Online microbial fingerprinting for quality management of drinking water: Full-scale event detection

Microbial drinking water monitoring now and in the future

Over time, humanity has addressed microbial water contamination in various ways. Historically, individuals resorted to producing beer to combat the issue. Fast forward to the 19th century, and we witnessed a scientific approach by Robert Koch. His groundbreaking gelatine plating method aimed to identify and quantify bacteria, with a proposed limit of 100 colony-forming units per millilitre (CFU/mL) to avoid Cholera outbreaks. Despite considerable advancements in plating techniques through experimentation with media compositions and growth temperatures, the reliance on a century-old method for water safety remains the state-of-the-art. Even though most countries succeed in producing qualitative water at the end of the production centres, it is difficult to control, and guarantee, the same quality during distribution. Rather than focusing solely on specific sampling points, we propose a holistic examination of the entire water network to ensure comprehensive safety. Current practices leave room for uncertainties, especially given the low concentrations of pathogens. Innovative methods like flow cytometry and flow cytometric fingerprinting offer the ability to detect changes in the microbiome of drinking water. Additionally, molecular techniques and emerging sequencing technologies, such as third-generation sequencing (MinION), mark a significant leap forward, enhancing detection limits and emphasizing the identification of unwanted genes rather than the unwanted bacteria/microorganisms itself. Over the last decades, there has been the realization that the drinking water distribution networks are complex ecosystems that, beside bacteria, comprise of viruses, protozoans and even isopods. Sequencing techniques to find eukaryotic DNA are necessary to monitor the entire microbiome of the drinking water distribution network. Or will artificial intelligence, big data and machine learning prove to be the way to go for (microbial) drinking water monitoring? In essence, it is time to transcend century-old practices and embrace modern technologies to ensure the safety of our drinking water from production to consumption.

Assessing long-term ecological impacts of PCE contamination in groundwater using a flow cytometric fingerprint approach

This study aims to develop and validate a comprehensive method for assessing ecological disturbances in groundwater ecosystems caused by tetrachloroethylene (PCE) contamination, utilizing flow cytometry (FCM) fingerprint approach. We hypothesized that the ecological disturbance resulting from PCE contamination would exhibit 'press disturbance', persisting over extended periods, and inducing notable phenotypic differences in the microbial community compared to undisturbed groundwater. We collected 40 groundwater samples from industrial district with a history of over twenty years of PCE contamination, along with 56 control groundwater from the national surveillance groundwater system. FCM revealed significant alterations in the phenotypic diversity of microbial communities in PCE-contaminated groundwater, particularly during the dry season. The presence of specific dechlorinating bacteria (Dehalococcoides, Dehalogenimonas, and Geobacter) and their syntrophic partners was identified as an indicator of contamination. Phenotypic diversity measures provided clearer and more direct reflections of contamination impact compared to taxonomic diversity measures. This study establishes FCM fingerprinting as a simple, robust, and accurate method for evaluating ecological disturbances, with potential applications in early warning systems and continuous monitoring of groundwater contamination. The findings not only underscore the sensitivity of FCM in detecting phenotypic variations induced by environmental stressors but also highlight its utility in understanding the complex dynamics of microbial communities in contaminated groundwater ecosystems.

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.

Impact of operational conditions on drinking water biofilm dynamics and coliform invasion potential

Biofilms within drinking water distribution systems serve as a habitat for drinking water microorganisms. However, biofilms can negatively impact drinking water quality by causing water discoloration and deterioration and can be a reservoir for unwanted microorganisms. In this study, we investigated whether indicator organisms for drinking water quality, such as coliforms, can settle in mature drinking water biofilms. Therefore, a biofilm monitor consisting of glass rings was used to grow and sample drinking water biofilms. Two mature drinking water biofilms were characterized by flow cytometry, ATP measurements, confocal laser scanning microscopy, and 16S rRNA sequencing. Biofilms developed under treated chlorinated surface water supply exhibited lower cell densities in comparison with biofilms resulting from treated groundwater. Overall, the phenotypic as well as the genotypic characteristics were significantly different between both biofilms. In addition, the response of the biofilm microbiome and possible biofilm detachment after minor water quality changes were investigated. Limited changes in pH and free chlorine addition, to simulate operational changes that are relevant for practice, were evaluated. It was shown that both biofilms remained resilient. Finally, mature biofilms were prone to invasion of the coliform, Serratia fonticola. After spiking low concentrations (i.e., ±100 cells/100 mL) of the coliform to the corresponding bulk water samples, the coliforms were able to attach and get established within the mature biofilms. These outcomes emphasize the need for continued research on biofilm detachment and its implications for water contamination in distribution networks.

