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Microbial flow cytometry can rapidly characterize the status of microbial communities. Upon measurement, large amounts of quantitative single-cell data are generated, which need to be analyzed appropriately. Cytometric fingerprinting approaches are often used for this purpose. Traditional approaches either require a manual annotation of regions of interest, do not fully consider the multivariate characteristics of the data, or result in many community-describing variables. To address these shortcomings, we propose an automated model-based fingerprinting approach based on Gaussian mixture models, which we call PhenoGMM. The method successfully quantifies changes in microbial community structure based on flow cytometry data, which can be expressed in terms of cytometric diversity. We evaluate the performance of PhenoGMM using data sets from both synthetic and natural ecosystems and compare the method with a generic binning fingerprinting approach. PhenoGMM supports the rapid and quantitative screening of microbial community structure and dynamics. IMPORTANCE Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technology to characterize microbial community diversity and dynamics. The technology enables a fast measurement of optical properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian mixture models. We evaluated our workflow on data sets from both synthetic and natural ecosystems, illustrating its general applicability for the analysis of microbial flow cytometry data. PhenoGMM supports a rapid and quantitative analysis of microbial community structure using flow cytometry., (Copyright © 2021 Rubbens et al.)

Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantifies the distances between single-cell measurements. In most cases, researchers simply use the Euclidean distance metric. In this article, we exploit the availability of single-cell labels to find an optimal Mahalanobis distance metric derived from the data. We show that such a Mahalanobis distance metric results in an improved identification of cell populations compared with the Euclidean distance metric. Once determined, it can be used for the analysis of multiple samples that were measured under the same experimental setup. We illustrate this approach for cytometry data from two different origins, that is, flow cytometry applied to microbial cells and mass cytometry for the analysis of human blood cells. We also illustrate that such a distance metric results in an improved identification of cell populations when clustering methods are employed. Generally, these results imply that the performance of data analysis techniques can be improved by using a more advanced distance metric. © 2019 International Society for Advancement of Cytometry., (© 2019 International Society for Advancement of Cytometry.)

Species invasion is an important disturbance to ecosystems worldwide, yet knowledge about the impacts of invasive species on bacterial communities remains sparse. Using a novel approach, we simultaneously detected phenotypic and derived taxonomic change in a natural bacterioplankton community when subjected to feeding pressure by quagga mussels, a widespread aquatic invasive species. We detected a significant decrease in diversity within 1 h of feeding and a total diversity loss of 11.6 ± 4.1% after 3 h. This loss of microbial diversity was caused by the selective removal of high nucleic acid populations (29 ± 5% after 3 h). We were able to track the community diversity at high temporal resolution by calculating phenotypic diversity estimates from flow cytometry (FCM) data of minute amounts of sample. Through parallel FCM and 16S rRNA gene amplicon sequencing analysis of environments spanning a broad diversity range, we showed that the two approaches resulted in highly correlated diversity measures and captured the same seasonal and lake-specific patterns in community composition. Based on our results, we predict that selective feeding by invasive dreissenid mussels directly impacts the microbial component of the carbon cycle, as it may drive bacterioplankton communities toward less diverse and potentially less productive states., (© 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.)

The analysis of microbial populations is fundamental, not only for developing a deeper understanding of microbial communities but also for their engineering in biotechnological applications. Many methods have been developed to study their characteristics and over the last few decades, molecular analysis tools, such as DNA sequencing, have been used with considerable success to identify the composition of microbial populations. Recently, flow cytometric fingerprinting is emerging as a promising and powerful method to analyze bacterial populations. So far, these methods have primarily been used to observe shifts in the composition of microbial communities of natural samples. In this article, we apply a flow cytometric fingerprinting method to discriminate among 29 Lactobacillus strains. Our results indicate that it is possible to discriminate among 27 Lactobacillus strains by staining with SYBR green I and that the discriminatory power can be increased by combined SYBR green I and propidium iodide staining. Furthermore, we illustrate the impact of physiological changes on the fingerprinting method by demonstrating how flow cytometric fingerprinting is able to discriminate the different growth phases of a microbial culture. The sensitivity of the method is assessed by its ability to detect changes in the relative abundance of a mix of polystyrene beads down to 1.2%. When a mix of bacteria was used, the sensitivity was as between 1.2% and 5%. The presented data demonstrate that flow cytometric fingerprinting is a sensitive and reproducible technique with the potential to be applied as a method for the dereplication of bacterial isolates. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

