Plankton biodiversity and species co-occurrence based on environmental DNA – a multiple marker study

Profiling Analysis of Filter Feeder Polypedilum (Chironomidae) Gut Contents Using eDNA Metabarcoding Following Contrasting Habitat Types-Weir and Stream

We analyzed the dietary composition of Polypedilum larvae among two contrasting habitats (river and weir). Our approach was (i) to apply eDNA-based sampling to reveal the gut content of the chironomid larvae, (ii) the diversity of gut contents in the two aquatic habitats, and (iii) assessment of habitat sediment condition with the food sources in the gut. The most abundant food was Chlorophyta in the gut of the river (20%) and weir (39%) chironomids. The average ratio of fungi, protozoa, and zooplankton in river chironomids gut was 5.9%, 7.2%, and 3.8%, while it was found decreased to 1.2%, 2.5%, and 0.1% in weir chironomids. Aerobic fungi in river midge guts were 3.6% and 10.34% in SC and IS, while they were in the range of 0.34-2.58% in weir midges. The hierarchical clustering analysis showed a relationship of environmental factors with food contents. Abiotic factors (e.g., pH) in the river and weir habitats correlated the clustered pattern with phytoplankton and minor groups of fungi. This study could help understand the food source diversity in the chironomid and habitat environmental conditions by using eDNA metabarcoding as an effective tool to determine dietary composition.

Monitoring harmful microalgal species and their appearance in Tokyo Bay, Japan, using metabarcoding

During the recent decade, high-throughput sequencing (HTS) techniques, in particular, DNA metabarcoding, have facilitated increased detection of biodiversity, including harmful algal bloom (HAB) species. In this study, the presence of HAB species and their appearance patterns were investigated by employing molecular and light microscopy-based monitoring in Tokyo Bay, Japan. The potential co-appearance patterns between the HAB species, as well as with other eukaryotes and prokaryotes were investigated using correlation and association rule-based time-series analysis. In total, 40 unique HAB species were detected, including 12 toxin-producing HAB species previously not reported from the area. More than half of the HAB species were present throughout the sampling season (summer to autumn) and no structuring or succession patterns associated with the environmental conditions could be detected. Statistically significant (p < 0.05, rS ranging from −0.88 to 0.90) associations were found amongst the HAB species and other eukaryotic and prokaryotic species, including genera containing growth-limiting bacteria. However, significant correlations between species differed amongst the years, indicating that variability in environmental conditions between the years may have a stronger influence on the microalgal community structure and interspecies interactions than the variability during the sampling season. The association rule-based time-series analysis allowed the detection of a previously reported negative relationship between Synechococcus sp. and Skeletonema sp. in nature. Overall, the results support the applicability of metabarcoding and HTS-based microalgae monitoring, as it facilitates more precise species identification compared to light microscopy, as well as provides input for investigating potential interactions amongst different species/groups through simultaneous detection of multiple species/genera.