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

ABSTRACT: 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.

SUBMITTER: Besmer MD

PROVIDER: S-EPMC4040452 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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

Besmer Michael D MD Weissbrodt David G DG Kratochvil Bradley E BE Sigrist Jürg A JA Weyland Mathias S MS Hammes Frederik F

Frontiers in microbiology 20140602

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 t ...[more]

PMID: 24917858

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Project description:High-nucleic-acid (HNA) and low-nucleic-acid (LNA) bacteria are two operational groups identified by flow cytometry (FCM) in aquatic systems. A number of reports have shown that HNA cell density correlates strongly with heterotrophic production, while LNA cell density does not. However, which taxa are specifically associated with these groups, and by extension, productivity has remained elusive. Here, we addressed this knowledge gap by using a machine learning-based variable selection approach that integrated FCM and 16S rRNA gene sequencing data collected from 14 freshwater lakes spanning a broad range in physicochemical conditions. There was a strong association between bacterial heterotrophic production and HNA absolute cell abundances (R2 = 0.65), but not with the more abundant LNA cells. This solidifies findings, mainly from marine systems, that HNA and LNA bacteria could be considered separate functional groups, the former contributing a disproportionately large share of carbon cycling. Taxa selected by the models could predict HNA and LNA absolute cell abundances at all taxonomic levels. Selected operational taxonomic units (OTUs) ranged from low to high relative abundance and were mostly lake system specific (89.5% to 99.2%). A subset of selected OTUs was associated with both LNA and HNA groups (12.5% to 33.3%), suggesting either phenotypic plasticity or within-OTU genetic and physiological heterogeneity. These findings may lead to the identification of system-specific putative ecological indicators for heterotrophic productivity. Generally, our approach allows for the association of OTUs with specific functional groups in diverse ecosystems in order to improve our understanding of (microbial) biodiversity-ecosystem functioning relationships.IMPORTANCE A major goal in microbial ecology is to understand how microbial community structure influences ecosystem functioning. Various methods to directly associate bacterial taxa to functional groups in the environment are being developed. In this study, we applied machine learning methods to relate taxonomic data obtained from marker gene surveys to functional groups identified by flow cytometry. This allowed us to identify the taxa that are associated with heterotrophic productivity in freshwater lakes and indicated that the key contributors were highly system specific, regularly rare members of the community, and that some could possibly switch between being low and high contributors. Our approach provides a promising framework to identify taxa that contribute to ecosystem functioning and can be further developed to explore microbial contributions beyond heterotrophic production.

Project description:The dynamics and activities of microbes colonizing organic particles (hereafter particles) greatly determine the efficiency of the aquatic carbon pump. Current understanding is that particle composition, structure and surface properties, determined mostly by the forming organisms and organic matter, dictate initial microbial colonization and the subsequent rapid succession events taking place as organic matter lability and nutrient content change with microbial degradation. We applied a transcriptomic approach to assess the role of stochastic events on initial microbial colonization of particles. Furthermore, we asked whether gene expression corroborates rapid changes in carbon-quality. Commonly used size fractionated filtration averages thousands of particles of different sizes, sources, and ages. To overcome this drawback, we used replicate samples consisting each of 3-4 particles of identical source and age and further evaluated the consequences of averaging 10-1000s of particles. Using flow-through rolling tanks we conducted long-term experiments at near in situ conditions minimizing the biasing effects of closed incubation approaches often referred to as "the bottle-effect." In our open flow-through rolling tank system, however, active microbial communities were highly heterogeneous despite an identical particle source, suggesting random initial colonization. Contrasting previous reports using closed incubation systems, expression of carbon utilization genes didn't change after 1 week of incubation. Consequently, we suggest that in nature, changes in particle-associated community related to carbon availability are much slower (days to weeks) due to constant supply of labile, easily degradable organic matter. Initial, random particle colonization seems to be subsequently altered by multiple organismic interactions shaping microbial community interactions and functional dynamics. Comparative analysis of thousands particles pooled togethers as well as pooled samples suggests that mechanistic studies of microbial dynamics should be done on single particles. The observed microbial heterogeneity and inter-organismic interactions may have important implications for evolution and biogeochemistry in aquatic systems.

Dataset Information

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

Publications

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

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