Multicolor approaches are challenging for microbial flow cytometry; as flow cytometers are mainly developed for biomedical applications, modern instruments contain more detectors than needed. Some of these additional fluorescence detectors measure biological information due to spectral overlap, yet the extent to which this information is relevant for the identification of bacterial populations is ambiguous. In this paper we characterize the usefulness of these additional detectors. We propose a data-driven detector selection method to select the smallest subset of detectors that will optimally discriminate between bacterial populations. Using a detector elimination strategy, we show that one or more detectors can be removed without loss of resolving power. A number of additional detectors are included in the final subset, which help to improve the identification of bacterial populations. Experimental data were retrieved from two types of modern cytometers with different configurations. The method reveals a clear ordering of detector importances, which depends on the instrument from which the data were retrieved. In addition, we were able to pinpoint unexpected behavior of SYBR Green I in the red spectrum. As the field of microbial flow cytometry is maturing, these results motivate the construction of a different kind of cytometric instruments for microbiologists, for which the number of detectors is reduced, but tailored toward the characteristics of microbial experiments. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

Drinking water networks need maintenance every once in a while, either planned interventions or emergency repairs. When this involves opening of the water pipes, precautionary measures need to be taken to avoid contamination of the drinking water at all time. Drinking water suppliers routinely apply plating for faecal indicator organisms as quality control in such a situation. However, this takes at least 21 h of waiting time, which can be crucial when dealing with major supply pipes. A combination of flow cytometric (FCM) bacterial cell counts with FCM fingerprinting techniques is proposed in this study as a fast and sensitive additional technique. In three full scale situations, major supply pipes with 400-1050 mm diameter were emptied for maintenance, shock-chlorinated and flushed with large amounts of clean drinking water before taking back in operation. FCM measurements of the discharged flushing water revealed fast lowering and stabilizing bacterial concentrations once flushing is initiated. Immediate comparison with clean reference drinking water used for flushing was done, and the moment when both waters had similar bacterial concentrations was considered as the endpoint of the necessary flushing works. This was usually after 2-4 h of flushing. FCM fingerprinting, based on both bacteria and FCM background, was used as additional method to verify how similar flushing and reference samples were and yielded similar results. The FCM approved samples were several hours later approved as well by the drinking water supplier after plating and incubation for total Coliforms and Enterococci. These were used as decisive control to set the pipes back in operation. FCM proved to be a more conservative test than plating, yet it yielded immediate results. Application of these FCM methods can therefore avoid long unnecessary waiting times and large drinking water losses., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called in silico communities, which allow us to explore the possibilities of bacterial flow cytometry data using supervised machine learning techniques. We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic (i.e., in vitro) communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general., Competing Interests: The authors have declared that no competing interests exist.

Flow cytometry is a rapid and quantitative method to determine bacterial viability. Although different stains can be used to establish viability, staining protocols are inconsistent and lack a general optimization approach. Very few "true" multicolor protocols, where dyes are combined in one sample, have been developed for microbiological applications. In this mini-review, the discrepancy between protocols for cell-permeant nucleic acid and functional stains are discussed as well as their use as viability dyes. Furthermore, optimization of staining protocols for a specific setup are described. Original data using the red-excitable SYTO dyes SYTO 59 to 64 and SYTO 17, combined with functional stains, for double and triple staining applications is also included. As each dye and dye combination behaves differently within a certain combination of medium matrix, microorganism, and instrument, protocols need to be tuned to obtain reproducible results. Therefore, single, double, and triple stains are reviewed, including the different parameters that influence staining such as stain kinetics, optimal stain concentration, and the effect of the chelator EDTA as membrane permeabilizer. In the last section, we highlight the need to investigate the stability of multicolor assays to ensure correct results as multiwell autoloaders are now commonly used.

