ABSTRACT
Reliable and comprehensive monitoring data are required to trace and counteract biodiversity loss. High-throughput metabarcoding using DNA extracted from community samples (bulk) or from water or sediment (environmental DNA) has revolutionized biomonitoring, given the capability to assess biodiversity across the tree of life rapidly with feasible effort and at a modest price. DNA metabarcoding can be upscaled to process hundreds of samples in parallel. However, while automated high-throughput analysis workflows are well-established in the medical sector, manual sample processing still predominates in biomonitoring laboratory workflows limiting the upscaling and standardization for routine monitoring applications. Here we present an automated, scalable, and reproducible metabarcoding workflow to extract DNA from bulk samples, perform PCR and library preparation on a liquid handler. Key features are the independent sample replication throughout the workflow and the use of many negative controls for quality assurance and quality control. We generated two datasets: i) a validation dataset consisting of 42 individual arthropod specimens of different species, and ii) a routine monitoring dataset consisting of 60 stream macroinvertebrate bulk samples. As a marker, we used the mitochondrial COI gene. Our results show that the developed single-deck workflow is free of laboratory-derived contamination and produces highly consistent results. Minor deviations between replicates are mostly due to stochastic differences for low abundant OTUs. Thus, we successfully demonstrated that robotic liquid handling can be used reliably from DNA extraction to final library preparation on a single deck, thereby substantially increasing throughput, reducing costs, and increasing data robustness for biodiversity assessments and monitoring.
ABSTRACT
Worldwide, multiple stressors affect stream ecosystems and frequently lead to complex and non-linear biological responses. These combined stressor effects on ecologically diverse and functionally important macroinvertebrate communities are often difficult to assess, in particular species-specific responses across many species and effects of different stressors and stressor levels in concert. A central limitation in many studies is the taxonomic resolution applied for specimen identification. DNA metabarcoding can resolve taxonomy and provide greater insights into multiple stressor effects. This was detailed by results of a recent multiple stressor mesocosm experiment, where only for the dipteran family Chironomidae 183 Operational Taxonomic Units (OTUs) could be distinguished. Numerous OTUs showed very different response patterns to multiple stressors. In this study, we applied DNA metabarcoding to assess multiple stressor effects on all non-chironomid invertebrates from the same experiment. In the experiment, we applied three stressors (increased salinity, deposited fine sediment, reduced flow velocity) in a full-factorial design. We compared stressor responses inferred through DNA metabarcoding of the mitochondrial COI gene to responses based on morphotaxonomic taxa lists. We identified 435 OTUs, of which 122 OTUs were assigned to EPT (Ephemeroptera, Plecoptera, Trichoptera) taxa. The most common 35 OTUs alone showed 15 different response patterns to the experimental manipulation, ranging from insensitivity to any applied stressor to sensitivity to single and multiple stressors. These response patterns even comprised differences within one family. The species-specific taxonomic resolution and the inferred response patterns to stressors highlights the potential of DNA metabarcoding in the context of multiple stressor research, even for well-known taxa such as EPT species.