IMPORTANCE

The revelation that even low concentrations of coliforms can infiltrate into mature drinking water biofilms highlights a potential public health concern. Nowadays, the measurement of coliform bacteria is used as an indicator for fecal contamination and to control the effectiveness of disinfection processes and the cleanliness and integrity of distribution systems. In Flanders (Belgium), 533 out of 18,840 measurements exceeded the established norm for the coliform indicator parameter in 2021; however, the source of microbial contamination is mostly unknown. Here, we showed that mature biofilms, are susceptible to invasion of Serratia fonticola. These findings emphasize the importance of understanding and managing biofilms in drinking water distribution systems, not only for their potential to influence water quality, but also for their role in harboring and potentially disseminating pathogens. Further research into biofilm detachment, long-term responses to operational changes, and pathogen persistence within biofilms is crucial to inform strategies for safeguarding drinking water quality.

Domestic hot-water boilers harbour active thermophilic bacterial communities distinctly different from those in the cold-water supply

Running cold and hot water in buildings is a widely established commodity. However, interests regarding hygiene and microbiological aspects had so far been focussed on cold water. Little attention has been given to the microbiology of domestic hot-water installations (DHWIs), except for aspects of pathogenic Legionella. World-wide, regulations consider hot (or warm) water as 'heated drinking water' that must comply (cold) drinking water (DW) standards. However, the few reports that exist indicate presence and growth of microbial flora in DHWIs, even when supplied with water with disinfectant residual. Using flow cytometric (FCM) total cell counting (TCC), FCM-fingerprinting, and 16S rRNA-gene-based metagenomic analysis, the characteristics and composition of bacterial communities in cold drinking water (DW) and hot water from associated boilers (operating at 50 - 60 °C) was studied in 14 selected inhouse DW installations located in Switzerland and Austria. A sampling strategy was applied that ensured access to the bulk water phase of both, supplied cold DW and produced hot boiler water. Generally, 1.3- to 8-fold enhanced TCCs were recorded in hot water compared to those in the supplied cold DW. FCM-fingerprints of cold and corresponding hot water from individual buildings indicated different composition of cold- and hot-water microbial floras. Also, hot waters from each of the boilers sampled had its own individual FCM-fingerprint. 16S rRNA-gene-based metagenomic analysis confirmed the marked differences in composition of microbiomes. E.g., in three neighbouring houses supplied from the same public network pipe each hot-water boiler contained its own thermophilic bacterial flora. Generally, bacterial diversity in cold DW was broad, that in hot water was restricted, with mostly thermophilic strains from the families Hydrogenophilaceae, Nitrosomonadaceae and Thermaceae dominating. Batch growth assays, consisting of cold DW heated up to 50 - 60 °C and inoculated with hot water, resulted in immediate cell growth with doubling times between 5 and 10 h. When cold DW was used as an inoculum no significant growth was observed. Even boilers supplied with UVC-treated cold DW contained an actively growing microbial flora, suggesting such hot-water systems as autonomously operating, thermophilic bioreactors. The generation of assimilable organic carbon from dissolved organic carbon due to heating appears to be the driver for growth of thermophilic microbial communities. Our report suggests that a man-made microbial ecosystem, very close to us all and of potential hygienic importance, may have been overlooked so far. Despite consumers having been exposed to microbial hot-water flora for a long time, with no major pathogens so far been associated specifically with hot-water usage (except for Legionella), the role of harmless thermophiles and their interaction with potential human pathogens able to grow at elevated temperatures in DHWIs remains to be investigated.