The impact of multi-well plate automation on bacterial flow cytometric analyses was investigated. Cell concentrations in up to 96 samples can be measured accurately, as long as a reproducible staining protocol and a total measurement time of below 80 min is used. Fluorescence distribution in the samples may, however, display some variability., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Characterizing the microbial community of water is important in different domains, ranging from food and beverage production to wastewater treatment. Conventional methods, such as heterotrophic plate count, selective plating and molecular techniques, are time consuming and labor intensive. A flow cytometry based approach was developed for a fast and objective comparison of microbial communities based on the distribution of cellular features from single cells within these communities. The method consists of two main parts, firstly the generation of fingerprint data by flow cytometry and secondly a novel statistical pipeline for the analysis of flow cytometric data. The combined method was shown to be useful for the discrimination and classification of different brands of drinking water. It was also successfully applied to detect changes in microbial community composition of drinking water caused by changing environmental factors. Generally, the method can be used as a fast fingerprinting method of microbial communities in aquatic samples and as a tool to detect shifts within these communities., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Recent developments in host-microbe research give rise to a growing demand for rapid and accurate methods to quantify bacterial adhesion to epithelial cells. Here, we describe a new flow cytometric method to determine the amount and viability of gut bacteria, adhered to a monolayer of differentiated cells. The latter is a more relevant epithelium model than the suspended eukaryotic cells currently used in flow cytometric protocols. During the development of the method, we monitored the adhesion potential of six bacterial species and an intestinal microbial community to Caco-2 cells. The combination of SYBR Green I/propidium iodide was more efficient than carboxyfluorescein diacetate to stain the bacterial cells. In addition, a better separation between the Caco-2 background signal and viable and dead bacteria was obtained. A precise amount of Triton X-100 was used to detach adhered bacteria from Caco-2 cells and cell debris. Yet, a limited decrease in viability was observed for the intestinal microbial community treated with Triton X-100. The flow cytometric lower detection limit for pure bacterial cultures was 3.0-4.0log/mL, whereas a 5.0-5.5log/mL detection limit was obtained in the presence of Caco-2 cell background. The latter was sufficient to quantify adhered bacteria. To the best of our knowledge, this is the first description of a flow cytometric protocol that quantifies adhesion of both pure and mixed gut microbial cultures to a differentiated monolayer of Caco-2 cells and that allows to distinguish between viable and dead adhered bacteria., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Flow cytometry (FCM) is rapidly becoming an essential tool in the field of aquatic microbiology. It provides opportunities for microbial analysis at both the community and single-cell levels. Compared with other techniques, FCM facilitates rapid data acquisition and multi-parameter analysis, leading to increased popularity and widespread applications. Here, we briefly review the current status of FCM in the field of microbiology, focusing on its recent applications in aquatic microbiology. These developments range from straightforward total cell counts to community structure analysis, and further extend to physiological analysis at a single-cell level. Exciting future prospects for the applications of FCM in aquatic microbiology are also discussed based on current scientific and practical needs., (Copyright 2010 Elsevier Ltd. All rights reserved.)

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. [ABSTRACT FROM AUTHOR]

Methane-producing Archaea can be found in a variety of habitats, including the gastrointestinal tract, where they are linked to various diseases. The majority of current monitoring methods can be slow and laborious. To facilitate gut methanogenic Archaea detection, we investigated flow cytometry for rapid quantification based on the autofluorescent F420 cofactor, an essential coenzyme in methanogenesis. The methanogenic population was distinguishable from the SYBR green (SG) and SYBR green/propidium iodide (SGPI) stained background microbiome based on elevated 452 nm emission in Methanobrevibacter smithii spiked controls. As a proof-of-concept, elevated F420-autofluorescence was used to detect and quantify methanogens in 10 faecal samples and 241 in vitro incubated faecal samples. The methanogenic population in faeces, determined through Archaea-specific 16S rRNA gene amplicon sequencing, consisted of Methanobrevibacter and Methanomassiliicoccus. F420-based methanogen quantification in SG and SGPI-stained faecal samples showed an accuracy of 90 and 100% against Archaea proportions determined with universal primers. When compared to methane and Archaea presence, methanogen categorisation in in vitro incubated faeces exhibited an accuracy of 71 and 75%, with a precision of 42 and 70%, respectively. To conclude, flow cytometry is a reproducible and fast method for the detection and quantification of gut methanogenic Archaea. [ABSTRACT FROM AUTHOR]

Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, such as flow cytometry and Raman spectroscopy, which describe optical properties of the individual cell. In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth stages of three replicate Escherichia coli populations were characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high‐throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single‐cell level (i.e., more biochemical information is recorded). Therefore, it can identify distinct phenotypic populations when coupled with analyses tailored toward single‐cell data. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. We propose a computational workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external data set. We recommend using flow cytometry to quantify phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in‐depth analysis of heterogeneity at the single‐cell level. © 2019 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

The influence of different rock mineralogical compositions on element leaching and bio-weathering processes is poorly understood. Here, the role of basalt composition on nutrient leaching (calcium, iron, phosphorus or magnesium) and subsequent support of Cupriavidus metallidurans CH34 growth was evaluated. Seven different basalts were examined. In iron-limiting media, growth could be restored for all basalts tested, while only two basalts could restore growth in magnesium-limiting medium. Only for magnesium growth complementation was correlated with the composition of the basalts tested. Our results showed that basalt composition can affect leaching and availability of different elements, in turn, affecting bacterial growth. [ABSTRACT FROM AUTHOR]

