Publications by authors named "Michael D Besmer"

8 Publications

  • Page 1 of 1

Automated Online Flow Cytometry Advances Microalgal Ecosystem Management as , High-Temporal Resolution Monitoring Tool.

Front Bioeng Biotechnol 2021 23;9:642671. Epub 2021 Mar 23.

Sustainable Food Processing Laboratory, Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland.

Microalgae are emerging as a next-generation biotechnological production system in the pharmaceutical, biofuel, and food domain. The economization of microalgal biorefineries remains a main target, where culture contamination and prokaryotic upsurge are main bottlenecks to impair culture stability, reproducibility, and consequently productivity. Automated online flow cytometry (FCM) is gaining momentum as bioprocess optimization tool, as it allows for spatial and temporal landscaping, real-time investigations of rapid microbial processes, and the assessment of intrinsic cell features. So far, automated online FCM has not been applied to microalgal ecosystems but poses a powerful technology for improving the feasibility of microalgal feedstock production through , real-time, high-temporal resolution monitoring. The study lays the foundations for an application of automated online FCM implying far-reaching applications to impel and facilitate the implementation of innovations targeting at microalgal bioprocesses optimization. It shows that emissions collected on the FL1/FL3 fluorescent channels, harnessing nucleic acid staining and chlorophyll autofluorescence, enable a simultaneous assessment (quantitative and diversity-related) of prokaryotes and industrially relevant phototrophic in mixed ecosystems of different complexity over a broad concentration range (2.2-1,002.4 cells ⋅μL). Automated online FCM combined with data analysis relying on phenotypic fingerprinting poses a powerful tool for quantitative and diversity-related population dynamics monitoring. Quantitative data assessment showed that prokaryotic growth phases in engineered and natural ecosystems were characterized by different growth speeds and distinct peaks. Diversity-related population monitoring based on phenotypic fingerprinting indicated that prokaryotic upsurge in mixed cultures was governed by the dominance of single prokaryotic species. Automated online FCM is a powerful tool for microalgal bioprocess optimization owing to its adaptability to myriad phenotypic assays and its compatibility with various cultivation systems. This allows advancing bioprocesses associated with both microalgal biomass and compound production. Hence, automated online FCM poses a viable tool with applications across multiple domains within the biobased sector relying on single cell-based value chains.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fbioe.2021.642671DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023406PMC
March 2021

Phylogenetic clustering of small low nucleic acid-content bacteria across diverse freshwater ecosystems.

ISME J 2018 05 7;12(5):1344-1359. Epub 2018 Feb 7.

Department of Environmental Microbiology, Eawag-Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.

Here we used flow cytometry (FCM) and filtration paired with amplicon sequencing to determine the abundance and composition of small low nucleic acid (LNA)-content bacteria in a variety of freshwater ecosystems. We found that FCM clusters associated with LNA-content bacteria were ubiquitous across several ecosystems, varying from 50 to 90% of aquatic bacteria. Using filter-size separation, we separated small LNA-content bacteria (passing 0.4 µm filter) from large bacteria (captured on 0.4 µm filter) and characterized communities with 16S amplicon sequencing. Small and large bacteria each represented different sub-communities within the ecosystems' community. Moreover, we were able to identify individual operational taxonomical units (OTUs) that appeared exclusively with small bacteria (434 OTUs) or exclusively with large bacteria (441 OTUs). Surprisingly, these exclusive OTUs clustered at the phylum level, with many OTUs appearing exclusively with small bacteria identified as candidate phyla (i.e. lacking cultured representatives) and symbionts. We propose that LNA-content bacteria observed with FCM encompass several previously characterized categories of bacteria (ultramicrobacteria, ultra-small bacteria, candidate phyla radiation) that share many traits including small size and metabolic dependencies on other microorganisms.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41396-018-0070-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5932017PMC
May 2018

Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water.

Front Microbiol 2017 22;8:2229. Epub 2017 Nov 22.

Department of Urban Water Management, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.

Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly). This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days), for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM). We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1) analyze any relevant event and (2) limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their current monitoring strategies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fmicb.2017.02229DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703154PMC
November 2017

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

Front Microbiol 2017 4;8:1900. Epub 2017 Oct 4.

Drinking Water Microbiology Group, Department of Environmental Microbiology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.

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 to less than 30 cells μl 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fmicb.2017.01900DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5649192PMC
October 2017

Online analysis: Deeper insights into water quality dynamics in spring water.

Sci Total Environ 2017 Dec 3;599-600:227-236. Epub 2017 May 3.

Applied and Environmental Geology, Department of Environmental Sciences, University of Basel, Basel, Switzerland.