To gate or not to gate: Revisiting drinking water microbial assessment through flow cytometry fingerprinting

Flow cytometry has been utilized for over a decade as a rapid and reproducible approach to assessing microbial quality of drinking water. However, the need for specialized expertise in gating-a fundamental strategy for distinguishing cell populations-introduces the potential for human error and obstructs the standardization of methods. This work conducts a comprehensive analysis of various gating approaches applied to flow cytometric scatter plots, using a dataset spanning a year. A sensitivity analysis is carried out to examine the impact of different gating strategies on final cell count results. The findings show that dynamic gating, which requires user intervention, is essential for the analysis of highly variable raw waters and distributed water. In contrast, static gating proved suitable for more stable water sources, interstage sample locations, and water presenting a particularly low cell count. Our conclusions suggest that cell count analysis should be supplemented with fluorescence fingerprinting to gain a more complete understanding of the variability in microbial populations within drinking water supplies. Establishing dynamic baselines for each water type in FCM monitoring studies is essential for choosing the correct gating strategy. FCM fingerprinting offers a dynamic approach to quantify treatment processes, enabling options for much better monitoring and control. This study offers new insights into the vagaries of various flow cytometry gating strategies, thereby substantially contributing to best practices in the water industry. The findings foster more efficient and reliable water analysis, improving of standardizing methods in microbial water quality assessment using FCM.

Predicting the performance of chain elongating microbiomes through flow cytometric fingerprinting

As part of the circular bio-economy paradigm shift, waste management and valorisation practices have moved away from sanitation and towards the production of added-value compounds. Recently, the development of mixed culture bioprocess for the conversion of waste(water) to platform chemicals, such as medium chain carboxylic acids, has attracted significant interest. Often, the microbiology of these novel bioprocesses is less diverse and more prone to disturbances, which can lead to process failure. This issue can be tackled by implementing an advanced monitoring strategy based on the microbiology of the process. In this study, flow cytometry was used to monitor the microbiology of lactic acid chain elongation for the production of caproic acid, and assess its performance both qualitatively and quantitatively. Two continuous stirred tank reactors for chain elongation were monitored flow cytometrically for over 336 days. Through community typing, four specific community types could be identified and correlated to both a specific functionality and genotypic diversity. Additionally, the machine-learning algorithms trained in this study demonstrated the ability to predict production rates of, amongst others, caproic acid with high accuracy in the present (R² > 0.87) and intermediate accuracy in the near future (R² > 0.63). The identification of specific community types and the development of predictive algorithms form the basis of advanced bioprocess monitoring based on flow cytometry, and have the potential to improve bioprocess control and optimization, leading to better product quality and yields.

Opportunities in optical and electrical single-cell technologies to study microbial ecosystems

New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.

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.

Development of an Automated Online Flow Cytometry Method to Quantify Cell Density and Fingerprint Bacterial Communities

Cell density is an important factor in all microbiome research, where interactions are of interest. It is also the most important parameter for the operation and control of most biotechnological processes. In the past, cell density determination was often performed offline and manually, resulting in a delay between sampling and immediate data processing, preventing quick action. While there are now some online methods for rapid and automated cell density determination, they are unable to distinguish between the different cell types in bacterial communities. To address this gap, an online automated flow cytometry procedure is proposed for real-time high-resolution analysis of bacterial communities. On the one hand, it allows for the online automated calculation of cell concentrations and, on the other, for the differentiation between different cell subsets of a bacterial community. To achieve this, the OC-300 automation device (onCyt Microbiology, Zürich, Switzerland) was coupled with the flow cytometer CytoFLEX (Beckman Coulter, Brea, USA). The OC-300 performs the automatic sampling, dilution, fixation and 4',6-diamidino-2-phenylindole (DAPI) staining of a bacterial sample before sending it to the CytoFLEX for measurement. It is demonstrated that this method can reproducibly measure both cell density and fingerprint-like patterns of bacterial communities, generating suitable data for powerful automated data analysis and interpretation pipelines. In particular, the automated, high-resolution partitioning of clustered data into cell subsets opens up the possibility of correlation analysis to identify the operational or abiotic/biotic causes of community disturbances or state changes, which can influence the interaction potential of organisms in microbiomes or even affect the performance of individual organisms.

Can online particle counters and electrochemical sensors distinguish normal periodic and aperiodic drinking water quality fluctuations from contamination?