Rapid contamination of drinking water in distribution and storage systems can occur due to pressure drop, backflow, cross-connections, accidents, and bio-terrorism. Small volumes of a concentrated contaminant (e.g., wastewater) can contaminate large volumes of water in a very short time with potentially severe negative health impacts. The technical limitations of conventional, cultivation-based microbial detection methods neither allow for timely detection of such contaminations, nor for the real-time monitoring of subsequent emergency remediation measures (e.g., shock-chlorination). Here we applied a newly developed continuous, ultra high-frequency flow cytometry approach to track a rapid pollution event and subsequent disinfection of drinking water in an 80-min laboratory scale simulation. We quantified total (TCC) and intact (ICC) cell concentrations as well as flow cytometric fingerprints in parallel in real-time with two different staining methods. The ingress of wastewater was detectable almost immediately (i.e., after 0.6% volume change), significantly changing TCC, ICC, and the flow cytometric fingerprint. Shock chlorination was rapid and detected in real time, causing membrane damage in the vast majority of bacteria (i.e., drop of ICC from more than 380 cells µl-1 to less than 30 cells µl-1 within 4 min). Both of these effects as well as the final wash-in of fresh tap water followed calculated predictions well. Detailed and highly quantitative tracking of microbial dynamics at very short time scales and for different characteristics (e.g., concentration, membrane integrity) is feasible. This opens up multiple possibilities for targeted investigation of a myriad of bacterial shortterm dynamics (e.g., disinfection, growth, detachment, operational changes) both in laboratory-scale research and full-scale system investigations in practice. [ABSTRACT FROM AUTHOR]

Microbe-mineral interactions have become of interest for space exploration as microorganisms could be used to biomine from extra-terrestrial material and extract elements useful as micronutrients in life support systems. This research aimed to identify the impact of space flight on the long-term survival of Cupriavidus metallidurans CH34 in mineral water and the interaction with basalt, a lunar-type rock in preparation for the ESA spaceflight experiment, BIOROCK. Therefore, C. metallidurans CH34 cells were suspended in mineral water supplemented with or without crushed basalt and send for 3 months on board the Russian FOTON-M4 capsule. Long-term storage had a significant impact on cell physiology and energy status (by flow cytometry analysis, plate count and intracellular ATP measurements) as 60% of cells stored on ground lost their cell membrane potential, only 17% were still active, average ATP levels per cell were significantly lower and cultivability dropped to 1%. The cells stored in the presence of basalt and exposed to space flight conditions during storage however showed less dramatic changes in physiology, with only 16% of the cells lost their cell membrane potential and 24% were still active, leading to a higher cultivability (50%) and indicating a general positive effect of basalt and space flight on survival. Microbe-mineral interactions and biofilm formation was altered by spaceflight as less biofilm was formed on the basalt during flight conditions. Leaching from basalt also changed (measured with ICP-OES), showing that cells release more copper from basalt and the presence of cells also impacted iron and magnesium concentration irrespective of the presence of basalt. The flight conditions thus could counteract some of the detrimental effects observed after the 3 month storage conditions. [ABSTRACT FROM AUTHOR]

The widespread use of platinum in high-tech and catalytic applications has led to the production of diverse Pt loaded wastewaters. Effective recovery strategies are needed for the treatment of low concentrated waste streams to prevent pollution and to stimulate recovery of this precious resource. The biological recovery of five common environmental Pt-complexes was studied under acidic conditions; the chloro-complexes PtCl42- and PtCl62-, the amine-complex Pt(NH3)4Cl2 and the pharmaceutical complexes cisplatin and carboplatin. Five bacterial species were screened on their platinum recovery potential; the Gram-negative species Shewanella oneidensis MR-1, Cupriavidus metallidurans CH34, Geobacter metallireducens, and Pseudomonas stutzeri, and the Gram-positive species Bacillus toyonensis. Overall, PtCl42- and PtCl62- were completely recovered by all bacterial species while only S. oneidensis and C. metallidurans were able to recover cisplatin quantitatively (99%), all in the presence of H2 as electron donor at pH 2. Carboplatin was only partly recovered (max. 25% at pH 7), whereas no recovery was observed in the case of the Pt-tetraamine complex. Transmission electron microscopy (TEM) revealed the presence of both intra- and extracellular platinum particles. Flow cytometry based microbial viability assessment demonstrated the decrease in number of intact bacterial cells during platinum reduction and indicated C. metallidurans to be the most resistant species. This study showed the effective and complete biological recovery of three common Pt-complexes, and estimated the fate and transport of the Pt-complexes in wastewater treatment plants and the natural environment. [ABSTRACT FROM AUTHOR]

