Biome analysis and composition of Danish freshwater streams
One aim of the present study was to assess the merit of using
high-throughput technologies for stream water quality assessment to
increase sensitivity and simultaneously reduce labour intensity and
cost. One of the steps in conventional bioassessment protocols is
pre-treatment and sorting of the collected samples. Previous studies
have developed generalised protocols for sample collection and handling
for this purpose (Aylagas et al., 2016). Recently obtained results from
a study involving metabarcoding of stream water bodies showed that
direct sample homogenisation without pre-treatment was equally effective
for molecular analysis compared to samples that had been washed and
sorted prior to DNA extraction (Kuntke et al., 2020). The obtained
sequencing results in the present study supports the direct use of
samples without pre-treatment, as it was possible to obtain high quality
sequences to a sufficient depth for detailed biome analysis from all
three domains in 50 out of 53 samples. The omission of pre-treatment
steps from the methodology reduces the sample preparation time and the
extent of the biases associated with this process.
The obtained sequencing data was of high quality and shown to be of
sufficient sequencing depth for high resolution analysis of
domain-specific community profiles (Figure S1), with the majority of the
captured diversity originating from the bacterial communities present in
the samples (Figure 1a). This was as expected, as sediment material
makes up a large fraction of the sample, and the sediment microbiome is
one of the most complex biomes that has been studied (Battin, Besemer,
Bengtsson, Romani, & Packmann, 2016). The methodology of analysing
multiple domains for ecosystem quality studies has previously been
attempted in a study involving the use of multiple biomarkers (16S
rRNA , 18S rRNA and COI genes) and sequencing technologies
aimed to develop a framework for metasystematic analysis of bulk samples
containing arthropods (Gibson et al., 2014). The sequencing data
obtained in the present study reveal a measured diversity for all
domains that is multiple times higher than previously reported.
Furthermore, the novel approach of using a single primer set to capture
a comprehensive picture of the stream water biome simultaneously
improves data handling and comparability, and highlights the quality and
convenience of the chosen methodology.
A number of known sediment associated bacteria were detected abundantly
across samples of all qualities (Figure S2-S4), including the generaRhodoferax , Nitrospira and the familyComamonadaceae , as well as representatives of the archaeal familyNitrosospaeraceae (Battin et al., 2016). The composition of plant
life in forest ecosystems has previously been used to predict soil
microbiome profiles in grasslands, with moderate success (Leff et al.,
2018), which highlights the relationship of the soil microbes with the
flora and fauna of the ecosystem they are present in. Furthermore,
microbial community monitoring has previously been applied in the
tracking of bioremediation after oil spills in marine sediment
environments (Acosta-González & Marqués, 2016; Urakawa et al., 2012).
Moreover, the quality of the soil and its microbes has previously been
shown to function as a predictor for ecosystem health based on land
usage (Lear et al., 2013), and it can thus be suggested that measuring
the microbiome as well as the fauna and flora composition could improve
assessment resolution for quality index studies in stream waters. Not
surprisingly, a number of taxonomic groups containing organisms
previously used as indicator species for bioassessment were also
detected (Skriver et al., 2000), including representatives ofDiptera , Caenogastropoda , Mollusca andColeoptera .