Early warning systems monitoring the quality of drinking water need to distinguish between normal quality fluctuations and those caused by contaminants. Thus, to decrease the number of false positive events, normal water quality fluctuations, whether periodic or aperiodic, need to be characterized. For this, we used a novel flow-imaging particle counter, a light-scattering particle counter, and electrochemical sensors to monitor the drinking water quality of a pressure zone in a building complex for 109 days. Data were analyzed to determine the feasibility of the sensors and particle counters to distinguish periodic and aperiodic fluctuations from real-life contaminants. The concentrations of particles smaller than 10 μm and N, Small, Large, and B particles showed sudden changes recurring daily, likely due to the flow rate changes in the building complex. Conversely, the concentrations of larger than 10 μm particles and C particles, in addition to the responses of electrochemical sensors, remained in their low typical values despite flow rate changes. The aperiodic events, likely resulting from an abnormally high flow rate in the water mains due to maintenance, were detected using particle counters and electrochemical sensors. This study provides insights into choosing water quality sensors by showing that machine learning-based particle classes, such as B, C, F, and particles larger than 10 μm are promising in distinguishing contamination from aperiodic and periodic fluctuations while the use of other particle classes and electrochemical sensors may require dynamic baseline to decrease false positive events in an early warning system.

Exploration of microbiome diversity of stacked fermented grains by flow cytometry and cell sorting

Sauce-flavor baijiu is one of the twelve flavor types of Chinese distilled fermented product. Microbial composition plays a key role in the stacked fermentation of Baijiu, which uses grains as raw materials and produces flavor compounds, however, the active microbial community and its relationship remain unclear. Here, we investigated the total and active microbial communities of stacked fermented grains of sauce-flavored Baijiu using flow cytometry and high-throughput sequencing technology, respectively. By using traditional high-throughput sequencing technology, a total of 24 bacterial and 14 fungal genera were identified as the core microbiota, the core bacteria were Lactobacillus (0.08–39.05%), Acetobacter (0.25–81.92%), Weissella (0.03–29.61%), etc. The core fungi were Issatchenkia (23.11–98.21%), Monascus (0.02–26.36%), Pichia (0.33–37.56%), etc. In contrast, using flow cytometry combined with high-throughput sequencing, the active dominant bacterial genera after cell sorting were found to be Herbaspirillum, Chitinophaga, Ralstonia, Phenylobacterium, Mucilaginibacter, and Bradyrhizobium, etc., whereas the active dominant fungal genera detected were Aspergillus, Pichia, Exophiala, Candelabrochaete, Italiomyces, and Papiliotrema, etc. These results indicate that although the abundance of Acetobacter, Monascus, and Issatchenkia was high after stacked fermentation, they may have little biological activity. Flow cytometry and cell sorting techniques have been used in the study of beer and wine, but exploring the microbiome in such a complex environment as Chinese baijiu has not been reported. The results also reveal that flow cytometry and cell sorting are convenient methods for rapidly monitoring complex microbial flora and can assist in exploring complex environmental samples.

Monitoring groundwater quality with real-time data, stable water isotopes, and microbial community analysis: A comparison with conventional methods

Groundwater provides much of the world's potable water. Nevertheless, groundwater quality monitoring programmes often rely on a sporadic, slow, and narrowly focused combination of periodic manual sampling and laboratory analyses, such that some water quality deficiencies go undetected, or are detected too late to prevent adverse consequences. In an effort to address this shortcoming, we conducted enhanced monitoring of untreated groundwater quality over 12 months (February 2019-February 2020) in four shallow wells supplying potable water in Finland. We supplemented periodic manual sampling and laboratory analyses with (i) real-time online monitoring of physicochemical and hydrological parameters, (ii) analysis of stable water isotopes from groundwater and nearby surface waters, and (iii) microbial community analysis of groundwater via amplicon sequencing of the 16S rRNA gene and 16S rRNA. We also developed an early warning system (EWS) for detecting water quality anomalies by automating real-time online monitoring data collection, transfer, and analysis - using electrical conductivity (EC) and turbidity as indirect water quality indicators. Real-time online monitoring measurements were largely in fair agreement with periodic manual measurements, demonstrating their usefulness for monitoring water quality; and the findings of conventional monitoring, stable water isotopes, and microbial community analysis revealed indications of surface water intrusion and faecal contamination at some of the studied sites. With further advances in technology and affordability expected into the future, the supplementary methods used here could be more widely implemented to enhance groundwater quality monitoring - by contributing new insights and/or corroborating the findings of conventional analyses.