Measuring the microbial diversity in natural and engineered environments is important for ecosystem characterization, ecosystem monitoring and hypothesis testing. Although the conventional assessment through single marker gene surveys has resulted in major advances, the complete procedure remains slow (i.e. weeks to months), labour-intensive and susceptible to multiple sources of laboratory and data processing bias. Growing interest, in highly resolved, temporal surveys of microbial diversity, necessitates rapid, inexpensive and robust analytical platforms that require limited computational effort., Here, we demonstrate that sensitive single-cell measurements of phenotypic attributes, obtained via flow cytometry, can provide fast (i.e. within minutes) first-line assessments of microbial diversity dynamics, without demanding extensive sample preparation and downstream data processing. We developed a data processing pipeline that fits bivariate kernel density functions to phenotypic parameter combinations of an entire microbial community and concatenates them to a single one-dimensional phenotypic fingerprint. By calculating established diversity metrics from such phenotypic fingerprints, we construct an alternative interpretation of the microbial diversity that incorporates distinct phenotypic traits underlying cell-to-cell heterogeneity (i.e. morphology and nucleic acid content)., Based on a detailed longitudinal study of a highly dynamic microbial ecosystem, our approach delivered temporal alpha diversity profiles that strongly correlated with the reference diversity, as estimated by 16S rRNA amplicon sequencing. This strongly suggests that the distribution of a limited amount of phenotypic features within a microbial community already provides sufficient resolving power for the measurement of diversity dynamics at the species level., We present a fast, robust analysis method for monitoring the microbial biodiversity of natural and engineered ecosystems that correlates well with the conventional marker gene surveys. Our work has both applied and fundamental implications that stretch from ecosystem monitoring and studies on microbial community dynamics, to supervised sampling strategies. Furthermore, our approach offers perspectives for the development of online and in situ monitoring systems for microbial ecosystems. [ABSTRACT FROM AUTHOR]

Bacterial growth in drinking water networks can result in health-based implications, affect network hydrology and induce customer complaints. In this study, cultivation-based methods were compared to flow cytometric methods for the study of growth in a local drinking water network. Comparison of flow cytometric cell concentrations indicated growth in several samples, while further data analysis with fingerprinting algorithms showed the different origin of this growth; low similarity between samples with elevated cell counts indicated that growth occurred mainly in the sampled household plumbing installations instead of centrally in the water network. Fast obtained flow cytometric data made this thorough analysis possible, while cultivation-based methods were yielding too scarce information. Flow cytometry showed to be more rapid, complete, and accurate than cultivationbased methods for a network growth study. It is proposed as a future useful tool for the fast detection of microbial point contaminations in drinking water networks. [ABSTRACT FROM AUTHOR]

Two 4-chloro-2-methylphenoxyacetic acid (MCPA)-degrading enrichment cultures selected from an aquifer on low (0.1 mg liter-1) or high (25 mg liter-1) MCPA concentrations were compared in terms of metabolic activity, community composition, population growth, and single cell physiology. Different community compositions and major shifts in community structure following exposure to different MCPA concentrations were observed using both 16S rRNA gene denaturing gradient gel electrophoresis fingerprinting and pyrosequencing. The communities also differed in their MCPA-mineralizing activities. The enrichments selected on low concentrations mineralized MCPA with shorter lag phases than those selected on high concentrations. Flow cytometry measurements revealed that mineralization led to cell growth. The presence of low-nucleic acid-content bacteria (LNA bacteria) was correlated with mineralization activity in cultures selected on low herbicide concentrations. This suggests that LNA bacteria may play a role in degradation of low herbicide concentrations in aquifers impacted by agriculture. This study shows that subpopulations of herbicide-degrading bacteria that are adapted to different pesticide concentrations can coexist in the same environment and that using a low herbicide concentration enables enrichment of apparently oligotrophic subpopulations. [ABSTRACT FROM AUTHOR]