We have studied the dynamics of water quality in three karst springs taking advantage of new technological developments that enable high-resolution measurements of bacterial load (total cell concentration: TCC) as well as online measurements of abiotic parameters. We developed a novel data analysis approach, using self-organizing maps and non-linear projection methods, to approximate the TCC dynamics using the multivariate data sets of abiotic parameter time-series, thus providing a method that could be implemented in an online water quality management system for water suppliers. The (TCC) data, obtained over several months, provided a good basis to study the microbiological dynamics in detail. Alongside the TCC measurements, online abiotic parameter time-series, including spring discharge, turbidity, spectral absorption coefficient at 254nm (SAC254) and electrical conductivity, were obtained. High-density sampling over an extended period of time, i.e. every 45min for 3months, allowed a detailed analysis of the dynamics in karst spring water quality. Substantial increases in both the TCC and the abiotic parameters followed precipitation events in the catchment area. Differences between the parameter fluctuations were only apparent when analyzed at a high temporal scale. Spring discharge was always the first to react to precipitation events in the catchment area. Lag times between the onset of precipitation and a change in discharge varied between 0.2 and 6.7h, depending on the spring and event. TCC mostly reacted second or approximately concurrent with turbidity and SAC254, whereby the fastest observed reaction in the TCC time series occurred after 2.3h. The methodological approach described here enables a better understanding of bacterial dynamics in karst springs, which can be used to estimate risks and management options to avoid contamination of the drinking water.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2017.04.204DOI Listing
December 2017

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

Sci Rep 2016 12 7;6:38462. Epub 2016 Dec 7.

Department of Environmental Microbiology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/srep38462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5141442PMC
December 2016

Short-term microbial dynamics in a drinking water plant treating groundwater with occasional high microbial loads.

Water Res 2016 Dec 18;107:11-18. Epub 2016 Oct 18.

Department of Environmental Microbiology, Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland. Electronic address:

Short-term fluctuations in bacterial concentrations in drinking water systems, occurring on time scales of hours-to-weeks, are essentially unexplored due to a lack of microbial monitoring tools that allow high frequency measurements. Here, we applied fully automated online flow cytometry to measure the total cell concentrations (TCC) in both raw water (karstic groundwater) and treated water (flocculation - ultrafiltration (UF) - ozonation - granular active carbon (GAC) filtration) during a period of 70 days at high temporal resolution (n > 4000 for both water types). We detected and characterized in considerable detail aperiodic fluctuations in the raw water following regional precipitation, with TCC increasing up to 50-fold from a dry weather baseline of approximately 120 cells μl to an event peak of > 5000 cells μl. Moreover, we observed the buffering of the treatment plant against these fluctuations, but in addition we recorded a completely unexpected periodic fluctuation of TCC in the treated water after GAC filtration. We concluded that the latter was the result of fluctuating water abstraction from the treatment plant reservoir by two connected water utilities, which resulted in variations in water throughput in the plant. This in turn influenced bacterial detachment and dilution in the GAC filter. This study provides strong evidence of multiple different microbial dynamics occurring in a drinking water treatment system. Given numerous possible sources of natural and operational fluctuations in raw water and drinking water treatment plants, such microbial fluctuations should be expected in many systems. The high-frequency monitoring approach presented herein can improve the understanding and eventual mitigation of such fluctuations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.watres.2016.10.041DOI Listing
December 2016

The feasibility of automated online flow cytometry for in-situ monitoring of microbial dynamics in aquatic ecosystems.

Front Microbiol 2014 2;5:265. Epub 2014 Jun 2.

Department of Environmental Microbiology, Eawag - Swiss Federal Institute for Aquatic Science and Technology Dübendorf, Switzerland.

Fluorescent staining coupled with flow cytometry (FCM) is often used for the monitoring, quantification and characterization of bacteria in engineered and environmental aquatic ecosystems including seawater, freshwater, drinking water, wastewater, and industrial bioreactors. However, infrequent grab sampling hampers accurate characterization and subsequent understanding of microbial dynamics in all of these ecosystems. A logic technological progression is high throughput and full automation of the sampling, staining, measurement, and data analysis steps. Here we assess the feasibility and applicability of automated FCM by means of actual data sets produced with prototype instrumentation. As proof-of-concept we demonstrate examples of microbial dynamics in (i) flowing tap water from a municipal drinking water supply network and (ii) river water from a small creek subject to two rainfall events. In both cases, automated measurements were done at 15-min intervals during 12-14 consecutive days, yielding more than 1000 individual data points for each ecosystem. The extensive data sets derived from the automated measurements allowed for the establishment of baseline data for each ecosystem, as well as for the recognition of daily variations and specific events that would most likely be missed (or miss-characterized) by infrequent sampling. In addition, the online FCM data from the river water was combined and correlated with online measurements of abiotic parameters, showing considerable potential for a better understanding of cause-and-effect relationships in aquatic ecosystems. Although several challenges remain, the successful operation of an automated online FCM system and the basic interpretation of the resulting data sets represent a breakthrough toward the eventual establishment of fully automated online microbiological monitoring technologies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fmicb.2014.00265DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4040452PMC
June 2014