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

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.

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.

Application of flow cytometry for rapid, high-throughput, multiparametric analysis of environmental microbiomes

Quantification of the abundance and understanding of the dynamics of the microbial communities is essential to establish a basis for microbiome characterization. The conventional techniques used for the quantification of microbes are complicated and time-consuming. With scientific advancement, many techniques evolved and came into account. Among them, flow cytometry is a robust, high-throughput technique through which microbial dynamics, morphology, microbial distribution, physiological characteristics, and many more attributes can be studied in a high-throughput manner with comparatively less time and resources. Flow cytometry, when combined with other omics-based methods, offers a rapid and efficient platform to analyze and understand the composition of microbiome at the cellular level. The microbial diversity observed through flow cytometry will not be equivalent to that obtained by sequencing methods, but this integrated approach holds great potential for high throughput characterization of microbiomes. Flow cytometry is regarded as an established characterization tool in haematology, oncology, immunology, and medical microbiology research; however, its application in environmental microbiology is yet to be explored. This comprehensive review aims to delve into the diverse environmental applications of flow cytometry across various domains, including but not limited to bioremediation, landfills, anaerobic digestion, industrial bioprocesses, water quality regulation, and soil quality regulation. By conducting an in-depth analysis, this article seeks to shed light on the potential benefits and challenges associated with the utilization of flow cytometry in addressing environmental concerns.

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.

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.

Stagnation trigger changes to tap water quality in winter season: Novel insights into bacterial community activity and composition

The drinking water distribution system is important for water supply and it affects the quality of the drinking water. Indoor pipeline water quality is regulated by physical, hydraulic and biological elements, such as indoor temperature and stagnation. In this work, the effects of indoor heating and overnight stagnation on the variation in bacterial community structure and the total cell count were assessed by full-length 16S rRNA gene sequencing and flow cytometry, respectively. The results exhibited that the average intact cell count was 6.99 × 10⁴ cells/mL and the low nucleic acid (LNA) bacteria was 4.48 × 10⁴ cells/mL after stagnation. The average concentration of total and intracellular adenosine triphosphate (ATP) was 3.64 × 10^-12 gATP/mL and 3.13 × 10^-17 gATP/cell in stagnant water, respectively. The growth of LNA cells played a crucial role in increasing ATP. The dominant phylum observed was Proteobacteria (87.21 %), followed by Actinobacteria (8.25 %). Opportunistic pathogens increased the risk of disease in stagnant water (up to 1.2-fold for Pseudomonas sp. and 5.8-fold for Mycobacterium sp.). Meanwhile, structural equation model (SEM) and redundancy analysis (RDA) also illustrated that water temperature, residual chlorine and Fe significantly affected the abundance and composition of bacterial community. Taking together, these results show response of tap water quality to overnight stagnation and indoor heating, and provide scientific basis for drinking water security management in winter season.