Pathogens resistant to multiple antibiotics are rapidly emerging, entailing important consequences for human health. This study investigated if the broad-host-range multiresistance plasmid pB10, isolated from a wastewater treatment plant, harbouring amoxicillin, streptomycin, sulfonamide, and tetracycline resistance genes, was transferable to the foodborne pathogens Salmonella spp. or E. coli O157:H7 and how this transfer alters the phenotype of the recipients. The transfer ratio was determined by both plating and flow cytometry. Antibiotic resistance profiles were determined for both recipients and transconjugants using the disk diffusion method. For 14 of the 15 recipient strains, transconjugants were detected. Based on plating, transfer ratios were between 6.8×10-9 and 3.0×10-2 while using flow cytometry, transfer ratios were between <1.0×10-5 and 1.9×10-2.With a few exceptions, the transconjugants showed phenotypically increased resistance, indicating that most of the transferred resistance genes were expressed. In summary, we showed that an environmental plasmid can be transferred into foodborne pathogenic bacteria at high transfer ratios. However, the transfer ratio seemed to be recipient strain dependent. Moreover, the newly acquired resistance genes could turn antibiotic susceptible strains into resistant ones, paving the way to compromise human health. [ABSTRACT FROM AUTHOR]

Pellet softening reactors are used in centralized and decentralized drinking water treatment plants for the removal of calcium (hardness) through chemically induced precipitation of calcite. This is accomplished in fluidized pellet reactors, where a strong base is added to the influent to increase the pH and facilitate the process of precipitation on an added seeding material. Here we describe for the first time the opportunistic bacterial colonization of the calcite pellets in a full-scale pellet softening reactor and the functional contribution of these colonizing bacteria to the overall drinking water treatment process. ATP analysis, advanced microscopy, and community fingerprinting with denaturing gradient gel electrophoretic (DGGE) analysis were used to characterize the biomass on the pellets, while assimilable organic carbon (AOC), dissolved organic carbon, and flow cytometric analysis were used to characterize the impact of the biological processes on drinking water quality. The data revealed pellet colonization at concentrations in excess of 500 ng of ATP/g of pellet and reactor biomass concentrations as high as 220 mg of ATP/m3 of reactor, comprising a wide variety of different microorganisms. These organisms removed as much as 60% of AOC from the water during treatment, thus contributing toward the biological stabilization of the drinking water. Notably, only a small fraction (about 60,000 cells/ml) of the bacteria in the reactors was released into the effluent under normal conditions, while the majority of the bacteria colonizing the pellets were captured in the calcite structures of the pellets and were removed as a reusable product. [ABSTRACT FROM AUTHOR]

Abstract: Drinking water quality is routinely monitored in the distribution network but not inside households at the point of consumption. Fluctuating temperatures, residence times (stagnation), pipe materials and decreasing pipe diameters can promote bacterial growth in buildings. To test the influence of stagnation in households on the bacterial cell concentrations and composition, water was sampled from 10 separate households after overnight stagnation and after flushing the taps. Cell concentrations, measured by flow cytometry, increased (2–3-fold) in all water samples after stagnation. This increase was also observed in adenosine tri-phosphate (ATP) concentrations (2–18-fold) and heterotrophic plate counts (4–580-fold). An observed increase in cell biovolume and ATP-per-cell concentrations furthermore suggests that the increase in cell concentrations was due to microbial growth. After 5 min flushing of the taps, cell concentrations and water temperature decreased to the level generally found in the drinking water network. Denaturing gradient gel electrophoresis also showed a change in the microbial composition after stagnation. This study showed that water stagnation in household pipes results in considerable microbial changes. While hygienic risk was not directly assessed, it emphasizes the need for the development of good material validation methods, recommendations and spot tests for in-house water installations. However, a simple mitigation strategy would be a short flushing of taps prior to use. [ABSTRACT FROM AUTHOR]

The present study reports the disinfection effects of chemically and electrochemically dosed chlorine on two models for typical water-borne bacteria ( Escherichia coli and Legionella beliardensis) by plating and flow cytometry (FCM) in combination with different fluorescence dyes. The residual effect on various cell functions, including cultivability, esterase activity, membrane polarization, and integrity, was tested at different free chlorine concentrations. In comparison, chemical disinfection yielded on average 60% more E. coli cells entering the viable but nonculturable (VBNC) state than electrochemical disinfection. Here, VBNC is defined as those cells with intact cell membrane but which cannot be cultured on solid nutrient agar plates. L. beliardensis was about five times more resistant to chlorine disinfection than E. coli. The results also suggested the two methods result in different disinfection mechanisms on L. beliardensis, i.e., chemically dosed chlorine targeted cell membrane integrity before enzyme activity, while electrochemically dosed chlorine acted the other way round. In addition, both bacteria lost the integrity of their cell membranes at three times lower chlorine concentration over a longer contact time (i.e., 40 vs. 10 min) by the chemical method. Our results showed that FCM is an appropriate tool to evaluate the effects of water disinfection and the percentage of cells in VBNC in a matter of hours. Electrochemical disinfection is suggested to be a favorable alternative for chemical disinfection. [ABSTRACT FROM AUTHOR]

