Evidence map›Paper›PMID 30555435›Full record

ArticleFrontiers in microbiology2018

Assessment of Microbial Community Dynamics in River Bank Filtrate Using High-Throughput Sequencing and Flow Cytometry.

Christina J Fiedler, Christoph Schönher, Philipp Proksch, David Johannes Kerschbaumer, Ernest Mayr, Marija Zunabovic-Pichler, Konrad J Domig, Reinhard Perfler

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Christina J FiedlerLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
Christoph SchönherLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
Philipp ProkschLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
David Johannes KerschbaumerLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
Ernest MayrLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
Marija Zunabovic-PichlerLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.
Konrad J DomigLaboratory of Food Microbiology and Hygiene, Institute of Food Science, Department of Food Science and Technology, University of Natural Resources and Life Sciences, Vienna, Austria.
Reinhard PerflerLaboratory of Microbiology, Institute of Sanitary Engineering and Water Pollution Control (SIG), Department of Water, Atmosphere and Environment, University of Natural Resources and Life Sciences, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surface-groundwater interactions play an important role in microbial community compositions of river bank filtrates. Surface water contaminations deriving from environmental influences are attenuated by biogeochemical processes in the hyporheic zone, which are essential for providing clean and high-quality drinking water in abstraction wells. Characterizing the flow regime of surface water into the groundwater body can provide substantial information on water quality, but complex hydraulic dynamics make predictions difficult. Thus, a bottom up approach using microbial community shifting patterns as an overall outcome of dynamic water characteristics could provide more detailed information on the influences that affect groundwater quality. The combination of high-throughput sequencing data together with flow cytometric measurements of total cell counts reveals absolute abundances among taxa, thus enhancing interpretation of bacterial dynamics. 16S rRNA high-throughput sequencing of 55 samples among six wells in a well field in Austria that is influenced by river bank filtrate within a time period of 3 months has revealed both, clear differences as well as strong similarity in microbiome compositions between wells and dates. A significant community shift from April to May occurred in four of six wells, suggesting that surface water flow regimes do affect these wells stronger than others. Triplicate sampling and subsequent sequencing of wells at different dates proved the method to be reproducible. Flow cytometric measurements of total cells indicate microbial shifts due to increased cell counts and emphasize the rise of allochthonous microorganisms. Typical freshwater bacterial lineages (Verrucomicrobia, Bacteroidetes, Actinobacteria, Cyanobacteria, Armatimonadetes) were identified as most increasing phyla during community shifts. The changes are most likely a result of increased water abstraction in the wells together with constant river water levels rather than rain events. The results provide important knowledge for future implementations of well utilization in dependency of the nearby Danube River water levels and can help drawing conclusions about the influence of surface water in the groundwater such that hygienically save and clean drinking water with a stable microbial community can be provided.

Indexed as

absolute abundancebank filtrationdrinking water qualityflow cytometrygroundwaterhigh-throughput sequencingmicrobial community compositionnext generation sequencing (NGS)

Identifiers

PMID30555435
PMCPMC6281747

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.