Gradual Recovery of Building Plumbing-Associated Microbial Communities after Extended Periods of Altered Water Demand during the COVID-19 Pandemic

COVID-19 pandemic-related building restrictions heightened drinking water microbiological safety concerns post-reopening due to the unprecedented nature of commercial building closures. Starting with phased reopening (i.e., June 2020), we sampled drinking water for 6 months from three commercial buildings with reduced water usage and four occupied residential households. Samples were analyzed using flow cytometry and full-length 16S rRNA gene sequencing along with comprehensive water chemistry characterization. Prolonged building closures resulted in 10-fold higher microbial cell counts in the commercial buildings [(2.95 ± 3.67) × 105 cells mL-1] than in residential households [(1.11 ± 0.58) × 104 cells mL-1] with majority intact cells. While flushing reduced cell counts and increased disinfection residuals, microbial communities in commercial buildings remained distinct from those in residential households on the basis of flow cytometric fingerprinting [Bray-Curtis dissimilarity (dBC) = 0.33 ± 0.07] and 16S rRNA gene sequencing (dBC = 0.72 ± 0.20). An increase in water demand post-reopening resulted in gradual convergence in microbial communities in water samples collected from commercial buildings and residential households. Overall, we find that the gradual recovery of water demand played a key role in the recovery of building plumbing-associated microbial communities as compared to short-term flushing after extended periods of reduced water demand.

Impact of different source-water switching patterns on the stability of drinking water in an estuarine urban water distribution system

Source-water switching can lead to instability in drinking water distribution systems. In estuarine cities using surface water as source water where salt tide occasionally happens, the influence can be particularly complex due to changes of Larson Index (LI). The objective of this study was to investigate the effects of different switching patterns on the stability of water in an estuarine city. Fluctuated LI was found in the current distribution system. LI of the new source water was lower and more stable. Susceptible areas with a high frequency of over standard water quality were identified and pipe scales there were mainly composed of relatively stable iron oxides with dense crystal structures (Fe₃O₄ and α-FeOOH). Two old pipe sections were used to simulate different switching patterns. The microbial risk did not increase significantly when the original and new water sources were combined in different ratios (2∶8, 5∶5), when multiple water sources were used (3∶3∶4) or when salinity increased. The better water quality, lower LI of the new source water, and stability of the current distribution system together contributed to the biostability. Total iron increased after switching, then declined and stabilized for most switching patterns. Salt tide can lead to sharp iron release. The results provided insightful information for distribution systems that have cast iron pipes and that might encounter source-water switching patterns.

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.

Microbiomes in drinking water treatment and distribution: A meta-analysis from source to tap

A meta-analysis of existing and available Illumina 16S rRNA datasets from drinking water source, treatment and drinking water distribution systems (DWDS) were collated to compare changes in abundance and diversity throughout. Samples from bulk water and biofilm were used to assess principles governing microbial community assembly and the value of amplicon sequencing to water utilities. Individual phyla relationships were explored to identify competitive or synergistic factors governing DWDS microbiomes. The relative importance of stochasticity in the assembly of the DWDS microbiome was considered to identify the significance of source and treatment in determining communities in DWDS. Treatment of water significantly reduces overall species abundance and richness, with chlorination of water providing the most impact to individual taxa relationships. The assembly of microbial communities in the bulk water of the source, primary treatment process and DWDS is governed by more stochastic processes, as is the DWDS biofilm. DWDS biofilm is significantly different from bulk water in terms of local contribution to beta diversity, type and abundance of taxa present. Water immediately post chlorination has a more deterministic microbial assembly, highlighting the significance of this process in changing the microbiome, although elevated levels of stochasticity in DWDS samples suggest that this may not be the case at customer taps. 16S rRNA sequencing is becoming more routine, and may have several uses for water utilities, including: detection and risk assessment of potential pathogens such as those within the genera of Legionella and Mycobacterium; assessing the risk of nitrification in DWDS; providing improved indicators of process performance and monitoring for significant changes in the microbial community to detect contamination. Combining this with quantitative methods like flow cytometry will allow a greater depth of understanding of the DWDS microbiome.

