Abstract
We provide bacterial 16S rRNA community and hydrochemical data from water and sediments of Lake Neusiedl, Austria. The sediments were retrieved at 5 cm intervals from 30–40 cm push cores. The lake water community was recovered by filtration through a 3.0/0.2 µm filter sandwich. For 16S rRNA gene amplicon-based community profiling, DNA was extracted from the sediment and filters and the bacterial V3-V4 regions were amplified and sequenced using a MiSeq instrument (Illumina). The reads were quality-filtered and processed using open source bioinformatic tools, such as PEAR, cutadapt and VSEARCH. The taxonomy was assigned against the SILVA SSU NR 132 database. The bacterial community structure was visualised in relation to water and porewater chemistry data. The bacterial community in the water column is distinct from the sediment. The most abundant phyla in the sediment shift from Proteobacteria to Chloroflexota (formerly Chloroflexi). Ammonium and total alkalinity increase while sulphate concentrations in the porewater decrease. The provided data are of interest for studies targeting biogeochemical cycling in lake sediments.
Highlights
Background & SummaryLake Neusiedl is the largest, seasonally evaporative lake in western Europe covering an area of approximately 315 km[2 1]
The bacterial community composition and diversity as well as the porewater chemistry of the sediment are distinct from the water column and change gradually with depth (Fig. 1b)
While they indicate an anthropogenic impact on the sediment, the bacteria detected are based on DNA amplification and may not be metabolically active
Summary
Avril Jean Elisabeth von Hoyningen-Huene 1, Dominik Schneider 1, Dario Fussmann[2], Andreas Reimer[2], Gernot Arp 2 & Rolf Daniel 1. We provide bacterial 16S rRNA community and hydrochemical data from water and sediments of Lake Neusiedl, Austria. The lake water community was recovered by filtration through a 3.0/0.2 μm filter sandwich. For 16S rRNA gene amplicon-based community profiling, DNA was extracted from the sediment and filters and the bacterial V3-V4 regions were amplified and sequenced using a MiSeq instrument (Illumina). The reads were quality-filtered and processed using open source bioinformatic tools, such as PEAR, cutadapt and VSEARCH. The bacterial community structure was visualised in relation to water and porewater chemistry data. The bacterial community in the water column is distinct from the sediment. Ammonium and total alkalinity increase while sulphate concentrations in the porewater decrease. The provided data are of interest for studies targeting biogeochemical cycling in lake sediments
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