Ecological quality in freshwater streams is reflected across all three domains of life

Abstract

Assessment of ecological quality in streaming surface water is often based on different Biological Quality Elements (BQE) such as plants, fish or invertebrates. Conventional stream-water quality assessment based on invertebrates as BQE relies on taxonomic expertise, which is costly and time consuming. Next-generation sequencing approaches for high-throughput analyses of diverse ecosystems are increasingly used for environmental monitoring and holds a great potential for application in stream-water quality assessments. This approach is to some extent hampered by the currently available reference databases representing freshwater invertebrates. In the present study we apply metabarcoding simultaneously targeting the 16S (prokaryotes) and 18S (eukaryotes) rRNA genes to capture a snapshot of the ecosystem composition across the three domains of life. Results based on the analysis of 50 selected Danish streams showed that the combined, as well as the domain-specific profiles can separate the samples into their respective ecological quality categories as reflected by the parallel conventional assessment based on macroinvertebrates as BQE. Furthermore, it was possible to suggest potential indicator organisms, from all three domains, which correlated specifically to the conventional data e.g. organisms with a strong correlation to ecological status across all categories. The results clearly showed that community structure in all three domains of life reflect the ecological status of the sample location. Hence, when applying a molecular approach for water-quality assessment we are not limited to the composition of visible BQE, such as macroinvertebrates. The microbial community composition in the streams may often capture an even better and more comprehensive and sensitive snapshot of the ecological quality of stream waters.