Potential of Flow Cytometric Approaches for Rapid Microbial Detection and Characterization in the Food Industry-A Review

As microbial contamination is persistent within the food and bioindustries and foodborne infections are still a significant cause of death, the detection, monitoring, and characterization of pathogens and spoilage microorganisms are of great importance. However, the current methods do not meet all relevant criteria. They either show (i) inadequate sensitivity, rapidity, and effectiveness; (ii) a high workload and time requirement; or (iii) difficulties in differentiating between viable and non-viable cells. Flow cytometry (FCM) represents an approach to overcome such limitations. Thus, this comprehensive literature review focuses on the potential of FCM and fluorescence in situ hybridization (FISH) for food and bioindustry applications. First, the principles of FCM and FISH and basic staining methods are discussed, and critical areas for microbial contamination, including abiotic and biotic surfaces, water, and air, are characterized. State-of-the-art non-specific FCM and specific FISH approaches are described, and their limitations are highlighted. One such limitation is the use of toxic and mutagenic fluorochromes and probes. Alternative staining and hybridization approaches are presented, along with other strategies to overcome the current challenges. Further research needs are outlined in order to make FCM and FISH even more suitable monitoring and detection tools for food quality and safety and environmental and clinical approaches.

Predicting the Presence and Abundance of Bacterial Taxa in Environmental Communities through Flow Cytometric Fingerprinting

Microbiome management research and applications rely on temporally resolved measurements of community composition. Current technologies to assess community composition make use of either cultivation or sequencing of genomic material, which can become time-consuming and/or laborious in case high-throughput measurements are required. Here, using data from a shrimp hatchery as an economically relevant case study, we combined 16S rRNA gene amplicon sequencing and flow cytometry data to develop a computational workflow that allows the prediction of taxon abundances based on flow cytometry measurements. The first stage of our pipeline consists of a classifier to predict the presence or absence of the taxon of interest, with yielded an average accuracy of 88.13% ± 4.78% across the top 50 operational taxonomic units (OTUs) of our data set. In the second stage, this classifier was combined with a regression model to predict the relative abundances of the taxon of interest, which yielded an average R² of 0.35 ± 0.24 across the top 50 OTUs of our data set. Application of the models to flow cytometry time series data showed that the generated models can predict the temporal dynamics of a large fraction of the investigated taxa. Using cell sorting, we validated that the model correctly associates taxa to regions in the cytometric fingerprint, where they are detected using 16S rRNA gene amplicon sequencing. Finally, we applied the approach of our pipeline to two other data sets of microbial ecosystems. This pipeline represents an addition to the expanding toolbox for flow cytometry-based monitoring of bacterial communities and complements the current plating- and marker gene-based methods.

IMPORTANCE Monitoring of microbial community composition is crucial for both microbiome management research and applications. Existing technologies, such as plating and amplicon sequencing, can become laborious and expensive when high-throughput measurements are required. In recent years, flow cytometry-based measurements of community diversity have been shown to correlate well with those derived from 16S rRNA gene amplicon sequencing in several aquatic ecosystems, suggesting that there is a link between the taxonomic community composition and phenotypic properties as derived through flow cytometry. Here, we further integrated 16S rRNA gene amplicon sequencing and flow cytometry survey data in order to construct models that enable the prediction of both the presence and the abundances of individual bacterial taxa in mixed communities using flow cytometric fingerprinting. The developed pipeline holds great potential to be integrated into routine monitoring schemes and early warning systems for biotechnological applications.

Evaluation of enzyme activity for monitoring biofiltration performance in drinking water treatment

