Freshwater metazoan biodiversity assessment using environmental DNA (eDNA) captured on filters offers new opportunities for water quality management. Filtering of water in the field is a logistical advantage compared to transport of water to the nearest lab, and thus, appropriate filter preservation becomes crucial for maximum DNA recovery. Here, the effect of four different filter preservation strategies, two filter types, and pre-filtration were evaluated by measuring metazoan diversity and community composition, using eDNA collected from a river and a lake ecosystem. The filters were preserved cold on ice, in ethanol, in lysis buffer and dry in silica gel. Our results show that filters preserved either dry or in lysis buffer give the most consistent community composition. In addition, mixed cellulose ester filters yield more consistent community composition than polyethersulfone filters, while the effect of pre-filtration remained ambiguous. Our study facilitates development of guidelines for aquatic community-level eDNA biomonitoring, and we advocate filtering in the field, using mixed cellulose ester filters and preserving the filters either dry or in lysis buffer.

Amplicon read sequencing has revolutionized the field of microbial diversity studies. The technique has been developed for bacterial assemblages and has undergone rigorous testing with mock communities. However, due to the great complexity of eukaryotes and the numbers of different rDNA copies, analyzing eukaryotic diversity is more demanding than analyzing bacterial or mock communities, so studies are needed that test the methods of analyses on taxonomically diverse natural communities. In this study, we used 20 samples collected from the Baltic Sea ice, slush and under-ice water to investigate three program packages (UPARSE, mothur and QIIME) and 18 different bioinformatic strategies implemented in them. Our aim was to assess the impact of the initial steps of bioinformatic strategies on the results when analyzing natural eukaryotic communities. We found significant differences among the strategies in resulting read length, number of OTUs and estimates of diversity as well as clear differences in the taxonomic composition of communities. The differences arose mainly because of the variable number of chimeric reads that passed the pre-processing steps. Singleton removal and denoising substantially lowered the number of errors. Our study showed that the initial steps of the bioinformatic amplicon read processing strategies require careful consideration before applying them to eukaryotic communities.

Over the last decade, steady advancements have been made in the use of DNA-based methods for detection of species in a wide range of ecosystems. This progress has culminated in molecular monitoring methods being employed for the detection of several species for enforceable management purposes of endangered, invasive, and illegally harvested species worldwide. However, the routine application of DNA-based methods to monitor whole communities (typically a metabarcoding approach) in order to assess the status of ecosystems continues to be limited. In aquatic ecosystems, the limited use is particularly true for macroinvertebrate communities. As part of the DNAqua-Net consortium, a structured discussion was initiated with the aim to identify potential molecular methods for freshwater macroinvertebrate community assessment and identify important knowledge gaps for their routine application. We focus on three complementary DNA sources that can be metabarcoded: 1) DNA from homogenised samples (bulk DNA), 2) DNA extracted from sample preservative (fixative DNA), and 3) environmental DNA (eDNA) from water or sediment. We provide a brief overview of metabarcoding macroinvertebrate communities from each DNA source and identify challenges for their application to routine monitoring. To advance the utilisation of DNA-based monitoring for macroinvertebrates, we propose an experimental design template for a series of methodological calibration tests. The template compares sources of DNA with the goal of identifying the effects of molecular processing steps on precision and accuracy. Furthermore, the same samples will be morphologically analysed, which will enable the benchmarking of molecular to traditional processing approaches. In doing so we hope to highlight pathways for the development of DNA-based methods for the monitoring of freshwater macroinvertebrates.

Background: Sloths are slow-moving arboreal mammals inhabiting tropical rainforests in Central and South America. The six living species of sloths are occasionally reported to display a greenish discoloration of their pelage. Trichophilus welckeri, a green algal species first described more than a century ago, is widely believed to discolor the animals fur and provide the sloth with effective camouflage. However, this phenomenon has not been explored in any detail and there is little evidence to substantiate this widely held opinion. Results: Here we investigate the genetic diversity of the eukaryotic community present in fur of all six extant species of sloth. Analysis of 71 sloth hair samples yielding 426 partial 18S rRNA gene sequences demonstrates a diverse eukaryotic microbial assemblage. Phylogenetic analysis reveals that sloth fur hosts a number of green algal species and suggests that acquisition of these organisms from the surrounding rainforest plays an important role in the discoloration of sloth fur. However, an alga corresponding to the morphological description of Trichophilus welckeri was found to be frequent and abundant on sloth fur. Phylogenetic analysis demonstrated the retention of this alga on the fur of sloths independent of geographic location. Conclusions: These results demonstrate a unique diverse microbial eukaryotic community in the fur of sloths from Central and South America. Our analysis streghtens the case for symbiosis between sloths and Trichophilus welckeri.

Characterisation of freshwater benthic biodiversity using DNA metabarcoding may allow more cost-effective environmental assessments than the current morphological-based assessment methods. DNA metabarcoding methods where sorting or pre-sorting of samples are avoided altogether are especially interesting, since the time between sampling and taxonomic identification is reduced. Due to the presence of non-target material like plants and sediments in crude samples, DNA extraction protocols become important for maximising DNA recovery and sample replicability. We sampled freshwater invertebrates from six river and lake sites and extracted DNA from homogenised bulk samples in quadruplicate subsamples, using a published method and two commercially available kits: HotSHOT approach, Qiagen DNeasy Blood & Tissue Kit and Qiagen DNeasy PowerPlant Pro Kit. The performance of the selected extraction methods was evaluated by measuring DNA yield and applying DNA metabarcoding to see if the choice of DNA extraction method affects DNA yield and metazoan diversity results. The PowerPlant Kit extractions resulted in the highest DNA yield and a strong significant correlation between sample weight and DNA yield, while the DNA yields of the Blood & Tissue Kit and HotSHOT method did not correlate with the sample weights. Metazoan diversity measures were more repeatable in samples extracted with the PowerPlant Kit compared to those extracted with the HotSHOT method or the Blood & Tissue Kit. Subsampling using Blood & Tissue Kit and HotSHOT extraction failed to describe the same community in the lake samples. Our study exemplifies that the choice of DNA extraction protocol influences the DNA yield as well as the subsequent community analysis. Based on our results, low specimen abundance samples will likely provide more stable results if specimens are sorted prior to DNA extraction and DNA metabarcoding, but the repeatability of the DNA extraction and DNA metabarcoding results was close to ideal in high specimen abundance samples.