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

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.

Coculturing Bacteria Leads to Reduced Phenotypic Heterogeneities.

Isogenic bacterial populations are known to exhibit phenotypic heterogeneity at the single-cell level. Because of difficulties in assessing the phenotypic heterogeneity of a single taxon in a mixed community, the importance of this deeper level of organization remains relatively unknown for natural communities. In this study, we have used membrane-based microcosms that allow the probing of the phenotypic heterogeneity of a single taxon while interacting with a synthetic or natural community. Individual taxa were studied under axenic conditions, as members of a coculture with physical separation, and as a mixed culture. Phenotypic heterogeneity was assessed through both flow cytometry and Raman spectroscopy. Using this setup, we investigated the effect of microbial interactions on the individual phenotypic heterogeneities of two interacting drinking water isolates. Through flow cytometry we have demonstrated that interactions between these bacteria lead to a reduction of their individual phenotypic diversities and that this adjustment is conditional on the bacterial taxon. Single-cell Raman spectroscopy confirmed a taxon-dependent phenotypic shift due to the interaction. In conclusion, our data suggest that bacterial interactions may be a general driver of phenotypic heterogeneity in mixed microbial populations.IMPORTANCE Laboratory studies have shown the impact of phenotypic heterogeneity on the survival and functionality of isogenic populations. Because phenotypic heterogeneity plays an important role in pathogenicity and virulence, antibiotic resistance, biotechnological applications, and ecosystem properties, it is crucial to understand its influencing factors. An unanswered question is whether bacteria in mixed communities influence the phenotypic heterogeneity of their community partners. We found that coculturing bacteria leads to a reduction in their individual phenotypic heterogeneities, which led us to the hypothesis that the individual phenotypic diversity of a taxon is dependent on the community composition.

Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data.

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.

Label-free Raman characterization of bacteria calls for standardized procedures.

Raman spectroscopy has gained relevance in single-cell microbiology for its ability to detect bacterial (sub)populations in a non-destructive and label-free way. However, the Raman spectrum of a bacterium can be heavily affected by abiotic factors, which may influence the interpretation of experimental results. Additionally, there is no publicly available standard for the annotation of metadata describing sample preparation and acquisition of Raman spectra. This article explores the importance of sample manipulations when measuring bacterial subpopulations using Raman spectroscopy. Based on the results of this study and previous findings in literature we propose a Raman metadata standard that incorporates the minimum information that is required to be reported in order to correctly interpret data from Raman spectroscopy experiments. Its aim is twofold: 1) mitigate technical noise due to sample preparation and manipulation and 2) improve reproducibility in Raman spectroscopy experiments studying microbial communities.

Flow cytometric fingerprinting for microbial strain discrimination and physiological characterization.

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.

Laboratory-Scale Simulation and Real-Time Tracking of a Microbial Contamination Event and Subsequent Shock-Chlorination in Drinking Water.

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 short-term dynamics (e.g., disinfection, growth, detachment, operational changes) both in laboratory-scale research and full-scale system investigations in practice.

Flow cytometry for immediate follow-up of drinking water networks after maintenance.

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.

Reevaluating multicolor flow cytometry to assess microbial viability.

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.

Sustained accumulation of prelamin A and depletion of lamin A/C both cause oxidative stress and mitochondrial dysfunction but induce different cell fates.

The cell nucleus is structurally and functionally organized by lamins, intermediate filament proteins that form the nuclear lamina. Point mutations in genes that encode a specific subset of lamins, the A-type lamins, cause a spectrum of diseases termed laminopathies. Recent evidence points to a role for A-type lamins in intracellular redox homeostasis. To determine whether lamin A/C depletion and prelamin A accumulation differentially induce oxidative stress, we have performed a quantitative microscopy-based analysis of reactive oxygen species (ROS) levels and mitochondrial membrane potential (Δψm) in human fibroblasts subjected to sustained siRNA-mediated knockdown of LMNA and ZMPSTE24, respectively. We measured a highly significant increase in basal ROS levels and an even more prominent rise of induced ROS levels in lamin A/C depleted cells, eventually resulting in Δψm hyperpolarization and apoptosis. Depletion of ZMPSTE24 on the other hand, triggered a senescence pathway that was associated with moderately increased ROS levels and a transient Δψm depolarization. Both knockdowns were accompanied by an upregulation of several ROS detoxifying enzymes. Taken together, our data suggest that both persistent prelamin A accumulation and lamin A/C depletion elevate ROS levels, but to a different extent and with different effects on cell fate. This may contribute to the variety of disease phenotypes witnessed in laminopathies.

Artificial sweat composition to grow and sustain a mixed human axillary microbiome.

A novel artificial sweat composition, Skin Community Interaction simulation, designed to mimic the human axillary sweat, was compared to other artificial sweat compositions. Axillary microbiota grown in the novel composition closely resembled the original community. Volatile organic compound analysis showed good correlations with in vivo axillary (mal)odor components.