Many water providers monitor adenosine triphosphate (ATP) as an indicator of biological acclimation of their biofilters; however, strong correlations between ATP concentration and filter performance (e.g., organic matter or disinfection by-product precursor removal) are not typically observed. As an alternative, this study evaluated the use of enzyme activity for monitoring biological processes within filters. Recent studies have proposed that enzyme activity may be used as an indicator of biofilter function as it provides a means to quantify biodegradation which may allow for a more accurate measure of degradation potential and to gain a better understanding of biofilter performance. Sampling was completed from full- and pilot-scale biofilters to assess impacts associated with pre-treatments, varying sources waters, as well as pre-treatment and operating conditions. Enzyme activity (carboxylic esterase, phosphatase, ß-glucosidase, α-glucosidase, ß-xylosidase, chitinase, and cellulase) and ATP were measured from the top 5 cm of biofilter media representative of typical full-scale sampling; water quality parameters included dissolved organic carbon (DOC) and disinfection by-products (DBPs): trihalomethane (THM) formation potential (FP), and haloacetic acid FP (HAA FP). Results confirmed that ATP was not a reliable monitoring tool for DOC and DBP FP reduction in biofilters. A strong relationship was observed between esterase activity and DOC reduction; chitinase activity significantly correlated to THM FP reduction for filters treating three different source waters and HAA FP reduction achieved by filters treating the same source water with a range of pre-treatment and backwash conditions. This study showed that enzyme activity may be appropriate for monitoring biological processes within drinking water filters and may act as a surrogate for the removal of organic compounds.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

Online microbial monitoring of drinking water: How do different techniques respond to contaminations in practice?

Safeguarding the microbial water quality remains a challenge for drinking water utilities, and because of population growth and climate change, new issues arise regularly. To overcome these problems, biostable drinking water production and water reuse will become increasingly important. In this respect, high-resolution online microbial monitoring during treatment and distribution could prove essential. Here, we present the first scientific and practical comparison of multiple online microbial monitoring techniques in which six commercially available devices were set up in a full-scale drinking water production plant. Both the devices' response towards operational changes and contaminations, as well as their detection limit for different contaminations were evaluated and compared. During normal operation, all devices were able to detect abrupt operational changes such as backwashing of activated carbon filters and interruption of the production process in a fast and sensitive way. To benchmark their response to contaminations, the calculation of a dynamic baseline for sensitive separation between noise and events is proposed. In order of sensitivity, enzymatic analysis, ATP measurement, and flow cytometric fingerprinting were the most performant for detection of rain- and groundwater contaminations (0.01 - 0.1 v%). On the other hand, optical classification and flow cytometric cell counts showed to be more robust techniques, requiring less maintenance and providing direct information about the cell concentration, even though they were still more sensitive than plate counting. The choice for a certain technology will thus depend on the type of application and is a balance between sensitivity, price and maintenance. All things considered, a combination of several devices and use of advanced data analysis such as fingerprinting may be of added value. In general, the strategic implementation of online microbial monitoring as early-warning system will allow for intensive quality control by high-frequency sampling as well as a short event response timeframe.

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.

Computational Analysis of Microbial Flow Cytometry Data

Flow cytometry is an important technology for the study of microbial communities. It grants the ability to rapidly generate phenotypic single-cell data that are both quantitative, multivariate and of high temporal resolution. The complexity and amount of data necessitate an objective and streamlined data processing workflow that extends beyond commercial instrument software. No full overview of the necessary steps regarding the computational analysis of microbial flow cytometry data currently exists. In this review, we provide an overview of the full data analysis pipeline, ranging from measurement to data interpretation, tailored toward studies in microbial ecology. At every step, we highlight computational methods that are potentially useful, for which we provide a short nontechnical description. We place this overview in the context of a number of open challenges to the field and offer further motivation for the use of standardized flow cytometry in microbial ecology research.

Dynamic Hydraulics in a Drinking Water Distribution System Influence Suspended Particles and Turbidity, But Not Microbiology

Spatial and short-term temporal changes in water quality as a result of water age and fluctuating hydraulic conditions were investigated in a drinking water distribution system. Online measurements of total and intracellular adenosine tri-phosphate (ATP), total and intact cell concentrations measured with flow cytometry (FCM), turbidity, and particle counts were performed over five weeks at five subsequent locations of the distribution system. The high number of parallel FCM and ATP measurements revealed the combined effect of water age and final disinfection on spatial changes in microbiology in the system. The results underlined that regular daily dynamics in flow velocities are normal and inevitable in drinking water distribution systems, and significantly impact particle counts and turbidity. However, hydraulic conditions had no detectable impact on the concentration of suspended microbial cells. A weak correlation between flow velocity and ATP concentrations suggests incidental resuspension of particle-bound bacteria, presumably caused by either biofilm detachment or resuspension from sediment when flow velocities increase. The highly dynamic hydraulic conditions highlight the value of online monitoring tools for the meaningful description of short-term dynamics (day-scale) in drinking water distribution systems.