during distribution with and without residual chlorine

Monitoring the changes that occur to water during distribution is vital to ensure water safety. In this study, the biological stability of reverse osmosis (RO) produced drinking water, characterized by low cell concentration and low assimilable organic carbon, in combination with chlorine disinfection was investigated. Water quality at several locations throughout the existing distribution network was monitored to investigate whether microbial water quality changes can be identified. Results revealed that the water leaving the plant had an average bacterial cell concentration of 10³ cells/mL. A 0.5-1.5 log increase in bacterial cell concentration was observed at locations in the network. The residual disinfectant was largely dissipated in the network from 0.5 mg/L at the treatment plant to less than 0.1 mg/L in the network locations. The simulative study involving miniature distribution networks, mimicking the dynamics of a distribution network, fed with the RO produced chlorinated and non-chlorinated drinking water revealed that distributing RO produced water without residual disinfection, especially at high water temperatures (25-30 °C), poses a higher chance for water quality change. Within six months of operation of the miniature network fed with unchlorinated RO produced water, the adenosine triphosphate (ATP) and total cell concentration (TCC) in the pipe biofilm were 4 × 10² pg ATP/cm² and 1 × 10⁷ cells/ cm². The low bacterial cell concentration and organic carbon concentration in the RO-produced water did not prevent biofilm development inside the network with and without residual chlorine. The bacterial community analysis using 16S ribosomal RNA (rRNA) gene sequencing revealed that mesophilic bacteria with higher temperature tolerance and bacteria associated with oligotrophic, nutrient-poor conditions dominated the biofilm, with no indication of the existence of opportunistic pathogenic species. However, chlorination selected against most bacterial groups and the bacterial community that remained was mainly the bacteria capable of surviving disinfection regimes. Biofilms that developed in the presence of chlorine contained species classified as opportunistic pathogens. These biofilms have an impact on shaping the water quality received at the consumer tap. The presence of these bacteria on its own is not a health risk indicator; viability assessment and qPCRs targeting genes specific to the opportunistic pathogens as well as quantitative microbiological risk assessment (QMRA) should be included to assess the risk. The results from this study highlight the importance of implementing multiple barriers to ensure water safety. Changes in water quality detected even when high-quality disinfected RO-produced water is distributed highlight microbiological challenges that chlorinated systems endure, especially at high water temperatures.

Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review

Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. This review summarizes available biological fecal indicators focusing on host specificity, degree of association with fecal pollution, environmental persistence, and quantification methods in fecal pollution assessment. The development of practical tools is a crucial requirement for the implementation of mitigation strategies that may help confine the types of host-specific pathogens and determine the source control point, such as sourcing fecal wastes from point sources and nonpoint sources. Emerging multidisciplinary bacterial enumeration platforms are also discussed, including individual working mechanisms, applications, advantages, and limitations.

Bacterial dynamics in drinking water distribution systems and flow cytometry monitoring scheme optimization

Water biostability is desired within drinking water distribution systems (DWDSs) to limit microbiologically-related operational, aesthetic and, eventually, health-related issues. However, variations in microbiological quality can take place both spatially along DWDS pipelines and temporally at single locations due to biofilm detachment, water quality seasonality and other processes. In this study, long- and short-term trends of bacterial concentration and community structure were investigated in a secondary branch of an unchlorinated DWDS for several months using high-frequency flow cytometry (FCM) and traditional laboratory monitoring campaigns. Long-term trends of bacterial concentrations and community structures were likely caused by changes in the water physical-chemical quality (i.e. pH and conductivity). Short-term daily pattern, instead, resulted in significant variations between the bacterial concentrations and community structures at different hours, likely due to biofilm detachment and loose deposits resuspension related to changes in the local water flow. These patterns, however, showed broad variations and did not persist during the entire monitoring campaign presumably due to the stochasticity of local instantaneous demand and seasonal changes in water consumption. During periods without sensible long-term trends, the sampling hours explain a comparable or larger fraction of the bacterial community diversity compared to dates. The variations observed with FCM were poorly or not detected by traditional laboratory analyses, as the correlation between the two were rather weak, highlighting the limited information provided by traditional approaches. On the other hand, FCM data correlated with water pH and conductivity, underlining the relation between physical-chemical and microbiological water quality. Such results suggest that the advanced control of the physical-chemical water quality could minimize the microbiological water quality variations. Moreover, monitoring campaign planning should take into account the sampling time to reduce the noise caused by daily fluctuations and/or assess the overall quality variations. Finally, as monitoring costs are one of the barriers which prevent a more widespread use of FCM, a monitoring scheme optimization strategy was developed. Such strategy employs the data from an initial high-frequency sampling period to select the sampling hours which maximize the observed variations of bacterial concentration and community composition.

Reuse of ultrafiltered effluents for crop irrigation: On-site flow cytometry unveiled microbial removal patterns across a full-scale tertiary treatment

Reuse of treated wastewater for crop irrigation has been widely adopted to mitigate the effects of water scarcity on agricultural yields and to help preserving the integrity of aquatic ecosystems. This paper presents the outcomes of one-year monitoring of a full-scale agro-industrial wastewater treatment plant designed for water reuse, with a multistage tertiary treatment based on sand filtration, membrane ultrafiltration, storage and on-demand UV disinfection. We aimed to test flow cytometry as a monitoring tool to provide on-site indications on tertiary treatment performances and on the quality of treated wastewater along the treatment scheme. Membrane ultrafiltration retained prokaryotic cells and E. coli (>3 log). During storage of treated effluents, a significant decay of E. coli was observed together with the growth of prokaryotic and eukaryotic cells, and the UV disinfection was effective only against fecal indicators. The microbial quality of the treated effluent was comparable to the control groundwater locally used for irrigation. On-site rapid assessments by flow cytometry allowed unveiling crucial aspects affecting the microbiological quality of ultrafiltration permeate and treated effluent immediately after sampling, including plant operating performances and microbial removal patterns across the treatment train.

Short communication: Effects of electrochemically activated drinking water on bovine milk production and composition, including chlorate, perchlorate, and fatty acid profile

The objective of this study was to assess the effects of electrochemically activated drinking water (ECW) on milk chlorate, milk perchlorate, milk iodine, milk composition, milk fatty acid profile, and overall performance of dairy cows. Ten Red Danish cows in mid-lactation (203 ± 31 d in milk; average ± SD) were chosen from these 2 groups for intensive sampling. The treated group drank water with 4 ppm of ECW (29 mg/L of chlorate of Neuthox, Danish Clean Water A/S, Sønderborg, Denmark). The treatment lasted 60 consecutive days, with milk and water sampling on d 0, 30, and 60. Additionally, milk samples from both the control group and treated group were taken on d 90 to assess if any carry-over effect was present. Interactions between period and milk yield and somatic cell for the full group and period and milk fat content and milk urea nitrogen in the selected animals occurred. Milk yield was not significantly affected by treatments. Milk fat, milk fatty acid profile, chlorate, perchlorate, and iodine contents were not significantly different between treatments. Milk urea increased, whereas β-hydroxybutyrate and somatic cell count decreased significantly in the treated groups. Results showed that at a dosing of 4 ppm of ECW, both chlorate and perchlorate concentrations in milk (<0.002 mg/kg) were low, and no deleterious effects on milk production or milk chemical composition were observed. These data can be of use when assessing the effects of ECW on milk and milk powder chlorate and perchlorate levels and provide a context for assessing the potential for influencing human health under the conditions prevailing on a commercial dairy farm.