An evolutionary algorithm was used to determine the optimal combination of parameters for transconjugant formation. As a model system, a gfp tagged TOL plasmid pWW0 was chosen to examine transfer from Pseudomonas putida to Escherichia coli. A comparison of flow cytometry results with plating and microscopy showed that the majority of transconjugants were not culturable. The transconjugant ratio therefore was determined by flow cytometry. The evolutionary algorithm showed that the optimal conditions were obtained at 28°C and at the highest nutrient concentrations. This work demonstrates that evolutionary algorithms can be used to find optimal parameter interactions in environmental microbiology. [ABSTRACT FROM AUTHOR]

The ever-increasing need for high-quality drinking and process waters, and growing public awareness about possible contamination, drive efforts for the further development of automated control of water treatment plants. For example, membrane filtration processes and reverse osmosis in particular are generally regarded as a safe barrier for inorganic, organic, and microbial contamination. Yet, to ensure the final water quality and to increase the confidence of the end-user, intensive and preferably online monitoring should be further implemented as an early-warning tool to control membrane integrity and to prevent microbial regrowth in the distributing network. In this paper, we test the applicability of flow cytometry and cytometric fingerprinting for a full-scale water treatment plant. We demonstrate in a full-scale water treatment plant that flow cytometry can be used as online monitoring tool and that changes in water quality can be observed, which are not monitored by commonly used online quality parameters. Furthermore, we illustrate with ultrafiltration that process conditions impact the flow cytometric cell counts. Bacterial monitoring: Let it flow Flow cytometry can be used as an online, automated tool to monitor water quality in full-scale water treatment plants. The presence of bacteria in high concentrations in water leads to the unwanted growth of biofilms, which can damage water treatment equipment through microbiologically influenced corrosion. Biofilms can also host pathogenic bacteria, leading to water contamination upon their shedding. Monitoring microbial communities in water treatment plants is thus crucial, and a team led by Bart De Gusseme at Ghent University in Belgium demonstrate that online flow cytometry is capable of achieving this in high throughput and at single-cell resolution. Monitoring at different stages of the treatment plant, their method provides important insights into microbiological dynamics that are unattainable through commonly used online quality parameters, and additionally finds that bacterial concentrations are directly related to process operations. [ABSTRACT FROM AUTHOR]

• Flow cytometry enables real-time and near-future bioprocess performance assessment. • Chain elongation community was translated into unique cytometric fingerprints. • Based on cytometric fingerprints, several community types could be identified. • Each community type reflects a specific reactor performance and community composition. • Machine learning algorithms predict production rates of key fermentation products. 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. [Display omitted] [ABSTRACT FROM AUTHOR]

Microbial regrowth during drinking water distribution can result in a variety of problems such as a deviating taste and odor, and may even pose a risk to public health. Frequent monitoring is essential to anticipate events of biological instability, and relevant microbial parameters for operational control of biostability of drinking water should be developed. Here, online flow cytometry and derived biological metrics were used to assess the biological stability of a full-scale drinking water tower during normal and disturbed flow regime. Pronounced operational events, such as switching from drinking water source, and seasonal changes, were detected in the total cell counts, and regrowth was observed despite the short hydraulic residence time of 6–8 h. Based on the flow cytometric fingerprints, the Bray-Curtis dissimilarity was calculated and was developed as unambiguous parameter to indicate or warn for changing microbial drinking water quality during operational events. In the studied water tower, drastic microbial water quality changes were reflected in the Bray-Curtis dissimilarity, which demonstrates its use as an indicator to follow-up and detect microbial quality changes in practice. Hence, the Bray-Curtis dissimilarity can be used in an online setup as a straightforward parameter during full-scale operation of drinking water distribution, and combined with the cell concentration, it serves as an early-warning system for biological instability. Image 1 • Changes in drinking water source and loss of chlorine residual affect cell counts. • Flow cytometric fingerprinting serves as sensitive tool for monitoring biostability. • Bray-Curtis dissimilarity is developed as novel parameter for event detection. • This straightforward parameter facilitates more objective decision-making. • Combining cell counts and Bray-Curtis dissimilarity to detect water quality change. [ABSTRACT FROM AUTHOR]

