Development of multi-metric eDNA-based indicators of water quality based on planktonic microorganisms

Assessing the ecological quality of inland waters is key to managing resources and guiding sustainable agriculture practices. In EU member states, the monitoring of surface waters is based on the Water Framework Directive (WFD; 2000/60/EC), which links the ecological status with anthropogenic pressures. For this, the framework introduced the biological quality elements (BQEs) that are used to establish ecological status. Among BQEs, a key element for assessing nutrient enrichment reflecting eutrophication is phytoplankton, for which several multi-metric indicators have been proposed and used for different types of lake and river water bodies. Among the metrics included in phytoplankton indicators, biomass, cyanobacterial contribution to total phytoplankton and composition are routinely integrated. However, classical phytoplankton measurements are based on the microscopic identification of several morphologically dubious taxa, cryptic and rare species, especially in the pico- and nanoplankton. Thus, eDNA high-throughput sequencing is emerging as a cost-effective, massively parallel approach to resolve morphology-based bottlenecks on phytoplankton water quality indicators. Aiming to propose and develop a multi-metric eDNA-based water quality indicator, we applied a staggered strategy using SSU rRNA gene metabarcoding of planktonic communities across lakes of different typologies in Greece and Cyprus. First, the mirroring of metabarcoding normalized abundance data, presented as relative number of reads per taxon, with conventional estimates of phytoplankton abundance and biomass was attempted. We found that correcting for unicellular eukaryotic rRNA gene copy number based on taxon-specific biovolume data provided reliable coupling of biomass-based metrics and read numbers. Then, assessment metrics were selected to reflect eutrophication conditions in the eDNA-based indicator through ecological modelling tools, including multiple linear regression models and random forest predictors. Among the tested metrics, the most fitted were the relative number of cyanobacterial reads, the dominance of bloom forming taxa, and the ratio of harmful:non-harmful groups or taxa. Using eDNA tools will further lead to the development of emerging indicators of additional quality elements, such as bacterioplankton, zooplankton, and functional diversity. Bacterial groups, albeit not included in the WFD legislation, can play key roles in nitrogen, phosphorus, and organic carbon cycling, with metabolic pathways that process many of the pollutants associated with eutrophication. Zooplankton species are the link between primary producers and higher trophic levels, containing taxa that are directly linked to eutrophication. In addition, by integrating shotgun metagenomics to resolve the underlying gene content, the functional genetic capacities of planktonic communities can be associated with environmental stressors reflecting the overall water quality. By associating phytoplankton metacommunity dynamics (composition, functional traits, and indicator taxa metrics), to hydro-ecological connectivity gradients, eDNA can provide a scalable tool for assessing ecosystem health, resilience, and the impacts of fragmentation or homogenization.