Abstract Detecting disturbances in microbial communities is an important aspect of managing natural and engineered microbial communities. Here, we implemented a custom-built continuous staining device in combination with real-time flow cytometry (RT-FCM) data acquisition, which, combined with advanced FCM fingerprinting methods, presents a powerful new approach to track and quantify disturbances in aquatic microbial communities. Through this new approach we were able to resolve various natural community and single-species microbial contaminations in a flow-through drinking water reactor. Next to conventional FCM metrics, we applied metrics from a recently developed fingerprinting technique in order to gain additional insight into the microbial dynamics during these contamination events. Importantly, we found that multiple community FCM metrics based on different statistical approaches were required to fully characterize all contaminations. Furthermore we found that for accurate cell concentration measurements and accurate inference from the FCM metrics (coefficient of variation ≤ 5%), at least 1000 cells should be measured, which makes the achievable temporal resolution a function of the prevalent bacterial concentration in the system-of-interest. The integrated RT-FCM acquisition and analysis approach presented herein provides a considerable improvement in the temporal resolution by which microbial disturbances can be observed and simultaneously provides a multi-faceted toolset to characterize such disturbances. Graphical abstract Image 1 Highlights • Real-time flow cytometry is combined with advanced flow cytometric fingerprinting data analysis. • Conventional and advanced fingerprinting metrics grant complementary insights in microbial dynamics. • Guidelines for data acquisition and analysis are proposed. • RT-FCM and fingerprinting metrics extend toolset for studying microbial community disturbances. [ABSTRACT FROM AUTHOR]

Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6–52 h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (± 0.6) × 104 cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, so far for unknown reasons, recorded a slight but significantly higher TCC (1.3 (± 0.1) × 105 cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used provides a powerful and sensitive tool to assess and evaluate biological stability and microbial processes in drinking water distribution systems. [ABSTRACT FROM AUTHOR]

• Triangulation of fingerprinting methods reveals similar separation of digesters • Combining of fingerprinting features does not improve clustering of digesters • Identification of features is not always consistent between methods • Cytometric fingerprinting is reliable for anaerobic digestion microbiome monitoring 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. [ABSTRACT FROM AUTHOR]

Abstract: Application of mild inactivation treatments follows an increasing trend in the food industry and is often combined with sub-optimal intrinsic product conditions to ensure appropriate level of microbial safety. Listeria monocytogenes was subjected to mild heat treatment (20 min at 60 °C) and subsequently exposed to various mild preservation conditions based on increased NaCl concentration and decreased pH. Recovery and resuscitation of L. monocytogenes cells were studied using various methods. Using 12-fold Most Probable Number (MPN) method no difference in the amount of recovered cells under adverse conditions was noted between heat-treated and non-treated L. monocytogenes cells. Time-to-detection method using on-line OD measurements showed that heat-treated L. monocytogenes cells reached detection limit faster in acidified media and NaCl supplemented media in comparison with non-heated control cells. Flow cytometry (FCM) analysis using 5–6-carboxyfluorescein diacetate (cFDA) and propidium iodide (PI) staining showed presence of low numbers of viable cells. Overall, there was no indication of sub-lethal injury in L. monocytogenes cells after mild heat treatment. [Copyright &y& Elsevier]

Abstract: Quantifying microorganisms responsible for bioremediation can provide insight in their behavior and can help to obtain a better understanding of the physicochemical parameters monitored during bioremediation. A real time PCR (RTm PCR) assay based on the detection with SYBR Green I was optimized in order to quantify the 1,2-dichloroethane dehalorespiring Desulfitobacterium dichloroeliminans strain DCA1. A primer pair targeting unique regions of the 16 S rRNA gene was designed and tested in silico for its specificity. Selectivity was furthermore evaluated and a Limit of Quantification of 1.5·104 cells/μL DNA extract was obtained for spiked groundwater. Real time measurements of groundwater samples retrieved from a bioaugmented monitoring well and which had an average concentration lying in the range of the Limit of Quantification were evaluated positively with regards to reproducibility. Validation of the RTm PCR assay on groundwater samples originating from different sites confirmed the specificity of the designed primer pair. This RTm PCR assay can be used to survey the abundance and kinetics of strain DCA1 in in situ bioaugmentation field studies. [Copyright &y& Elsevier]